1
Blockchain for Internet of Things: A Survey
Hong-Ning Dai, Senior Member, IEEE, Zibin Zheng, Senior Member, IEEE, Yan Zhang, Senior Member, IEEE
Abstract— Internet of Things (IoT) is reshaping the incumbent
industry to smart industry featured with data-driven decisionmaking. However, intrinsic features of IoT result in a number of
challenges such as decentralization, poor interoperability, privacy
and security vulnerabilities. Blockchain technology brings the
opportunities in addressing the challenges of IoT. In this paper,
we investigate the integration of blockchain technology with IoT.
We name such synthesis of blockchain and IoT as Blockchain of
Things (BCoT). This paper presents an in-depth survey of BCoT
and discusses the insights of this new paradigm. In particular,
we first briefly introduce IoT and discuss the challenges of
IoT. Then we give an overview of blockchain technology. We
next concentrate on introducing the convergence of blockchain
and IoT and presenting the proposal of BCoT architecture. We
further discuss the issues about using blockchain for 5G beyond
in IoT as well as industrial applications of BCoT. Finally, we
outline the open research directions in this promising area.
Index Terms— Blockchain; Internet of Things; Smart Contract; Industrial Applications
I. I NTRODUCTION
The recent advances in information and communication
technology (ICT) have promoted the evolution of conventional
computer-aided industry to smart industry featured with datadriven decision making [1]. During this paradigm shift, Internet of Things (IoT) plays an important role of connecting the physical industrial environment to the cyberspace of
computing systems consequently forming a Cyber-Physical
System (CPS). IoT can support a wide diversity of industrial
applications such as manufacturing, logistics, food industry
and utilities. IoT aims to improve operation efficiency and
production throughput, reduce the machine downtime and
enhance product quality. In particular, IoT has the following
features: 1) decentralization of IoT systems, 2) diversity of
IoT devices and systems, 3) heterogeneity of IoT data and
4) network complexity. All of them result in the challenges
including heterogeneity of IoT system, poor interoperability,
resource constraints of IoT devices, privacy and security
vulnerabilities.
The appearance of blockchain technologies brings the opportunities in overcoming the above challenges of IoT. A
blockchain is essentially a distributed ledger spreading over
the whole distributed system. With the decentralized consensus, blockchains can enable a transaction to occur and be
validated in a mutually-distrusted distributed system without
the intervention of the trusted third party. Unlike incumbent
Corresponding authors: Zibin Zheng and Yan Zhang.
H.-N. Dai is with Faculty of Information Technology, Macau University of
Science and Technology, Macau (email: hndai@ieee.org).
Z. Zheng is with School of Data and Computer Science, Sun Yat-sen
University, China (email: zhzibin@mail.sysu.edu.cn).
Y. Zhang is with Department of Informatics, University of Oslo, Norway.
He is also with Simula Metropolitan Center for Digital Engineering, Norway
(email: yanzhang@ieee.org).
transaction-management systems where the centralized agency
needs to validate the transaction, blockchains can achieve the
decentralized validation of transactions, thereby greatly saving
the cost and mitigating the performance bottleneck at the central agency. Moreover, each transaction saved in blockchains
is essentially immutable since each node in the network keeps
all the committed transactions in the blockchain. Meanwhile,
crytographic mechanisms (such as asymmetric encryption algorithms, digital signature and hash functions) guarantee the
integrity of data blocks in the blockchains. Therefore, the
blockchains can ensure non-repudiation of transactions. In
addition, each transaction in blockchains is traceable to every
user with the attached historic timestamp.
Blockchain is essentially a perfect complement to IoT with
the improved interoperability, privacy, security, reliability and
scalability. In this paper, we investigate a new paradigm of
integrating blockchain with IoT. We name such synthesis
of blockchain and IoT as Blockchain of Things (BCoT). In
particular, BCoT has the following merits:
•
•
•
•
Interoperability across IoT devices, IoT systems and
industrial sectors, where the interoperability is the ability
of interacting with physical systems and exchanging
information between IoT systems. It can be achieved
through the blockchain-composite layer built on top of an
overlay peer-to-peer (P2P) network with uniform access
across different IoT systems.
Traceability of IoT data, where the traceability is the
capability of tracing and verifying the spatial and temporal information of a data block saved in the blockchain.
Each data block saved in a blockchain is attached with a
historic timestamp consequently assuring the data traceability.
Reliability of IoT data is the quality of IoT data being
trustworthy. It can be ensured by the integrity enforced by
crytographic mechanisms including asymmetric encryption algorithms, hash functions and digital signature, all
of which are inherent in blockchains.
Autonomic interactions of IoT system refer to the capability of IoT systems interacting with each other without the
intervention of a trusted third party. This autonomy can be
achieved by smart contracts enabled by blockchains. In
particular, contract clauses embedded in smart contracts
will be executed automatically when a certain condition
is satisfied (e.g., the user breaching the contract will be
punished with a fine automatically).
Though BCoT can benefit IoT, there are also a number of
challenges to be addressed before the potentials of BCoT can
be fully unleashed. Therefore, this paper aims to present an indepth survey on the state-of-the-art advances, challenges and
open research issues in BCoT.
2
A. Comparison between this paper and existing surveys
There are several published papers discussing the convergence of blockchain with IoT. For example, the work of
[2] presents a smart home application of using blockchains
for IoT. Zhang and Wen [3] proposed a business model to
support P2P trading based on smart contracts and blockchains.
However, these studies are too specific to a certain scenario
of incorporating blockchain with IoT (e.g., a smart home
application).
Recently, several surveys on the convergence of blockchain
with IoT have been published. In particular, [4] gives a
systematic literature review on blockchain for IoT with the
categorization of a number of use cases. The work of [5]
presents a survey on IoT security and investigates the potentials of blockchain technologies as the solutions. Reyna
et al. [6] investigated the possibility and research issues of
integrating blockchain with IoT. The work of [7] presents a
review on integrating blockchain with IoT in the application
aspect. Ref. [8] attempted to give a comprehensive survey
on application of blockchain in IoT. The work of [9] gives
a categorization of applications of blockchain for IoT.
However, most of the existing surveys suffer from the following limitations: 1) there is no general architecture proposed
for BCoT; 2) there is no study explicitly discussing blockchain
for 5G beyond networks for IoT (however, this topic is of great
importance for the development of IoT); 3) other important
issues like life cycle of smart contracts are missing in most of
the existing surveys.
B. Contributions
In view of prior work, we aim to (i) provide a conceptual introduction on IoT and blockchain technologies, (ii)
present in-depth analysis on the potentials of incorporating
blockchains into IoT and (iii) give insightful discussions of
technical challenges enabling BCoT. In summary, the main
contributions of this paper are highlighted as follows:
1) A brief introduction on IoT is first given and then
accompanied by a summary of key characteristics of IoT.
Meanwhile, research challenges of IoT are outlined.
2) An overview of key blockchain technologies is
then given with a summary of key characteristics
of blockchains and a taxonomy of the incumbent
blockchain systems.
3) The core part of this paper is focused on the convergence
of blockchain and IoT. In this respect, the opportunities
of integrating blockchain with IoT are first discussed. An
architecture of BCoT is then proposed and illustrated.
4) The 5G-beyond networks play an important role in constructing the infrastructure for BCoT. Research issues
about blockchain for 5G-beyond networks in IoT are
also discussed.
5) Furthermore, this paper summarizes the applications of
BCoT and outlines the open research issues in BCoT.
The remainder of the paper is organized as follows. Section
II first presents an overview on IoT. Section III then gives
the introduction of blockchain technology. The convergence
of blockchain and IoT is discussed in Section IV. Section
V discusses the research issues about blockchain for 5Gbeyond networks. Section VI next summarizes the applications
of BCoT. Open research issues are discussed in Section VII.
Finally, the paper is concluded in Section VIII.
II. I NTERNET OF T HINGS
In this section, we briefly introduce Internet of Things (IoT)
in Section II-A and summarize the challenges of IoT in Section
II-B.
A. Introduction to Internet of Things
Today’s industry is experiencing a paradigm shift from
conventional computer-aided industry to smart industry driven
by recently advances in Internet of Things (IoT) and Big
Data Analytics (BDA). During this evolution, IoT plays a
critical role of bridging the gap between the physical industrial
environment and the cyberspace of computing systems while
BDA can help to extract hidden values from massive IoT data
so as to make intelligent decisions.
IoT is essentially a network of smart objects (i.e., things)
with provision of various industrial services. A typical IoT
system consists of the following layered sub-systems (from
bottom to up) as shown in Fig. 1:
• Perception Layer: There is a wide diversity of IoT devices
including sensors, actuators, controllers, bar code/Quick
Response Code (QR Code) tags, RFID tags, smart meters
and other wireless/wired devices. These devices can sense
and collect data from the physical environment. Meanwhile, some of them (like actuators and controllers) can
make actions on the environment.
