International Journal of
Comput Syst Sci & Eng (2014) 1: 91–100
© 2014 CRL Publishing Ltd
Computer Systems
Science & Engineering
Routing protocols for mobile sensor
networks: a comparative study
Shahzad Ali1,2 , Sajjad A. Madani2 , Atta ur Rehman Khan3 and Imran Ali Khan2
1 Institute IMDEA Networks, Avenida del Mar Mediterraneo, Madrid, Spain.
2 COMSATS Institute of Information Technology, Abbottabad, Pakistan.
3 FSKTM, University of Malaya, Kuala Lumpur, Malaysia.
E-mail: shahzadali@ciit.net.pk, madani@ciit.net.pk, attaurrehman@siswa.um.edu.my, imran@ciit.net.pk
This paper presents a comparison of cluster-based position and non position-based routing protocols for mobile wireless sensor networks to outline design
considerations of protocols for mobile environments. The selected protocols are compared on the basis of multiple parameters, which include packet delivery
ratio, packet loss, network lifetime, and control overhead using variable number of nodes and speeds. The extensive simulation and analysis of results show
that position-based routing protocols incur less packet loss as compared to the non position based protocols. However, position-based protocols require
localization mechanism or a GPS for the location information, which consumes energy and affects the network lifetime. Alternatively, non position-based
protocols are more energy efficient and provide extended network lifetime.
Keywords: Wireless sensor networks, mobility, clustering, routing protocols, ad hoc networks.
1.
INTRODUCTION
Wireless sensor network (WSN) is a network of sensor nodes
that are distributed over a certain area to monitor a physical
phenomenon, such as temperature, humidity, or fire. WSN
consist of a large number of sensor nodes and a resource rich
sink node(s) that acts as a gateway to other networks or a final
destination [1]. The sensor nodes are characterized by limited
battery power, processing capacity, and memory resources [2].
Therefore, WSNs require low footprint communication schemes,
which utilize minimum resources without compromising the required quality of service. Moreover, due to limited energy of
the sensor nodes, the energy efficiency is one of the most important design considerations of the WSN routing protocols [3].
However, mobility of sensor nodes makes the routing process
challenging and complex, which hampers the energy efficiency
of the routing protocols.
An overwhelming majority of the current research on sensor
networks consider static networks [1, 2, and 4]. However, there
exist many applications [6, 7] which require mobile nodes, for
instance, habitat monitoring, battlefield surveillance, and ob-
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ject tracking. In mobile WSNs, unpredictable topology changes
and frequent path failures make the routing challenging [2], because path breakage leads to increase in the end-to-end delay
and packet loss [8]. Some routing schemes assume that the
sensor nodes can directly communicate with the sink node [7,
8, and 9]. This assumption restricts the geographic scalability,
but is countered by multi-hop routing schemes. Considering
the mobility and resource constrained environment, WSNs require energy aware routing protocols, capable of decreasing the
packet loss, and enhancing robustness against mobility of nodes.
Furthermore, WSN protocols require scalability and aptitude to
coup with dynamicity of the network that is caused by the mobility [10, 11]. To achieve this, backup strategies are required
which enable data packets to reach a destination in the presence
of mobility [12].
In this study, we focus the comparison of cluster based position and non position-based hierarchal routing schemes based
on multiple performance factors, such as energy efficiency, overhead, and packet loss. We select six routing protocols for comparison, which are studied thoroughly for variable network densities and node speeds. The performance metrics that are used
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ROUTING PROTOCOLS FOR MOBILE SENSOR NETWORKS: A COMPARATIVE STUDY
for the evaluation of the protocols include, average packet delivery ratio, network lifetime, average number of control packets
sent during the protocol operation, and average percentage of
packet loss.
The remainder of this paper is organized as follows. Section
2 contains the related work. Section 3 presents the comparison
strategy. Section 4 consists of results and discussion, whereas
Section 5 concludes the paper.
2.
RELATED WORK
Due to limited resources of sensor nodes, important design goals
for WSNs comprise: (a) minimizing the total energy consumption within the network (b) minimizing the overhead of control
messages, (c) achieving fault-tolerance, and (d) balancing energy dissipation among the sensor nodes to avoid disconnected
networks.
