Sensor Protocols for Information via Negotiation (SPIN)
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Wireless sensor networks consist of large numbers of sensor nodes that monitor parameters and communicate wirelessly. The SPIN protocol family was developed to address the limitations of sensor nodes, particularly their limited energy, computation, and communication capabilities. SPIN uses meta-data negotiation and resource awareness to disseminate data between nodes more efficiently than flooding protocols. SPIN-1 is a simple three-stage handshake protocol that reduces energy costs. SPIN-2 builds upon SPIN-1 with an additional energy conservation heuristic to further prolong network lifetime. Evaluation shows SPIN consumes significantly less energy than flooding for data dissemination in wireless sensor networks.
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Wireless sensor network is collection of one or more homogeneous or heterogeneous sensor
nodes which sense some events and inform sink for that by sending that data towards it to perform some
action. Data transmission is the most effective factor in sensor network that directly regret energy of
sensor node but though energy of sensor node is very crucial one need to save that energy by means of
minimizing redundancy and retransmission of data. Till the day many routing protocols are introduced
to route data efficiently in order to improve network life time but all protocols have some deficiency.
One of the most popular data centric dissemination protocols is Sensor Protocol for Information via
Negotiation (SPIN). It efficiently disseminates data among other nodes in the network. This protocol
uses meta-data for negotiation and eliminates the transmission of the outmoded data throughout the
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Energy Efficient Routing Strategies for Large Scale Wireless Sensor in Hetero...
The efficiency of a wireless sensor network depends on its life time. By conserving the energy of each sensor for increase in the network life time. The basic operations of a wireless sensor network are sensing 1 the data to the energy sink term is for next transmitting node. The communication or routing 2 process operation be allowed in any operations for all nodes 3 . We propose to select a specific collection of nodes for communication with considering the importance of wireless sensor where security 4 and power usage 5 is taken as top priority. O. Sampath | . P. Suryanarayana Babu "Energy Efficient Routing Strategies for Large Scale Wireless Sensor in Heterogeneous Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd20281.pdf
Paper URL: https://www.ijtsrd.com/computer-science/computer-network/20281/energy-efficient-routing-strategies-for-large-scale-wireless-sensor-in-heterogeneous-networks/o-sampath
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
The document analyzes and compares the performance of two routing protocols for wireless sensor networks: LEACH and SPIN. LEACH is a hierarchical clustering protocol that randomly selects cluster heads to aggregate and transmit data to the base station. SPIN is a data-centric protocol that uses data negotiation to disseminate data and avoid redundant transmissions. The document simulates both protocols and finds that SPIN has lower overall energy consumption than LEACH due to its negotiation-based approach. Key differences between the protocols include LEACH using clusters and SPIN being flat, with SPIN allowing for possible node mobility and multipath transmission.
WSN_Chapter 4 Routing Protocols-I.pptx
The document discusses routing protocols for wireless sensor networks (WSNs). It provides an overview of routing challenges in WSNs, including energy constraints, data delivery models, fault tolerance, and quality of service issues. It then describes two common flat routing protocols for WSNs: SPIN and Directed Diffusion. SPIN uses data negotiation to disseminate information and avoid redundant transmissions. Directed Diffusion establishes interest gradients to route data from sources to a sink based on attribute-value pairs.
Final PPT.pptx
It's a ppt on "Evaluation of different performance matrices of wireless sensor network using DSR routing protocol using Ns2 simulator
Network structure routing_protocols_in_wsn
This document summarizes key routing protocols proposed for network structure in wireless sensor networks (WSNs). It classifies routing protocols into three categories: flat-based, hierarchical-based, and location-based routing. Flat-based routing treats all nodes equally, while hierarchical-based routing uses cluster heads to reduce energy consumption. Location-based routing exploits node positions. Key protocols discussed include SPIN, directed diffusion, LEACH, PEGASIS, and SOP. The document provides an overview of how each protocol operates and its advantages.
Survey on sensor protocol for information via negotiation (spin) protocol
This document summarizes a survey on the Sensor Protocol for Information via Negotiation (SPIN) routing protocol for wireless sensor networks. It begins with an introduction to wireless sensor networks and describes the basic operation of the SPIN protocol. It then discusses several extensions and improvements made to the SPIN protocol, including M-SPIN, SPIN-pi, and SPIN-I, noting problems or limitations with each. It proposes a new solution that combines the M-SPIN protocol with "plug-in" nodes to improve reliability and network lifetime. The proposed solution is described along with an algorithm and network topology. The document concludes by acknowledging references used in the survey.
Data Center Network Design Using Metrics And Their Results...