• Communication Layer: Various wireless/wired devices
such as sensors, RFIDs, actuators, controllers and other
tags can then connect with IoT gateways, WiFi Access
Points (APs), small base stations (BS) and macro BS
to form an industrial network. The network connection
is enabled by a diverse of communication protocols
such as Bluetooth, Near Field Communications (NFC),
Low-power Wireless Personal Area Networks (6LoWPAN), Wireless Highway Addressable Remote Transducer (WirelessHART) [10], Low Power Wide Area Networks (LPWAN) technologies including Sigfox, LoRa,
Narrowband IoT (NB-IoT) and industrial Ethernet [11].
• Industrial Applications: IoT can be widely used to support a number of industrial applications. The typical industrial applications include manufacturing, supply chain,
food industry, smart grid, health care and internet of
vehicles.
B. Challenges of Internet of Things
In this paper, we mainly focus on Industrial IoT. We denote
Industrial IoT by IoT thereafter without loss of generality.
The IoT ensures the connection of various things (smart
objects) mounted with various electronic or mechanic sensors,
actuators and software systems which can sense and collect
information from the physical environment and then make
actions on the physical environment. The unique features of
3
Industrial
Applications
Manufacturing
Communication
layer
Supply chain
Food Industry
Health care
Smart grid
Internet of Vehicles
Small BS
Macro BS
Bluetooth
IoT gateway
Small BS
WiFi AP
WiFi AP
Perception
layer
Sensor
Meter Surveillance
camera
Robot arm QR code Bar code Panel PC Portable PCs Reader
Fig. 1. Internet of Things (IoT) consists of perception layer, communication
layer and industrial applications
IoT pose a number of research challenges exhibiting in the
following aspects.
•
•
•
•
•
Heterogeneity of IoT systems exhibits in the heterogeneous IoT devices, heterogeneous communication protocols and heterogeneous IoT data types (i.e., structured,
semi-structured and nonstructured). The heterogeneity is
also the root of other challenges such as interoperability,
privacy and security (to be explained as follows).
Complexity of networks. There are a number of communication/network protocols coexisting in IoT. Typical
network protocols include NFC, Bluetooth, 6LoWPAN,
WirelessHART, Sigfox, LoRa and NB-IoT, all of which
offer different network services. For example, 6LoWPAN
and WirelessHART have typically short communication
coverage (e.g., less than 100 meters) while LPWAN
technologies can provide the coverage from 1km to 10
km [12], [13].
Poor interoperability is the capability of IoT systems
(both hardware and software) to exchange, make use of
information and collaborate with each other. Due to the
decentralization of IoT systems and the heterogeneity
of IoT systems, it is challenging to exchange the data
between different industrial sectors, strategic centers, IoT
systems. As a result, the interoperability of IoT is difficult
to be achieved.
Resource constraints of IoT devices. IoT devices such
as sensors, actuators, RFID tags and smart meters suffer
from limited resources including computing resource,
storage resource and battery power. For example, there
is no battery power for passive RFID tags that can only
harvest the energy from RFID readers or from ambient
environment [14]. Moreover, the resource constraints also
result in the vulnerability of IoT devices to malicious
attacks.
Privacy vulnerability. Privacy is to guarantee the appropriate usage of IoT data while there is no disclosure
of user private information without user consent. It is
challenging to preserve data privacy in IoT due to the
complexity and the decentralization of IoT systems, the
heterogeneity of IoT systems. Moreover, it becomes a
trend to integrate IoT with cloud computing since cloud
computing can empower IoT with extra computing and
storage capabilities. However, uploading the confidential
IoT data to the third-party cloud servers may also com-
promise the vulnerable privacy of IoT [15].
Security vulnerability. The decentralization and the heterogeneity of IoT systems also result in the difficulty in
ensuring the security of IoT while the security is extremely important for an enterprise. The typical solutions
such as authentication, authorization and communication
encryption may not be appropriate to IoT due to the difficulty in implementing the security countermeasures in
resource-constrained IoT systems. Moreover, IoT systems
are also vulnerable to malicious attacks due to the failure
of security firmware updates in time [16].
Discussion. Some intrinsic limitations of IoT can be overcome via recent ICT advances. For example, ambient backscatter assisted communications [17] can help IoT nodes obtain
extra energy from ambience. Meanwhile, mobile edge computing can extend the capability of IoT nodes via offloading
the computationally-intensive tasks to edge servers [18]. Moreover, the recent advances in blockchain technologies offer potential solutions to the challenges such as poor interoperability,
privacy and security vulnerabilities. In addition, blockchain
is also beneficial to improve heterogeneity of IoT systems.
We will discuss these opportunities brought by blockchain
to IoT in Section IV-A after giving a briefing on blockchain
technologies in Section III.
•
III. B LOCKCHAIN T ECHNOLOGIES
In this section, we first give an overview on blockchain technologies in Section III-A, then summarize the key blockchain
characteristics in Section III-B and present a taxonomy of
blockchain platforms in Section III-D.
A. Overview of Blockchain Technologies
1) Blockchain: A blockchain is essentially a distributed
ledger spreading over the whole blockchain system [19].
Fig. 2 shows an exemplary blockchain consisting of a number of consecutively-connected blocks. Each block (with the
exception of the first block) in a blockchain points to its
immediately-previous block (called parent block) via an inverse reference that is essentially the hash value of the parent
block. For example, block i contains the hash of block i − 1
as shown in Fig. 2. The first block of a blockchain is called
the genesis block having no parent block. In particular, a
block structure consists of the following information: 1) block
version (indicating the validation rules to follow), 2) the hash
of parent block, 3) Timestamp recording the current time in
seconds, 4) Nonce staring from 0 and increasing for every hash
calculation, 5) the number of transactions, 6) MerkleRoot (i.e.,
the hash value of the root of a Merkel tree with concatenating
the hash values of all the transactions in the block) as shown
in the detailed view of Fig. 2.
A blockchain is continuously growing with the transactions
being executed. When a new block is generated, all the nodes
in the network will participate in the block validation. A
validated block will be automatically appended at the end
of the blockchain via the inverse reference pointing to the
parent block. In this manner, any unauthorized alterations on
the previously-generated block can be easily detected since the
4
Hash of block j − 1
Timestamp
Nonce
Hash of block j
Timestamp
MerkleRoot
Merkle tree
structure
TX 1
TX 2
TX n
Block j
MerkleRoot
Nonce
MerkleRoot
TX 1
TX 2
TX n
Block j + 1
A shorter chain is deserted
Hash of block 0
Timestamp
Nonce
hash(TX1, TX2)
hash(TX1)
…
hash(TX2)
hash(TXn − 1, TXn)
…
hash(TXn)
Hash of block i − 1
Timestamp
MerkleRoot
TX 1
TX 2
Nonce
Hash of block i
Timestamp
MerkleRoot
TX n
TX 1
TX 2
…
TX n
TX 1
TX 2
Block i
Genesis block
Nonce
Hash of block m − 1
Timestamp
MerkleRoot
TX n
TX 1
TX 2
Block i + 1
Nonce
MerkleRoot
TX n
TX 1
TX 2
TX n
Block m
Detailed view
Fig. 2. Blockchain consists of a number of consecutively-connected blocks and the detailed view represents a Merkle tree structure (where TX represents a
transaction)
hash value of the tampered block is significantly different from
that of the unchanged block. Moreover, since the blockchain
is distributed throughout the whole network, the tampering
behavior can also be easily detected by other nodes in the
network.
Data integrity guarantee in blockchain. Blockchains leverage cryptographic techniques to guarantee data integrity. In
particular, there are two mechanisms in blockchains to ensure
the data integrity: 1) an ordered link list structure of blocks, in
which each newly-appended block must include the hash value
of the preceding block. In this manner, a falsification on any
of the previous blocks will invalidate the subsequent blocks.
2) Merkel Tree structure, in which each block contains a root
hash of a Merkel tree of all the transactions. Each non-leave
node is essentially a hash value of two concatenated values of
its two children. Therefore, a Merkel tree is typically a binary
tree. In this way, any falsification on the transactions will lead
to a new hash value in the above layer, consequently resulting
in a falsified root hash. As a result, any falsification can be
easily detected.
2) Consensus algorithms: One of the advantages of
blockchain technologies is to validate the block trustfulness in
a decentralized trustless environment without the necessity of
the trusted third-party authority. In distributed environment, it
is challenging to reach a consensus on a newly-generated block
as the consensus may be biased in favor of malicious nodes.
This trustfulness validation in a decentralized environment
can be achieved by consensus algorithms. Typical consensus
algorithms include proof of work (PoW), proof of stake (PoS)
and practical byzantine fault tolerance (PBFT) [20].
Take PoW as an example. The creation of a newly-generated
block is equivalent to the solution of a computationallydifficult problem. This computationally-difficult problem (aka
a puzzle) can nevertheless be verifiable without difficulty
[21]. Each node in the distributed peer-to-peer (P2P) network
can participate in the validation procedure. The first node
who solves the puzzle can append the validated block to the
blockchain; this node is also called a miner. It then broadcasts
the validation results in the whole blockchain system, consequently other nodes validating and updating the new results in
the blockchain. A small portion of bonus will then be given
to this node as a compensation for solving the puzzle.