Some of the position and non position-based routing protocols
are discussed as follows:
2.1
Position Based Protocols
Position-based routing protocols use location information for
routing decisions. To facilitate in getting the location information, a node can either be equipped with a low power GPS
module, or it may use distributed localization schemes, which
are based on received signal strength indicator, time of arrival,
and manual registration [13, 14, 15]. In position based protocols, it is assumed that each node knows position of the destination and its neighbours, because the locations of nodes can be
used to identify their network connectivity [16, 17]. Position
of neighbours is usually identified via periodic hello messages.
Moreover, position-based protocols can substantially reduce the
communication overhead that is caused by flooding. However,
getting location information of a node and its neighbours is a
costly operation in terms of message transfer overhead and energy; particularly in mobile environments, where the nodes update their position more frequently.
Geographical Energy Aware Routing (GEAR) [17] is an energy aware geographic protocol that is designed to increase the
network lifetime of WSNs. GEAR uses energy aware metrics
for neighbour selection, and balances the energy consumption
among neighbours by maintaining a cost function for each neighbour. The cost function facilitates in finding the cost for reaching
a neighbour that is based on the location and required energy.
Geographical Adaptive Fidelity (GAF) [18] also relies on the
location information of the nodes. GAF extends the network
lifetime by reducing the energy consumption for which it builds
a geographical grid that consists of cells. Each cell contains
multiple nodes, but only a single node is active at a time. Meanwhile, the remaining nodes of the cell can switch to sleep state
to conserve energy [16].
Distance Routing Effect Algorithm for Mobility (DREAM)
[19] is a position based routing scheme that is designed for mobile applications. DREAM is based on a directional forwarding
approach that floods the data in a particular direction (using a
certain angle) towards the sink node. The drawback of DREAM
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is that it maintains a routing table to store information of the
network nodes. Therefore, for very large networks, DREAM
maintains large routing tables, which raise scalability issues.
Adaptive Face Routing (AFR) [20] is a distributed geographic
ad hoc routing protocol. It is based on Euclidean planar graphs,
in which the nodes and edges of a plane are partitioned into
regions called faces. AFR uses face routing to traverse the faces
in a restricted way, and avoids exploring complete boundary
of the faces that lie between the source and destination. This
restriction is based on the size of the ellipse area which depends
on the path length. However, if the face routing fails to reach
the destination, AFR falls back and repeats the process using
eclipse of double size. In [21], authors propose a new version of
the AFR named Other Adaptive Face Routing (OAFR) with an
extension that it selects the boundary points that are close to the
destination.
Greedy Perimeter Stateless Routing (GPSR) [22] uses a hybrid mechanism that is based on greedy forwarding and face
routing. It embeds the location of the destination into a packet
and forwards it towards the destination using greedy forwarding
approach. When the greedy forwarding fails and reaches a local maximum problem, GPSR uses face routing to route around
dead-ends until the packet reaches a node that is close to the
destination.
Greedy Other Adaptive Face Routing (GOAFR) [21] is a distributed geographic routing protocol that uses greedy forwarding
and Other Adaptive Face Routing. It forward the packets towards
the destination using greedy forwarding approach. However, unlike face routing in GPSR, it uses OAFR for recovery.
There are some other protocols that are designed for mobile
ad hoc networks, but they cannot be applied to WSNs directly,
because they are not optimized for resource constrained environment of WSNs and are not energy aware. Few examples of such
protocols include, Ad hoc On-Demand Distance Vector (AODV)
[23], Location Aided Routing (LAR) [24], and On Demand Multi
path Distance Vector Routing in Ad Hoc Networks (AOMDV)
[4]. Moreover, the number of nodes in WSNs is comparatively
very large as compared to MANETs [25]. In addition, the capabilities of sensor nodes are limited as compared to the MANET
nodes. Therefore, it is not practical to use MANET protocols
for the WSNs.