The document discusses implementing complex protocols on network systems. It notes that networks are currently built by implementing protocols across devices like routers, switches, and middleware. Network administrators manually configure new policies by converting them into low-level device commands. This approach has issues with security, scalability, and manageability. Previous efforts tried to make networks programmable through systems like Forces, Routing Control Platform, Ethane, and OpenFlow, but SDN aims to better address these issues.
Fault tolerance in wsn
The document discusses fault tolerance techniques in wireless sensor networks (WSNs). It first reviews WSNs and types of failures that can occur, such as energy depletion, hardware failure, and communication link errors. It then covers approaches to fault detection including centralized (Sympathy, Secure Locations) and distributed (node self-detection, clustering). Fault recovery techniques like relay node placement, hop-by-hop TCP, and data aggregation are also summarized. The document aims to provide an overview of key aspects of fault tolerance in WSNs.
Protocols for wireless sensor networks
Wireless Sensor Network (WSN) consists of sensor nodes which interact with each other through physical parameters like sunlight, wind, vibration, humidity etc. Routing protocols provide an optimal data transmission route from sensor nodes to sink node to save energy of nodes. From Base Station (BS) Sensor node sends and receives data to or from wireless stations. Clustering mechanism is one of the popular routing mechanisms used in WSN for optimizing the problem in sensor nodes. There are two types of clustering schemes known as homogeneous schemes and heterogeneous schemes. In Homogeneous scheme initial energy is same for each node but in heterogeneous scheme initial energy is different for each node and also used to determine the efficiency of sensor networks. Enhanced Modified LEACH (EMODLEACH) is a reactive protocol which is implemented for homogeneous network model. We have implemented the concept of Efficient Cluster head Replacement scheme and Dual transmitting power level scheme of MODLEACH along with the concept of Efficient Intra Cluster transmission Scheme of TEEN in LEACH. We analyze the PEGASIS protocol and modified the exiting protocol called improved energy balanced routing protocol (IEBRP).This IEBRP is based on cluster formation, cluster routing and other aspects of LEACH protocol.
Bidirectional data centric routing protocol to improve the energy efficiency ...
This document summarizes a research paper that proposes a novel bidirectional data-centric routing protocol to improve energy efficiency in wireless sensor networks. The protocol aims to overcome issues with existing protocols like SPIN and Directed Diffusion, such as data redundancy, resource blindness, and packet loss. It uses meta-data descriptors to route data along the shortest path based on source and sink interests. Simulation results showed the proposed protocol increases bandwidth, network lifetime, and disseminates data with higher percentage compared to other protocols.
Based on Heterogeneity and Electing Probability of Nodes Improvement in LEACH
In heterogeneous sensor networks, certain nodes become cluster heads which aggregate the data of their cluster nodes and transfer it to the sink. An Improved Energy leach protocol for cluster head selection in a hierarchically clustered heterogeneous network to reorganize the network topology efficiently is proposed in this research work. The proposed algorithm will use thresholding to improve the cluster head selection. The presented algorithm considers the sensor nodes in wireless network and randomly distributed in the heterogeneous network. The coordinates of the sink and the dimensions of the sensor field are known in prior.
Wireless Sensor Networks.pptx
This document discusses wireless sensor networks and their architecture. It describes layered and clustered architectures for organizing sensor networks. Layered architectures arrange sensors in layers around a central base station, allowing for short-range transmissions. Clustered architectures organize sensors into clusters headed by cluster heads that can aggregate and transmit data to the base station. The document also introduces protocols like UNPF that implement layered architectures and LEACH that uses clustering to minimize energy use in sensor networks.
Complete report on DATA ACQUISITION SCHEME IN WIRELESS SENSOR NETWORK
With the development in data acquisition system, information-collection plays an increasingly important role in the field of Wireless Technology. There has been tremendous increase in the use of sensors in each and every field. In order to get fast response from these sensors the delay should be reduced. Also the congestion in the network should be tackled to increase the efficiency. Wireless Sensor Networks (WSNs) consist of many tiny wireless sensors which operate in an environment in order to collect data. In a typical WSN, data is gathered from environment by sensor nodes and then transmitted to a base station. All these operations are executed by sensor nodes with keeping in mind the limitation of power. Reliable communication, power efficiency, network congestion issues are among major concerns. So in our project our main focus is to avoid the packet loss by increasing the network efficiency and handling the congestion in the network by proper buffer management. Finally visualization of processed data is done at the base station and the future enhancement could be to directly send the sensed data to cloud storage.