Discrepancy solution. In a distributed system, multiple
nodes may validate blocks nearly at the same time. Meanwhile,
the network latency can somehow result in bifurcated (or
forked) chains at the same time. To solve the discrepancy, most
of existing blockchain systems typically maintain the longest
chain as the valid chain because the longest chain implies the
most tolerant of being compromised by adversaries. If so, a
shorter chain is automatically deserted (i.e., the blue dash-line
box as shown in Fig. 2) and the future validation work will
continue on the longest chain.
Trustfulness of PoW. The trustfulness of PoW is based on
the assumption that a majority of blockchain nodes is trustful.
Generally, 51% of computational capability is regarded as
the threshold of PoW being tolerant of malicious attacks.
The incentive mechanisms can encourage miners to be honest
against compromising. Meanwhile, solving the puzzle typically requires extensive computing power. The probability of
solving the puzzle at a miner is often proportional to the
computational capability and resource of a miner [22].
PoW schemes require extensive computation to solve the
puzzle, thereby resulting in the extensive energy consumption.
Unlike PoW, PoS requires the proof of ownership to validate
the trustfulness of a block since the users with more cryptocurrencies (i.e., more stakes) are more trustful than those
with fewer cryptocurrencies. In PBFT, each node who has the
equal right to vote for the consensus will send its voting state
to other nodes. After multiple rounds of voting procedure, the
consensus reaches.
We roughly categorize typical consensus algorithms into
two types: 1) Probabilistic consensus algorithms and 2) Deterministic consensus algorithms. Table I gives the taxonomy.
Probabilistic consensus algorithms including PoW, PoS and
Delegated proof of stake (DPOS) typically first save the
validated block to the chain and then seek the consensus of
all the nodes while deterministic consensus algorithms first
consent to the block and then saved the validated block to
the chain. Moreover, probabilistic consensus algorithms often
result in multiple bifurcate chains and the discrepancy is
solved by choosing the longest chain. In contrast, deterministic
consensus algorithms solve the discrepancy through multiple
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TABLE I
1 Transaction is initiated
TAXONOMY OF TYPICAL CONSENSUS ALGORITHMS
Bob
Alice
Probabilistic Consensus
Deterministic Consensus
Consensus
procedure
Saving first and then consenting
Consenting first and then
saving
Bifurcation
(fork)
Yes
No
Arbitration
mechanism
Adversary
tolerance
Choosing the longest chain
when there are multiple
forked chains
Transaction
2 The node broadcasts the
transaction to the P2P network
4
The validated transaction is
then appended to other
transactions to form a block
TX 1
TX 2
Forming a
block
Voting to solve discrepancy
through
multiple
communication-rounds
TX n
newly added
Hash of block i − 1
3 The P2P network validates
Timestamp
Nonce
the transcaction
MerkleRoot
< 50% computing or stakes
< 1/3 voting nodes
TX 1
TX 2
TX n
Block i
Complexity
High
computationalcomplexity
High network-complexity
Examples
PoW, PoS, DPOS
PBFT and PBFT variants,
Tendermint
rounds of communications in the overlay network.
There are many attempts to improve incumbent consensus
algorithms, such as Ripple [23], Algorand [24], Tendermint,
proof of authority (PoA) [25], proof of elapsed time (PoET)
[26]. Instead of choosing single consensus algorithm, there is
a trend of integrating multiple consensus algorithms to fulfill
the requirements from different applications.
3) Working flow of blockchains: We next show how a
blockchain works in an example. Take a money transfer as
an example as shown in Fig. 3. Alice wants to transfer an
amount of money to Bob. She first initiates the transaction
at a computer through her Bitcoin wallet (i.e., Step 1 ).
The transaction includes the information such as the sender’s
wallet, the receiver’s address and the amount of money. The
transaction is essentially signed by Alice’s private key and can
be accessible and verifiable by other users via Alice’s public
key thereafter. Then the computer broadcasts the initiated
transaction to other computers (or nodes) in the P2P network
(i.e., Step 2 ). Next, a validated transaction is then appended
to the end of the chain of transactions consequently forming a
new block in the blockchain once a miner successfully solves
the puzzle (i.e., Step 3 ). Finally, every node saves a replica
of the updated blockchain when the validated transaction is
appended to the blockchain (i.e., Step 4 ).
Fig. 3.
•
•
•
•
B. Key Characteristics of Blockchain
In summary, blockchain technologies have the following key
characteristics.
• Decentralization. In traditional transaction management
systems, the transaction validation has been conducted
through a trusted agency (e.g., a bank or government).
This centralization manner inevitably results in the extra
cost, the performance bottleneck and the single-point
failure (SPF) at centralized service providers. In contrast,
blockchain allows the transaction being validated between
two peers without the authentication, jurisdiction or intervention done by the central agency, thereby reducing
the service cost, mitigating the performance bottleneck,
lowering the SPF risk.
•
Working flow of blockchains
Immutability. A blockchain consists of a consecutivelylinked chain of blocks, in which each link is essentially
an inverse hash point of previous block. Any modification
on the previous block invalidates all the consequentlygenerated blocks. Meanwhile, the root hash of the Merkle
tree saves the hash of all the committed transactions. Any
(even tiny) changes on any transactions generates a new
Merkle root. Therefore, any falsification can be easily
detected. The integration of the inverse hash point and
the Merkle tree can guarantee the data integrity.
Non-repudiation. Recall the fact that the private key is
used to put the signature to the transaction, which can
then be accessible and verified by others via the corresponding public key. Therefore, the crytographicallysigned transaction cannot be denied by the transaction
initiator.
Transparency. For most of public blockchain systems
(like Bitcoin and Ethereum), every user can access and
interact with the blockchain network with an equal right.
Moreover, every new transaction is validated and saved
in the blockchain, consequently being available for every user. Therefore, the blockchain data is essentially
transparent to every user who can access and verify the
committed transactions in the blockchain.
Pseudonymity. Despite the transparency of blockchain
data, blockchain systems can preserve a certain level of
the privacy via making blockchain addresses anonymous.
For example, the work of [27] presents an application
of blockchain to preserve the privacy of personal data.
However, blockchain can only preserve the privacy at a
certain level since blockchain addresses are essentially
traceable by inference [8]. For example, it is shown in
[28] that the analysis of blockchain data can help to detect
fraud and illegal transactions. Therefore, blockchain can
only preserve the pseudonymity instead of full privacy.
Traceability. Each transaction saved in the blockchain is
attached with a timestamp (recorded when the transaction
occurs). Therefore, users can easily verify and trace
the origins of historical data items after analyzing the
blockchain data with corresponding timestamps.
6
Creation
Deployment
Negotiation Smart contract
Deployment Freezing assets
Execution
Evaluation
Write to
blockchain
Block 0
Block 1
Auto-execute
Write to
blockchain
Block i
Block i + 1
Completion
Updating states
Unfreezing assets
Write to
blockchain
Block m
Blockchain
Fig. 4. Life cycle of smart contracts consisting of four consecutive phases:
Creation, Deployment, Execution and Completion
C. Smart Contract
Smart contracts are a great advance for blockchain technology [29]. In 1990s, smart contracts were proposed as a
computerized transaction protocol that executes the contractual
terms of an agreement [30]. Contractual clauses that are
embedded in smart contracts will be enforced automatically
when a certain condition is satisfied (e.g., one party who
breaches the contract will be punished automatically).
Blockchains are enabling smart contracts. Essentially, smart
contracts are implemented on top of blockchains. The approved contractual clauses are converted into executable computer programs. The logical connections between contractual
clauses have also been preserved in the form of logical flows
in programs (e.g., if-else-if statement). The execution of
each contract statement is recorded as an immutable transaction stored in the blockchain. Smart contracts guarantee appropriate access control and contract enforcement. In particular,
developers can assign access permission for each function in
the contract. Contract enforcement ensures that the contract
execution is deterministic. Once any conditions in a smart contract are satisfied, the triggered statement will automatically
execute the corresponding function in a predictable manner.
For example, Alice and Bob agree on the penalty of violating
the contract. If Bob breaches the contract, the corresponding
penalty (as specified in the contract) will be automatically paid
from Bob’s deposit.
The whole life cycle of smart contracts consists of four
consecutive phases as illustrated in Fig. 4:
1) Creation of smart contracts. Several involved parties
first negotiate on the obligations, rights and prohibitions
on contracts. After multiple rounds of discussions and
negotiations, an agreement can reach. Lawyers or counselors will help parties to draft an initial contractual
agreement. Software engineers then convert this agreement written in natural languages into a smart contract
written in computer languages including declarative language and logic-based rule language [31]. Similar to
the development of computer software, the procedure
of the smart contract conversion is composed of design,
implementation and validation (i.e., testing). It is worth
mentioning that the creation of smart contracts is an
iterative process involving with multiple rounds of negotiations and iterations. Meanwhile, it is also involved
with multiple parties, such as stakeholders, lawyers and
software engineers.
2) Deployment of smart contracts. The validated smart
contracts can then be deployed to platforms on top of
blockchains. Contracts stored on the blockchains cannot
be modified due to the immutability of blockchains. Any
emendation requires the creation of a new contract. Once
the smart contracts are deployed on blockchains, all the
parties can access the contracts through the blockchains.
Moreover, digital assets of both involved parties in the
smart contract are locked via freezing the corresponding
digital wallets [32]. For example, the coin transfers
(either incoming or outgoing) on the wallets relevant
to the contract are blocked. Meanwhile, the parties can
be identified by their digital wallets.
3) Execution of smart contracts. After the deployment of
smart contracts, the contractual clauses have been monitored and evaluated. Once the contractual conditions
reach (e.g., product reception), the contractual procedures (or functions) will be automatically executed. It
is worth noting that a smart contract consisting of a
number of declarative statements with logical connections. When a condition is triggered, the corresponding
statement will be automatically executed, consequently
a transaction being executed and validated by miners in
the blockchains [33]. The committed transactions and
the updated states have been stored on the blockchains
thereafter.
4) Completion of smart contracts. After a smart contract
has been executed, new states of all involved parties
are updated. Accordingly, the transactions during the
execution of the smart contracts as well as the updated
states are stored in blockchains. Meanwhile, the digital
assets have been transferred from one party to another
party (e.g., money transfer from the buyer to the supplier). Consequently, digital assets of involved parties
have been unlocked. The smart contract has completed
the whole life cycle.
It is worth mentioning that during deployment, execution
and completion of a smart contract, a sequence of transactions
has been executed (each corresponding to a statement in the
smart contract) and stored in the blockchain. Therefore, all the
three phases need to write data to the blockchain as shown in
Fig. 4.
D. Taxonomy of Blockchain Systems
We classify blockchain systems into three types: 1) public
blockchains, 2) private blockchains and 3) consortium (or
community) blockchains [39]. Most digital currencies such as
BTC (i.e., the ticker symbol of Bitcoin cryptocurrency) and
ETH (i.e., the ticker symbol of Ethereum cryptocurrency) are
implemented on public blockchains, thereby being accessible
by anyone in the P2P network. Differently, private blockchains
can be managed or controlled by a single organization while
consortium blockchains sit in limbo between public and private
blockchains. Table II presents a comparison of three types of
blockchains.
In particular, we summary the comparison among public,
private and consortium blockchains in the following aspects.
• Key characteristics. Public blockchains are fullydecentralized while private and consortium blockchains
7
TABLE II
C OMPARISONS OF B LOCKCHAIN SYSTEMS
Public
Private
Consortium
Decentralization
Decentralized
Centralized
Partially Decentralized
Immutability
Immutable
Alterable
Partially
Immutable
Nonrepudiation
Nonrefusable
Refusable
Partially Refusable
Transparency
Transparent
Opaque
Partially Transparent
Traceability
Traceable
Traceable
Partially Traceable
Scalability
Poor
Superior
Good
Flexibility
Poor
Superior
Good
Permission
Permissionless Permissioned
Permissioned
Consensus
PoW, PoS
Ripple
PBFT, PoA, PoET
Bitcoin [34],
Ethereum
[35]
GemOS
[36],
Multichain
[37]
Hyperledger [38]
Ethereum [35]
Examples
•
•
•
•
•
are partially decentralized or fully controlled by a single
group or multiple groups. Moreover, it is nearly impossible to tamper transactions in public blockchains as every
node keeps a replica of the blockchain (containing all the
transactions) while the dominant organization or multiple
parties of consortium and private blockchains can modify
the blockchain. Similarly, public blockchains can fully
ensure the non-repudiation, transparency and traceability
of transactions while private and consortium blockchains
cannot or can only partially ensure these properties.
Scalability. Although public blockchains can guarantee the decentralization, immutability, transparency, nonrepudiation and traceability, the merits are obtained in the
cost of low transaction-validation rate, high latency and
extra storage space consumption, consequently limiting
the scalability of public blockchains. Compared with
public blockchains, private and consortium blockchains
have a better scalability since blockchains are fully controlled by a single group or multiple organizations and
the consensus can be easily reached.
Flexibility. Similarly, public blockchains have the less
flexibility than private and consortium blockchains since
configurations of private and consortium blockchains are
more adjustable.
Permission. Permission refers to consent or authorization
to access the blockchains. In public blockchains, public
participation is allowed, thereby being permissionless.
However, private and consortium blockchains can allow
one or more users to access and interact with blockchains
with different permission levels. For example, some users
can only read the blockchain data while others can either
read or initiate transactions.
Consensus. Public blockchains usually use PoW and PoS
as the consensus algorithms, which are Byzantine-failure
tolerant while resulting in extensive resource consump-
tion. Private blockchains can easily achieve the consensus
among the authenticated users. Typical consensus algorithms used for private blockchains include PBFT, PoA
and PoET. Moreover, consortium blockchains are a hybrid
type of public blockchains and private blockchains. In
particular, Ripple [23] is a variant of PBFT typically used
for consortium blockchains.
Exemplary platforms. Bitcoin [34] and Ethereum [35]
are two typical public blockchain platforms, which are
mainly used for digital currency. With regard to private blockchains, GemOS [36] is a private blockchain
platform for healthcare and supply chain. In addition,
MultiChain [37] is an open source platform granting the
implementation of private blockchains. As for consortium
blockchains, Hyperledger [38] is developing business
consortium blockchain frameworks. Moreover, Ethereum
also provides tools for building consortium blockchains
[40].
IV. C ONVERGENCE
OF
B LOCKCHAIN
AND I OT
In this section, we first discuss the opportunities of integrating blockchain with IoT in Section IV-A. We then present the
architecture of the integration of blockchain and IoT (namely
BCoT) in Section IV-B. We next discuss the deployment issues
on BCoT in Section IV-C.
A. Opportunities of integrating blockchain with IoT
As summarized in Section II-B, IoT systems are facing
many challenges such as heterogeneity of IoT systems, poor
interoperability, resource constraints of IoT devices, privacy
and security vulnerabilities. Blockchain technologies can complement IoT systems with the enhanced interoperability and
the improved privacy and security. Moreover, blockchain can
also enhance the reliability and scalability of IoT systems [6].
In short, we name such integration of blockchain with IoT as
BCoT. BCoT has the following potential benefits in contrast
to incumbent IoT systems.
• Enhanced interoperability of IoT systems. Blockchain
can essentially improve the interoperability of IoT
systems via transforming and storing IoT data into
blockchains. During this procedure, heterogeneous types
of IoT data are converted, processed, extracted, compressed and finally stored in blockchains. Moreover, the
interoperability also exhibits in easily passing through
different types of fragmented networks since blockchains
are established on top of the P2P overlay network that
supports universal internet access.
• Improved security of IoT systems. On one hand, IoT
data can be secured by blockchains since they are
stored as blockchain transactions which are encrypted and
digitally-signed by cryptographic keys (e.g., elliptic curve
digital signature algorithm [41]). Moreover, the integration of IoT systems with blockchain technologies (like
smart contracts) can help to improve the security of IoT
systems by automatically-updating IoT device firmwares
to remedy vulnerable breaches thereby improving the
system security [42].
8
Industrial
Applications
Data block
Manufacturing
Supply chain
Food Industry
Blockchain as a service
(BaaS)
Service sub-layer
Currency issue/
distribution mechanism
Blockchaincomposite layer
PoW
Propagration
protocol
Data
block
Communication
layer
Incentive sub-layer
Overlay
routing
Network sub-layer
Merkle
tree
Macro BS
Data sub-layer
PBFT
Hash
function
Cryptographic
algorithms
DPOS
Crypotograhic
algorithms
Digital signature
Hash of block 0
Timestamp
Digital
signature
Overlay network
sub-layer
Meter Surveillance
camera
•
•
Timestamp
Hash of block
Nonce
Timestamp
Nonce
Block
Blockchain
Blockchain node architecture
WiFi AP
IoT gateway
WiFi AP
Macro BS
Small BS
WiFi AP
Meter
Sensor
Sensor
Robot arm QR code Bar code Panel PC Portable PCs Reader
(a) Blockchain-composite layer
Fig. 5.
Data store
Has o
Nonce
Genesis block
Communication
layer
Small BS
Perception
layer
Sensor
Merkle tree
Hash function
Transaction
cost (fee)
Verification
mechanism
Bluetooth
IoT gateway
Peer
Smart contracts
Consensus sub-layer
Chain
structure
Chain structure
Internet of Vehicles
Reward
mechanism
PoS
Small BS
Perception
layer
Health care
Smart grid
Meter
Robot arm
Reader
(b) P2P overlay network and blockchain node architecture
Overview of BCoT architecture
Traceability and Reliability of IoT data. Blockchain data
can be identified and verified anywhere and anytime.
Meanwhile, all the historical transactions stored in the
blockchains are traceable. For example, the work of [43]
has developed a blockchain-based product traceability
system, which provide suppliers and retailers with traceable services. In this manner, the quality and originality of
the products can be inspected and verified. Moreover, the
immutability of blockchains also assures the reliability of
IoT data since it is nearly impossible to alter or falsify
any transactions stored in blockchains.