Ijarcet vol-2-issue-2-576-581
This document discusses techniques for data dissemination and caching in wireless sensor networks. It aims to reduce energy consumption by minimizing unnecessary data transmission through cooperative caching. Sensor nodes can store data in their local cache or use nearby nodes' caches through cooperative caching. One node close to the sink is selected as the Immediate Dissemination Node to cache data, while other nodes along the path act as dissemination nodes. By caching data closer to the sink, this approach reduces network traffic and prolongs the battery life of sensor nodes. The paper also reviews several routing protocols and discusses how data negotiation, change expectancy, and discarding duplicate data can further improve energy efficiency in wireless sensor networks.
Some aspects of wireless sensor networks
The development of the wireless sensor networks (WSNs) in various applications like Defense, Health,
Environment monitoring, Industry etc. always attract many researchers in this field. WSN is the network
which consists of collection of tiny devices called sensor nodes. Sensor node typically combines wireless
radio transmitter-receiver and limited energy, restricted computational processing capacity and
communication band width. These sensor node sense some physical phenomenon using different
transduces. The current improvement in sensor technology has made possible WSNs that have wide and
varied applications. While selecting the right sensor for application a number of characteristics are
important. This paper provides the basics of WSNs including the node characteristics. It also throws light
on the different routing protocols.
Kanchan ppt
The document summarizes a student's M. Tech thesis project on improving routing protocols in wireless sensor networks. It begins with an objective to develop a hybrid routing protocol combining features of PEGASIS and LEACH to increase network lifetime. It then reviews related work on routing protocols and energy efficiency. The proposed methodology describes a hybrid protocol that selects cluster heads probabilistically like LEACH while forming chains to route data like PEGASIS. Simulation results show the hybrid protocol increases network lifetime to over 2000 rounds compared to 2000 rounds for previous work. The conclusion is that lower cluster head election probabilities in the hybrid protocol extend network lifetime. Future work could analyze different network parameters.
Energy Efficient PEGASIS Routing Protocol in Wireless Sensor Network
This document discusses the PEGASIS routing protocol for wireless sensor networks. It begins with an abstract that introduces PEGASIS as an energy-efficient chain-based hierarchical protocol. It then provides background on wireless sensor networks and discusses challenges like energy efficiency and network lifetime. It explains how PEGASIS forms chains between sensor nodes so that each node only communicates with nearby neighbors, extending network lifetime. The document compares PEGASIS to LEACH, finding that PEGASIS provides more balanced energy distribution and longer network lifetime. It then outlines the PEGASIS algorithm and discusses potential improvements like minimizing delay. Simulation results show PEGASIS increases network efficiency and lifespan over LEACH. The conclusion is that
Energy saving in P2P oriented Wireless Sensor Network (WSN) using the approac...
This document discusses energy saving techniques in peer-to-peer wireless sensor networks through the use of data compression. It begins by introducing wireless sensor networks and their energy constraints. It then discusses how compression can reduce energy consumption by decreasing transmission time. Different compression techniques like LZO, Zlib, and Bzip2 are described. The document proposes using Adaptive Compression Environment to automatically select the best compression technique based on network conditions. It presents an algorithm for compressing data at the sender, transmitting it in chunks, and decompressing it at the receiver. The conclusion states that compression technologies can help save sensor energy in peer-to-peer networks and that more advances will optimize this solution.
Proactive Data Reporting of Wireless sensor Network using Wake Up Scheduling ...
In Wireless Sensor Network (WSNs), gather the data by using mobile sinks has become popular. Reduce the number of messages which is used for sink location broadcasting, efficient energy data forwarding, become accustomed to unknown earthly changes are achieved by a protocol which is projected by a SinkTrail. The forecast of mobile sinks’ location are done by using logical coordinate system. When sensor nodes don’t have any data to send, at that time they switch to sleep mode to save the energy and to increase the network lifetime. And due to this reason there is a chance of the involvement of nodes that are in sleeping state between the path sources to the mobile sink which is selected by the SinkTrail protocol. Before become the fully functional and process the information, these sleeping nodes can drop the some information. Due to this reason, it is vital to wake-up the sleeping nodes on the path earlier than the sender can start transferring of sensed data. In this paper, on-demand wake-up scheduling algorithm is projected which is used to activates sleeping node on the path before data delivery. Here, in this work the multi-hop communication in WSN also considers. By incorporating wake-up scheduling algorithm to perk up the dependability and improve the performance of on-demand data forwarding extends the SinkTrail solution in our work. This projected algorithm improves the quality of service of the network by dishonesty of data or reducing the loss due to sleeping nodes. The efficiency and the effectiveness projected solution are proved by the evaluation results.