Autonomic interactions of IoT systems. Blockchain technologies can grant IoT devices or subsystems to interact
with each other automatically. For example, the work
of [44] proposes Distributed autonomous Corporations
(DACs) to automate transactions, in which there are no
traditional roles like governments or companies involved
with the payment. Being implemented by smart contracts,
DACs can work automatically without human intervention consequently saving the cost.
2)
3)
B. Architecture of Blockchain of Things
We propose the architecture of BCoT as shown in Fig. 5.
In this architecture, the blockchain-composite layer plays as
a middleware between IoT and industrial applications. This
design has two merits: 1) offering an abstraction from the
lower layers in IoT and 2) providing users with blockchainbased services. In particular, the blockchain-composite layer
hides the heterogeneity of lower layers (like perception layer
and communication layer in IoT). On the other hand, the
blockchain-composite layer offers a number of blockchainbased services, which are essentially application programming
interfaces (APIs) to support various industrial applications. As
a result, the difficulty of developing industrial applications can
also be lowered down due to the abstraction achieved by the
blockchain-composite layer.
In particular, the blockchain-composite layer consists of 5
sub-layers as shown in Fig. 5(a) (from bottom to up):
1) Data sub-layer collects the IoT data from the lower layers (e.g., perception layer) and wraps up the encrypted
4)
5)
data with digital signature via asymmetric cryptographic
algorithms and hash functions. These consecutivelyconnected data blocks then form the blockchain after
the distributed validation. Different blockchain platforms
may choose different cryptographic algorithms and hash
functions. For example, Bitcoin blockchain chooses
SHA-256 as the hash function and elliptic curve digital
signature algorithm (ECDSA) as the signature algorithm.
Network sub-layer is essentially an overlay P2P network running on top of the communication layer. The
overlay network consists of either virtual or physical
links connecting nodes in the underlying communication
networks (i.e., wired/wireless communication networks).
One node only simply broadcasts the block of transactions to its connected peers. Once receiving the block
of transactions, other peers will verify it locally. If it
is valid, the block will be further propagated to other
nodes through the overlay network.
Consensus sub-layer is mainly involved with the distributed consensus for the trustfulness of a block. The
consensus can be achieved by various consensus algorithms like PoW, PoS, PBFT and DPOS (as explained
in Section III-A.2). It is worth mentioning that block
propagation mechanisms (such as relay network propagration and advertisement-based propagation [21]) are
the prerequisite for the distributed consensus protocols.
Incentive sub-layer is responsible for the following
tasks: 1) digital currency issuing, 2) digital currency distribution, 3) designing reward mechanism (especially for
miners), 4) handling transaction cost, etc. In particular,
it is important to design appropriate monetary policy of
digital currency (i.e., money creation and distribution),
distribute rewards to participants who contribute to distributed consensus (i.e., mining).
Service sub-layer provides users with blockchain-based
services for various industrial sectors include manufacturing, logistics, supply chains, food industry and
utilities. The blockchain as a service (BaaS) can be
achieved by smart contracts, which can be automatically
triggered when a special event occurs. For example,
9
Wired link
Wireless link
MEC server
Cloud server
Blockchain
Cloud server
Meter
MBS
Blockchain
D2
617d48c9
Dl
ink
617d48c9
Partial (hash) of
Partial (hash) of
blockchain
blockchain
Partial (hash) of
blockchain
617d48c9
Fig. 6.
IoT gateway
SBS
Blockchain
Blockchain
617d48c9
Partial (hash) of
blockchain
sensor
Partial (hash) of
blockchain
617d48c9
Deployment scenario of BCoT
a payment contract is automatically executed when a
product is well received by a consumer.
It is worth mentioning that the network sub-layer that is
established on top of the communication layer is the abstraction of underneath communication networks, consequently
offering a universal network access across different networks
as shown in Fig. 5(b). Fig. 5(b) also shows the architecture of
a blockchain node, which essentially includes blockchain data
and other elements in the data sub-layer.
C. Deployment of BCoT
The realistic deployment of BCoT is of great importance.
However, due to the constraints of IoT devices, it is challenging to store the whole blockchain at IoT devices. In particular,
there are two modes to store the blockchain data [6]: i) full
storage, in which the entire blockchain is stored, ii) partial
storage, in which only a subset of data blocks are stored
locally. Accordingly, we name the nodes with full storage
of blockchain data as full nodes and the nodes with partial
storage of blockchain data as lightweight nodes. In practice,
a full node can be a cloud server or an edge server with
adequate computing resources since it requires a large storage
space to save the entire blockchain (e.g., the whole Bitcoin
blockchain occupies nearly 185 GB at the end of September
2018 according to the statistic report1 ) and strong computing
capability of solving consensus puzzles (i.e., mining). On the
other hand, resource-constrained IoT devices (e.g., sensors,
IoT objects) can be lightweight nodes that can validate the
trustfulness of a transaction without downloading or saving
the whole blockchain (i.e., only saving partial blockchain
data such as hash values). It is worth mentioning that the
lightweight nodes highly rely on the full nodes.
Fig. 6 presents a possible deployment scenario of BCoT,
in which cloud servers and edge servers may store the whole
blockchain (or partial blockchain) data while IoT devices may
1 https://www.statista.com/statistics/647523/worldwide-bitcoin-blockchainsize/
only save the particial blockchain data. In addition to the
deployment of BCoT, there are also several possible interaction
manners between IoT and blockchain [8]: (i) direct interaction
between IoT and blockchain, in which IoT devices can directly
access blockchain data saved at edge servers co-located with
IoT gateways, Macro Base Stations (MBS) or Small BS; (ii)
direct interaction between IoT nodes, in which IoT nodes
can directly exchange/access partial blockchain data via D2D
links; (iii) hybrid interaction of cloud and edge servers with
IoT devices, in which IoT devices can interact with blockchain
data through edge/cloud servers.
There are several initiatives addressing the configuration
and initialization of blockchain at edge servers or at IoT
devices. For example, Raspnode2 is a project mainly for
installing Bitcoin and other blockchains at Raspberry Pi micro
computers. EthArmbian3 offers the customized Ubuntu Linux
image for ARM devices, each of which can serve as an
Ethereum node. Despite these initiatives, most of IoT devices
are still lightweight nodes due to the limited storage.
V. B LOCKCHAIN
FOR
5G B EYOND
IN I OT
Although blockchain technology is promising to IoT, there
are still many research issues to be addressed before the
integration of blockchain with IoT, especially for the nextgeneration networks (i.e., 5G-beyond or 6G networks), which
play a critical role in constructing the infrastructure for
blockchains. Fig. 7 illustrates the potentials brought by
blockchain to 5G-beyond networks in the perspectives from
communications, network management and computing management. We explain them in details as follows.
A. Blockchain for communications
The growing demands of mobile data traffic are driving the
more efficient resource management in the fifth generation
(5G) communication systems. For example, radio spectrum
2 http://raspnode.com/
3 http://raspnode.com/
10
Computing Management
Storage (cache)
management
Computing resource
Management
Cloud server
MEC Server
Storage
Storage
Network Management
SDN Control
Software
Network
Virtualization
Network
Slicing
Network device
Network device
Performance
control
Network device
Network controller
Commmunication Management
Spectrum
Management
Service
Management
Macro BS
Small BS
Block 0
IoT gateway
Small BS
Fig. 7.
WiFi AP
Block i
Block i + 1
Block m
Blockchain
Blockchain for 5G Beyond Networks in IoT
is one of the most important resources [45]. Radio spectrum
management typically includes spectrum auction and spectrum
sharing. It is shown in the latest speech [46] given by Federal
Communications Commission (FCC) commissioner J. Rosenworcel that blockchain technology could be used to achieve
the dynamic and secure spectrum management in 5G and
5G beyond (aka 6G) communication systems [47], [48]. The
benefits of using blockchains for 5G-beyond networks lie in
the secure and traceable transaction-management without the
necessity of a central intermediary, consequently saving the
management cost. Ref. [49] gives several use cases to illustrate
that using blockchain technology can benefit radio spectrum
sharing in terms of trustfulness, consensus and cost reduction.
Moreover, Kotobi and Bilen [50] put forth a blockchain-based
protocol to secure spectrum sharing between primary users and
cognitive users in wireless communication systems. In addition, blockchain may potentially help to share link conditions
to multiple IoT nodes with privacy preservation consequently
improving spectral efficiency via traffic optimization [51].
In addition to the radio spectrum management, blockchains
also have the potentials to provide users with the improved
mobile services. For example, 5G networks typically consist of
a number of fragmented heterogeneous networks. Blockchains
that are built on top of the network layer can help to integrate
different networks with the provision of seamless access
between different networks. Moreover, smart contracts can
automate the procedure of provisions and agreements between
network operators and subscribers while operational cost can
be greatly saved [52]. The work of [53] also shows that a
blockchain-based system can help operating nodes to improve
their operational and service capabilities. In the future, the
synthesis of blockchains and big data analytics can help
service providers to extract valuable insights from transactions
of subscribers and offer the better services for users.
B. Blockchain for network management
Recently, software defined networking (SDN) technology
can bestow the flexibility and scalability for distributed IoT
[54]. However, it is shown in [55] that the centralization
of SDN can also result in the single-point-of-failure. Moreover, incumbent SDN devices (such as gateways) are also
incapable of conducting computational-intensive analysis on
data traffic. The integration of blockchain technology with
SDN can overcome the disadvantages of SDN. For example,
the work of [56] proposes a secure blockchain-based SDN
framework for IoT. In particular, a blockchain-based scheme
has been developed to update the flow rule table in a secure
way without the necessity of the intermediary. In addition,
blockchain can also help to secure the network management
of network function visualization (NFV). In particular, it is
shown in [57] that the integration of blockchain with NFV can
ensure that the configuration of NFV is immutable, auditable,
non-repudiable, consistent and anonymous. A prototype of the
proposed architecture was also developed and implemented in
this work.
In addition to SDN and NFV, the appearance of network
slicing technologies [58] brings the agility and flexibility
of networks to support different functional and performance
requirements. As mentioned in Section IV, different industrial
sectors have diverse application demands on blockchains. For
example, a single blockchain is typically used in digitalcurrency like applications while an enterprise may maintain several blockchains to serve for different purposes. In
particular, four isolated blockchains are dedicate to Enterprise resource planning (ERP), Product Lifecycle Management (PLM), Manufacturing execution systems (MES) and
Customer Relationship Management (CRM), respectively [59].
Network slicing can essentially offer a solution to the diverse
demands of blockchain applications in mobile edge computing.
For example, each of network instances can be created for the
provision of a specific blockchain service on top of network
slicing and network visualization. However, it is necessary to
optimize and allocate both network and computing resources
to fulfill the diverse demands in the composite environment
of mobile edge computing and cloud computing. Moreover,
the integration of blockchain and network slicing technologies
11
Smart manufacturing
can also support the reliable content sharing in content-centric
networks (CCNs) [60] and privacy preservation in data sharing
in 5G networks [61].
Raw material
Factory
Supply chain
Retailer
Distribution
C. Blockchain for computing management
Due to the resource constraints of IoT devices, massive IoT
data has been typically uploaded to remote cloud servers for
further processing. However, the pure cloud-based computing
paradigm also causes the network traffic bottlenecks, long latency, context unawareness and privacy exposure [62], thereby
limiting the scalability of IoT. Recently, Mobile Edge Computing (MEC) [63] is becoming a crucial complement to cloud
computing by offloading computing tasks from distant cloud
servers to MEC servers typically installed at IoT gateways,
WiFi APs, Macro BS and Small BS, which are close to users.
In this manner, the context-aware, latency-critical and lesscomputing-intensive tasks can be migrated from remote cloud
servers to local MEC servers, thereby improving the response,
privacy-preservation and context-awareness.
Blockchain technology has been applied in a variety of
fields due to its capability of establishing trust in a decentralized fashion. There are still a number of issues needed
to be solved before MEC can be used in BCoT [64]. In
contrast to cloud servers with strong computing capability
and extensive storage space, mobile edge servers usually
have inferior capability. Moreover, mobile edge servers are
heterogeneous in terms of computing capability, main memory,
storage space and network connection. As a result, mobile
edge servers cannot accommodate the computational demands
alone. For example, a mobile edge server may not be able
to solve the consensus puzzle in blockchains while a cloud
server can serve for this goal. Therefore, it is worthwhile to
investigate the orchestration of mobile edge computing and
cloud computing for the provision of blockchain services [65].
D. Orchestration of cloud and edge computing with
blockchain
During the orchestration of cloud and edge computing with
blockchain, there are several challenges including computational task offloading and incentivizing resource sharing.
Offloading the computational tasks to edge servers can significantly reduce the delay. Therefore, it is crucial to conduct
edge-cloud interoperation [66]. Nevertheless, it can cause a
performance bottleneck and a single-point-of-failure if all the
nodes offload their tasks to the same MEC server. The work
of [67] presents an offloading method with consideration of
load balancing among multiple MEC servers. Meanwhile, it is
worthwhile to investigate how to incentivize both edge severs
and cloud servers. For example, [68] presents a contract-match
approach to allocate computational resource and assign tasks
while incentivizing edge severs and cloud servers effectively.
Moreover, it is challenging to design an optimal solution to the
offloading tasks with consideration of spectrum, computation
and energy consumption together. The work of [69] essentially
provides a solution to optimize the offloading energy consumption with consideration of feasible modulation schemes
and tasks scheduling. However, most of existing studies only
Food industry
Smart grid
Power plant
Smart meter
sensor
Blockchain of Things
Transmission Renewable energy
Internet of Vehicles
and UAV
Health care
UAV
RSU
Fig. 8.
Applications of Blockchain of Things
consider a task is either done at an edge sever or at a cloud.
In realistic application, a task can be partitioned into multiple
sub-tasks with task dependency and those sub-tasks can be
either executed at the edge server or at the cloud server. It is
worthwhile to investigate the task partition with consideration
of sub-task dependency in blockchains in the future.
VI. A PPLICATIONS
OF
B LOCKCHAIN
OF
T HINGS
There is a growing trend in applying blockchain in IoT since
blockchain technologies can help to overcome the challenges
of IoT. We then provide an overview of the applications of
BCoT. It is worth mentioning that there is a wide diversity of
applications of blockchains (ranging from smart manufacturing
to internet of vehicles and unmanned aerial vehicles). In this
paper, we mainly focus on the industrial applications of BCoT.
We roughly categorize the applications of BCoT into six types
as shown in Fig. 8.
A. Smart manufacturing
The manufacturing industry is experiencing an upgrading
from automated manufacturing to “smart manufacturing” [70].
Big data analytics on manufacturing data plays an important
role during this upgrading process. Massive data is generated
during every phase of the product life cycle consisting of
product designing, raw material supply, manufacturing, distribution, retail and after-sales service. However, the manufacturing data is highly fragmented, consequently leading to
the difficulty in data aggregation and data analytics. BCoT
can address the interoperability issue by interconnecting IoT
systems via P2P network and allowing data sharing across
industrial sectors. For example, several distributed blockchains
can be constructed to serve for different sectors and each
blockchain is serving for a sector or more than one sector.
BCoT can also improve the security of smart manufacturing. One of major bottlenecks limiting the upgrading of
factories is that the IoT systems have been maintained in
12
a centralized way. For example, IoT firmware needs to be
upgraded regularly to remedy security breaches. However,
most of the firmware updates are downloaded from a central
server and then are manually installed at IoT devices. It is
expensive and in-efficient to install and upgrade the firmware
updates in distributed IoT. The work of [42] presents an
automatic firmware upgrading solution based on smart contract
and blockchains. In particular, smart contracts describing the
firmware upgrading manners (e.g., when and where to upgrade
firmwares) are deployed across the whole industrial network.
Devices can then download and install the firmware hashes via
smart contracts being automatically executed. As a result, the
security maintenance cost can be greatly saved. In addition, a
decentralized blockchain-based automatic production platform
was proposed in [71] to offer a better security and privacy
protection than conventional centralized architecture.
B. Supply chain management
A product often consists of multiple parts provided by different manufacturers across countries. However, some forged
(or low-quality) parts may seep into the supply chain. It is
quite expensive to apply anti-fraud technologies in every part
of a product. The integration of blockchain and IoT can solve
this problem. In particular, every part will be associated with
a unique ID with the creation. Meanwhile, an immutable
timestamp is also attached with this ID. The identification
of every part can then be saved into a blockchain, which is
tamper-resistant and traceable. For example, the work of [72]
shows that the part ownership of a product can be authenticated
through a blockchain-based system. Moreover, the work of
[73] presents a traceability ontology with the integration of IoT
and blockchain technologies based on Ethereum blockchain
platform. The proposed framework has demonstrated to guarantee data provenance of supply chain.
On the other hand, BCoT can also be used to reduce the
costs in after-sale services in the supply chain management.
The work of [74] shows a user case of a motor insurance,
in which the settlement of claims can be automated via
smart contracts based on blockchains, thereby improving the
efficiency and reducing the claim-processing time. Moreover,
it is shown in [75] that integrating blockchain with IoT can
help to reduce the cost, fasten the speed and reduce the risk
in the supply chain management. Furthermore, a blockchainbased Machine Learning platform [76] was proposed to secure
the data sharing among different enterprises to improve the
quality of customer service.
During this procedure, blockchain technologies can ensure the
traceability and the provenance of food industry data.
There are several proposals in this aspect. For example, the
work of [78] proposed to use RFID and blockchain technology
to establish a supply chain platform from agriculture to food
production in China. This system has demonstrated to guarantee the traceability of food supply-chain data. Meanwhile,
the work of [79] shows that blockchain technologies can help
to improve food safety via the provision of the traceable food
products. Moreover, it is shown in [80] that the integration of
blockchain in food supply chain can allow customers to track
the whole process of food production. Authors also gave a
user case of using blockchain for the organic coffee industry
in Colombian. Furthermore, [81] proposes a food safety traceability system based on the blockchain and Electronic Product
Code (EPC) IoT tags. In particular, this system can prevent
data tampering and privacy exposure via smart contracts. A
prototype of the proposed architecture has been implemented
to demonstrate the effectiveness.