Wsn ppt
This document presents a clustering approach using a handoff mechanism to enhance network lifetime in wireless sensor networks. It proposes using a mobile-based LEACH-ERE method for clustering and cluster head election to improve energy efficiency. The method considers both fixed and mobile nodes to increase network lifetime, packet delivery ratio, and energy usage effectiveness. It was found that the mobile-based LEACH-ERE approach increases network lifetime and packet delivery ratio compared to the static LEACH protocol, as it consumes less energy over time.
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Sensor Protocols for Information via Negotiation (SPIN)
- 1. Sensor Protocols for Infor mation via Ne gotiation (SPIN) Rajiv Agarwal B.Sc.(cs)Hons. 115090
- 2. Outline WSN Components of Sensor node SPIN Conclusions
- 3. Wireless Sensor Network Wireless sensor networks consist of large number of nodes that have sensing, computing and communication capabilities. It is basically an interconnection between large number of nodes that are deployed for system monitoring by measuring its parameters. Wireless Networks of sensors are likely to be widely deployed in the future
- 5. Limitations of a Sensor node Several obstacles need to overcome Energy - limited supply of energy simply performing computations and transmitting information in a wireless environment, energyconserving forms of communication and computation are essential . Computation - limited computing power so may be unable to run some network protocols. Communication - The bandwidth of the wireless links connecting sensor nodes is often limited, on the order of a few hundred Kbps.
- 6. Classic flooding A source node sends its data to all of its neighbors. Upon receiving a piece of data, each node then stores and sends a copy of the data to all of its neighbors. limitations – Implosion – Overlap – Resource blindness
- 7. Implosion (A) A B (A) C (A) (A) D The implosion problem. In this graph, node A starts by flooding its data to all of its neighbors. Two copies of the data eventually arrive at node D. The system energy waste energy and bandwidth in one unnecessary send and receive.
- 8. Overlap q r s A B (q,r) (r,s) C The overlap problem. Two sensors cover an overlapping geographic region. When these sensors flood their data to node C, C receives two copies of the data marked r. 8
- 9. Resource blindness In classic flooding, nodes do not modify their activities based on the amount of energy available to them at a given time. A network of embedded sensors can be “resource-aware” and adapt its communication and computation to the state of its energy resource. The SPIN (Sensor Protocols for Information via Negotiation) family of protocols incorporates two key innovations that overcome these deficiencies : negotiation resource-adaptation 9
- 10. SPIN: A Data Centric Protocol For Wireless Sensor Networks Data-centric protocols differ from traditional address-centric protocols in the manner that the data is sent from source sensors to the sink. In address-centric protocols, each source sensor that has the appropriate data responds by sending its data to the sink independently of all other sensors. In datacentricprotocols, when the source sensors send theirdata to the sink, intermediate sensors can performsome form of aggregation on the data originating from multiple source sensors and send the aggregated data toward the sink.
- 11. SPIN SPIN-1 SPIN-2 The SPIN family of protocols rests upon two basic ideas: ◦ To operate efficiently and to conserve energy ◦ Nodes in a network must monitor and adapt to changes in their own energy resources to extend the operating lifetime of the system. 11
- 12. Meta-Data SPIN does not specify a format for meta-data Meta-data format is application specific SPIN Messages ADV-When a node has new data to share; it can advertise this using ADV message containing Metadata. REQ- Node sends an REQ when it needs to receive actual data. DATA – Contains actual data message
- 13. SPIN-1 : 3-Stage Handshake Protocol (SPIN-PP) Simple handshake protocol for disseminating data through a lossless network Work in three stages (ADV-REQ-DATA) Node A starts by advertising its data to node B (a). Node B responds by sending a request to node A (b). After receiving the requested data (c), node B then sends out advertisement to its neighbors (d), who in turn send requests back to B (e, f). 13
- 14. SPIN-1 : 3-Stage Handshake Protocol SPIN-1 can be run in a completely unconfigured network with a small, startup cost to determine nearest neighbors If the topology of the network changes frequently, these change only have to travel one hop before the nodes can continue running the algorithm SPIN-2 : SPIN-1 with a Low-Energy Threshold (SPIN-EC) Adds a simple energy-conservation heuristic to the SPIN-1 protocol When energy is plentiful, SPIN-2 nodes communicate using the same 3-stage protocol as SPIN-1 node 14 When its energy is approaching a low-energy threshold, it adapts by reducing its participation in the protocol
- 15. Conclusions SPIN solves the implosion and overlap problems. SPIN-1 and SPIN-2 are simple protocols for wireless sensor networks. SPIN-1 consumes only 25% energy w.r.t flooding SPIN-2 distributes 60% more data per unit energy w.r.t flooding.
- 16. Thank you!