D. Smart grid
The appearance of distributed renewable energy resources is
reshaping the role of energy consumers from pure consumers
to prosumers who can also generate energy (e.g., from renewable energy resources) in addition to consuming energy
only [82]. Energy prosumers who have extra energy can sell
it to other consumers. We name the energy trading between a
prosumer and a consumer (i.e., peers) as P2P energy trading.
However, it is challenging to ensure the secured and trusted
energy trading between two trading parties in the distributed
environment.
The appearance of blockchain technology brings the opportunities to ensure the secured P2P energy trading. Some
of recent studies proposed using blockchain technologies to
tackle these challenges. For example, the work in [83] developed a secure energy trading system based on consortium
blockchains. This system can greatly save the trading cost
without going through a central broker via the distributed
consensus of blockchains. Moreover, Aitzhan and Svetinovic
[84] developed a decentralized energy-trading system based on
blockchain technology. This system demonstrated the effectiveness in protecting confidential energy-trading transaction
in decentralized smart grid systems. Furthermore, the work
of [85] proposed a blockchain based mechanism to provide
a secure and transparent energy demand-side management on
smart grid.
E. Health care
C. Food industry
BCoT can enhance the visibility of the product life cycle
especially in food industry. In particular, the traceability of
food products is a necessity to ensure food safety. However,
it is challenging for the incumbent IoT to guarantee the food
traceability in the whole food supply chain [77]. For example,
a food company may be provisioned by a number of suppliers.
The traceability requires digitizing the information of raw
materials from sources to every sector of food manufacturing.
Health care becomes one of the major social-economic
problems due to the aging population; it poses new challenges in traditional healthcare services because of the limited
hospital resources. The recent advances in wearable healthcare devices as well as BDA in health-care data bring the
opportunities in promoting the remote health-care services at
home or at clinic. As a result, the burden of the hospital
resources can be potentially released [86]. For example, senior
citizens staying at their homes are wearing the health-care
13
devices at their bodies. These wearable devices continuously
measure and collect health-care data including heart beat
rate, blood sugar and blood pressure readings. Doctors and
health-care teams can access health-care data at any time and
anywhere via the health-care networks. However, assessing
health-care data also brings privacy and security concerns. The
vulnerability of health-care devices and the heterogeneity of
health-care networks pose the challenges in preserving privacy
an ensuring security of health-care data.
Incorporating blockchains into health-care networks can
potentially overcome the challenges in privacy preservation
and security assurance of health-care data. For example, the
work of [87] shows that using blockchain technology can
protect health-care data stored in cloud servers. Meanwhile,
Griggs et al. [88] developed a blockchain-based system to
assure the private health-care data management. In particular,
the health-care data generated by medical sensors can be
automatically collected and transmitted to the system via executing smart contracts, consequently supporting the real-time
patient monitoring. During the whole procedure, the privacy
can be preserved via underneath blockchains. Moreover, the
work of [89] proposed a blockchain-based solution to manage
individual health-care data and support data-sharing across
different hospitals, medical centers, insurance companies and
patients. During the whole process, the privacy and security of
health-care data can be assured. Furthermore, Sun et al. [90]
put forth an attribute-based signature scheme in decentralized
health-care blockchain systems. On one hand, this scheme can
verify the authenticity of health-care data and identification of
the health-care data owner. On the other hand, this scheme can
also preserve the privacy of the health-care data owner. The
recent work [91] presents an in-home therapy management
framework integrating IoT and blockchain-based MEC scheme
to provide secrecy and anonymity assurance. The experimental
results on a prototype demonstrate the effectiveness of the
proposed system.
F. Internet of vehicles and unmanned aerial vehicles
Internet of vehicles (IoV) essentially integrates vehicleto-vehicle networks, vehicle-to-roadside networks, vehicle-toinfrastructure networks and vehicle-to-pedestrian networks.
The decentralization, heterogeneity and non-trustworthiness
of IoV pose the challenges in securing message-transmission
and transaction-execution. Integrating blockchain with IoV
can tackle the above challenges. For example, the work of
[92] developed a trust-management platform in IoV on top
of blockchains. In particular, the trustworthiness of messages
can be validated via PoW/PoS consensus executed by Roadside Units (RSUs). Moreover, blockchain tehcnologies can be
used to protect both the energy and information interactions
between electric vehicles [93] and hybrid electric vehicles in
smart grids [94], [95]. In the future, incorporating artificial intelligence, mobile edge computing and blockchain can further
optimize the resource allocation in IoVs [96].
Recently, unmanned aerial vehicles (UAVs) communication
networks can compensate in-sufficient coverage of wireless
communication networks [97]. Meanwhile, UAVs can also be
TABLE III
C OMPARISON OF APPLICATIONS OF BLOCKCHAIN OF THINGS
Application
Benefits
Smart manufacturing
[42], [70], [71]
XImproving interoperability
XAutomating P2P business trading
XReducing cost for trusted third party
XAssuring data provenance
Supply chain
management [72]–[76]
XReducing the costs in after-sale services
XMitigating the supply chain risk
Food industry [77]–[81]
XImproving data traceability
XEnhancing food safety
XSecuring energy trading
Smart grid [82]–[85]
XImproving transparency
XPreserving privacy
XAssuring security
Health care [86]–[91]
XPreserving privacy
XVerifying authenticity
XAssuring trustworthiness of messages
IoV and UAVs
[92]–[102]
XSecuring energy-trading in electric vehicles
XGuaranteeing mutual-confidence among UAVs
used to deliver product items [98] and acquire real-time traffic
flow data [99]. Moreover, the recent study of [100] also shows
that UAVs can be used to support content-centric networking
and mobile edge computing. However, it is challenging to
assure the trustworthiness in decentralized non-trusted UAVnetworks and restrict the misbehaving UAVs [103]. The integration of blockchain technology with UAV-networks can
guarantee the mutual-confidence among UAVs. The work of
[101] developed an autonomous platform based on Ethereum
blockchain to provide the trust-management of UAVs. Moreover, IBM [102] recently applied for a patent to develop
a blockchain-based system to preserve privacy and assure
security of UAV data. In particular, blocks in blockchains will
store the information related to UAVs including model type,
manufacturer, proximity to restricted region. Consequently, the
misbehavior of UAVs can be detected and identified in time.
Summary. Table III summarizes major BCoT applications.
In particular, it is shown in Table III that incorporating
blockchain with IoT can bring a number of benefits in the
aforementioned applications. In summary, BCoT has merits
like reducing the cost for trusted third party, assuring security,
improving data traceability, verifying the data authenticity and
preserving privacy.
VII. O PEN RESEARCH
ISSUES OF
B LOCKCHAIN
OF
T HINGS
Although the convergence of blockchain and IoT brings a
number opportunities in upgrading the industry, there are many
challenges to be addressed before the potentials of BCoT can
be fully unleashed. In this section, we identify several major
challenges in incorporating blockchain into IoT and discuss
the potential solutions. Fig. 9 summarizes the open research
issues for blockchain of things.
14
Fig. 9.
Open research issues for blockchain of things
A. Resource constraints
Most of IoT devices are resource-constrained. For example,
sensors, RFID tags and smart meters have inferior computing
capability, limited storage space, low battery power and poor
network connection capability. However, the decentralized
consensus algorithms of blockchains often require extensive
computing power and energy consumption. For example, PoW
in Bitcoin is shown to have high energy consumption [6].
Therefore, the consensus mechanisms with huge energy consumption may not be feasible to low-power IoT devices.
On the other hand, the bulky size of blockchain data also
results in infeasibility of fully deploying blockchains across
IoT. For example, the Bitcoin blockchain size almost reaches
185 GB by the end of September 2018. It is impossible to fully
store the whole blockchain at each IoT device. Meanwhile, the
massive IoT data generated in nearly real time manner makes
this status quo even worse. Moreover, blockchains are mainly
designed for a scenario with the stable network connection,
which may not be feasible for IoT that often suffers from
the poor network connection of IoT devices and the unstable
network due to the failure of nodes (e.g., battery depletion).
Potential solutions. Incorporating MEC and cloud computing technologies into BCoT may potentially overcome
resource constraints of IoT devices. For example, cloud servers
or some MEC servers may serve as full nodes that store the
whole blockchain data and participate in most of blockchain
operations, such as initiating transactions, validating transactions (i.e., mining) while IoT devices may serve as lightweight
nodes that only store partial blockchain data (even hash value
of blockchain data) and undertake some less-computationalintensive tasks (such as initiating transactions) [104]. The
orchestration of MEC and cloud computing becomes an important issue in the sense of allocating resource in BCoT [105].
B. Security vulnerability
Although incorporating blockchain technologies into IoT
can improve the security of IoT via the encryption and digital
signature brought by blockchains, the security is still a major
concern for BCoT due to the vulnerabilities of IoT systems
and blockchain systems.
On one hand, there is a growing trend in deploying wireless
networks into industrial environment due to the feasibility
and scalability of wireless communication systems. However, the open wireless medium also makes IoT suffering
from the security breaches such as passive eavesdropping
[106], jamming, replaying attacks [107]. Moreover, due to
the resource constraints of IoT devices, conventional heavyweighted encryption algorithms may not be feasible to IoT
[108]. In addition, it is also challenging to manage the keys
(which are crucial to encryption algorithms) in distributed
environment.
Meanwhile, blockchain systems also have their own security
vulnerabilities such as program defects of smart contracts [21].
In particular, it is shown in [109] that the malicious users
can exploit Border Gateway Protocol (BGP) routing scheme
to hijack blockchain messages, thereby resulting in the higher
delay of block broadcasting. The work of [110] also shows that
a Decentralized Autonomous Organization (DAO) attack stole
$50 million worth of Ethereum by leveraging the vulnerability
of smart contracts.
Potential solutions. Security vulnerabilities of BCoT can be
remedied via either the security enhancement of IoT systems
or loophole repairing of blockchain. For example, cooperative
jamming scheme [111] was explored to improve the security
of IoT systems while no extra hardware is required for existing
IoT nodes. Meanwhile, [112] exploits key generations based
on reciprocity and randomness of wireless channels in Long
Range (LoRa) IoT network. In the perspective of repairing
blockchain loopholes, there are also some advances. In particular, the recent work of [113] proposes a secure relayingnetwork for blockchains, namely SABRE, which can prevent
blockchain from BGP routing attacks. Regarding DAO attacks,
Corda and Stellar trade the expressiveness for the verifiability
of smart contracts [114] so as to avoid DAO attacks.
C. Privacy leakage
Blockchain technologies have some mechanisms to preserve a certain data privacy of transaction records saved in
blockchains. For example, transactions are made in Bitcoin via
IP addresses instead of users’ real identities thereby ensuring a
certain anonymity. Moreover, one-time accounts are generated
in Bitcoin to achieve the anonymity of users. However, these
protection schemes are not robust enough. For example, it
is shown in [22] that user pseudonyms can be cracked via
learning and inferring the multiple transactions associated with
one common user. In addition, the full storage of transaction
data on blockchain can also lead to the potential privacy
leakage as indicated in [115].
Potential solutions. Recently, mixed coins are proposed to
confuse attackers so that they cannot infer the exact number
of real coins spent by a transaction. However, recent study
[116] demonstrates the weakness of the coin-mixed schemes
via extensive realistic experiments based on Monero4. Moreover, the actual transaction can be deduced by leveraging
the vulnerability of the coin-mixed schemes. The work of
4A
private digital currency platform (https://getmonero.org/)
15
[115] presents a memory optimized and flexible blockchain
data storage scheme, which can somewhat reduce the privacy
leakage risk.
D. Incentive mechanism in BCoT
An appropriate incentive mechanism is a benign stimulus
to blockchain systems. For example, a number of Bitcoins
(BTC) will be rewarded to a miner who first solves the
computationally-difficult task. Meanwhile, a transaction in
Ethereum will be charged with a given fee (i.e., gas) to pay
the miners for the execution of contracts. Therefore, there are
two issues in designing incentive mechanisms in blockchains:
1) the reward for proving (or mining) a block and 2) the
compensation for processing a transaction (or a contract).
However, it is challenging to design a proper incentive
mechanism for BCoT to fulfill the requirements of different
applications. Take digital currency platforms as an example,
where miners are keen on the price of digital currency. For
instance, the BTC reward for a generated block will be
halved every 210,000 blocks [117]. The reward decrement will
discourage miners to contribute to the solution of the puzzle
consequently migrating to other blockchain platforms. How to
design a proper rewarding and publishing mechanism of digital
currency is necessary to ensure the stability of blockchain
systems.
Potential solutions. On the other hand, the reputation and
honesty is an impetus to users in private or consortium
blockchain systems. Therefore, going beyond digital currency,
reputation credits can be used as incentives in the scenarios
like personal reputation systems [118], sharing economy [119],
data provenance [120] and the medication supply chain [121].
The recent work [122] presents RepChain, which exploits the
reputation of each node to develop the incentive mechanism.
E. Difficulty in BDA in BCoT
There is a surge of big volume of IoT data generated in
nearly real time fashion. The IoT data exhibits in massive
volume, heterogeneity and huge business value. Big data
analytics on IoT data can extract hidden values and make
intelligent decisions. However, it is challenging for apply
conventional big data analytics schemes in BCoT due to the
following reasons:
•
•
Conventional BDA schemes cannot be applied to IoT
devices due to the resource limitations. Since IoT devices
have inferior computing capability, the complicated BDA
schemes cannot be deployed at IoT devices directly.
Moreover, the bulky size of blockchain data also leads
to the infeasibility of the local storage of blockchain data
at IoT devices. Although cloud computing can address
these issues, uploading the data to remote cloud servers
can also result in the privacy-breach and the long-latency
[123].
It is difficult to conduct data analytics on anonymous
blockchain data. Blockchain technologies can protect
data privacy via encryption and digital signature on data
records. However, it often requires the data decryption before conducting data analytics. Nevertheless, the decryption process is often time-consuming thereby resulting in
the inefficiency of data analytics [124]. It is challenging to
design data analytics schemes on blockchain data without
decryption.
Potential solutions. MEC is serving as a crucial complement
to cloud computing by offloading computing tasks from distant
cloud servers to MEC in approximation to users. As a result,
MEC can improve the response, privacy-preservation and
context-awareness in contrast to cloud computing. Therefore,
offloading BDA tasks to MEC servers can potentially solve
the privacy-leakage and long latency issue of cloud computing
with blockchain [125]. Regarding data analytics on anonymous
blockchain data, there are some recent advances: 1) complex
network-based community detection [126] to identify multiple addresses associated with an identical user, 2) feature
extraction of transaction patterns of Bitcoin blockchain data
to identify payment relationships [127], 3) analysis of user
accounts and operation codes on Ethereum to detect Ponzi
fraud behavior [128].
F. Scalability of BCoT
The scalability of incumbent blockchains also limits the
wide usage of blockchains in large scale IoT. The scalability
of blockchains can be measured by the throughput of transactions per second against the number of IoT nodes and the
number of concurrent workloads [26], [114]. Many blockchain
systems are suffering from the poor throughput. For example,
it is shown in [129] that Bitcoin can only process seven
transactions per second. In contrast, VISA can process nearly
2,000 transactions per second and PayPal has the throughput
of 170 transactions per second [130], [131]. Ref. [4] shows
that Bitcoin blockchain may not be suitable for IoT due to
the poor scalability. In summary, the incumbent blockchain
systems may not be suitable for the applications with a large
volume of transactions especially for IoT.
Potential solutions. There are two possible directions in
improving the scalability of blockchains in IoT: 1) designing
more scalable consensus algorithms and 2) constructing private
or consortium blockchains for IoT. Regarding 1), we can
choose the consensus-localization strategy to improve the
throughput of transactions. Meanwhile, we may implement
some new blockchain structures such as directed acyclic graph
(DAG) [132] to allow the non-conflicting blocks from the
side-chain to be assembled with the main chain, consequently
reducing the cost for resolving bifurcation. In addition, we
may consider integrating PoW with PBFT to improve the
throughput of PoW similar to Sharding Protocol proposed in
[133], in which less computational-extensive puzzle is first
solved in PoW and consensus is then reached in multiple small
groups.
Regarding 2), transactions in private and consortium
blockchains can be processed much faster than public
blockchains due to the fully-controlled systems and the limited
number of permitted users. Meanwhile, the consensus can
also be easily reached in private and consortium blockchains.
16
Moreover, the fully-controlled blockchains also fulfill the
requirement that an enterprise needs to have a control on
different strategic sectors, e.g., ERP, MES, PLM and CRM
systems [59], [114]. Though there are some attempts such
as GemOS [36], Multichain [37] and Hyperledger [38], more
mature private and consortium blockchain platforms serving
for specific industrial sectors are still expected in the future.
VIII. C ONCLUSION
The incumbent Internet of Things (IoT) systems are facing a
number of challenges including heterogeneity, poor interoperability, resource constraints, privacy and security vulnerability.
The recent appearance of blockchain technologies essentially
offers a solution to the issues with the enhanced interoperability, privacy, security, traceability and reliability.
In this paper, we investigate integrating blockchain with
IoT. We name such synthesis of blockchain and IoT as BCoT.
We provide a comprehensive survey on BCoT. In particular,
we first briefly introduce internet of things and blockchain
technology. We then discuss the opportunities of BCoT and
depict the architecture of BCoT. We next outline the research
issues in blockchain for next-generation networks. We further
discuss the potential applications of BCoT and outline the open
research directions in BCoT.
ACKNOWLEDGEMENT
This work was supported by the National Key Research and Development Program (2016YFB1000101), the
National Natural Science Foundation of China (61722214
and U1811462), Macao Science and Technology Development
Fund under Grant No. 0026/2018/A1, and the Program for
Guangdong Introducing Innovative and Entrepreneurial Teams
(2016ZT06D211). In addition, this project has also received
funding from the European Union’s Horizon 2020 research
and innovation programme under the Marie Skłodowska-Curie
grant agreement No 824019. The authors would like to thank
Gordon K.-T. Hon for his constructive comments.
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