Hierarchical routing is widely investigated for ad hoc networks [8, 26–30] due to their attractive characteristics, such as
energy efficiency and scalability [31]. In hierarchical routing
protocols, the defined sensing filed is divided into regions called
clusters. Each cluster contain multiple nodes, out of which, one
node is designated as a cluster head. The remaining nodes associate with the cluster head and send their data. The cluster
head is responsible for collection and aggregation of data from
the associated nodes, and sending it to the base station.
The selected position-based protocols that are used for performance comparison are MAR [32] and GRC. Both of these
protocols are specifically designed for mobile sensor networks,
and they inherit the hierarchal routing characteristics, such as
scalability and energy efficiency.
2.1.1
Mobility Aware Routing (MAR)
MAR is a hierarchal position-based routing protocol in which the
sensing field is divided into a geographic grid, and cluster heads
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S. ALI ET AL
are selected on the basis of mobility factor of the nodes. Mobility
factor refers to the number of times a node has moved from one
zone to another. The objective of selecting cluster heads on
the basis of mobility factor is to select a node as a cluster head
that has minimum mobility. Therefore, during the cluster head
selection process, a node having the smallest mobility factor
is selected as a cluster head. This improves connectivity of the
cluster head with the associated nodes. However, the major issue
with this protocol is that it does not consider node energy in the
cluster head selection process. Therefore, it is not an energy
aware routing protocol. Moreover, it does not make full use of
location information of the nodes, which results as an increase
in the packet loss. Furthermore, it also incurs packet loss during
the inter-cluster communication, as the cluster heads move out
of the transmission range of each other.
2.1.2
Geographic Robust Clustering (GRC)
GRC is an energy aware protocol that uses location information
during the selection of the cluster heads. In addition, it uses
a recovery strategy for reducing packet loss during the intercluster communication phase. During the cluster head selection
phase, a node is selected as a cluster head that is either at the
center or close to the center, and has high residual energy. Each
node calculates the weight on the basis of its residual energy
and center-ness. The equation used for weight calculation is
presented as follows:
weight = w1 × E − w2 × C
Where,
2
i=1
(1)
wi = 1 and 0 < w2 < w1 .
E is the remaining energy of the sensor node, and C represents
the center-ness of the node that is calculated as follows:
Let (x, y) be the x and y coordinates of a mobile node ‘mi ’ in a
2D plane, where 1 ≤ i ≤ n. Also, let (xc , yc ) be the approximate
center point of the region in which ‘mi ’ is located. Using the
coordinates and center point of the node, the value of C can be
calculated as:
C = |xc − x| + xy − y
(2)
In addition to the aforementioned objectives, the selection of
cluster heads using this technique serves three purposes.
i. Cluster head is located either at the center or close to the
center of a zone having transmission
range
√ of ‘r’. There√
fore, size of each cell (zone) r/ 2 × r/ 2 provides better
coverage for mobile nodes during the intra-cluster communication phase.
ii. During inter-cluster communication, a cluster head may
incur less packet loss, because it is more likely that both
the cluster heads are within the transmission range of each
other.
iii. If both cluster heads are not within transmission range of
each other, then recovery strategy can be applied to avoid
packet loss.
After selection of the cluster heads, normal nodes send their
information to their respective cluster heads, followed by intercluster communication phase. Recovery strategy is applied during inter-cluster communication to reduce packet loss.
vol 29 no 1 March 2014
2.2
Non Position-based Protocols
In non position-based routing protocols, all the routing decisions
are made without any location information. Therefore, it is not
mandatory for the nodes to get their location information, or
keep location information of their neighbours. Few well known
non position-based protocols are discussed as follows.
In directed diffusion [33], data is named as attribute-value
pairs. Therefore, when the sink wants to collect a specific data,
the sink broadcasts interest to the nodes. The nodes save this
information, and whenever data is validated against the sink’s
interest, it is sent to the sink. The major benefit of directed
diffusion is that it provides data aggregation with optimal number
of transmissions.
Low Energy Adaptive Clustering Hierarchy (LEACH) [8] is
one of the early cluster based hierarchical non location-based
routing protocol. It is designed for static networks having a
fixed base station. The cluster heads are changed over a period
of time, and are selected in such a way that energy utilization
is evenly distributed among the nodes. LEACH is based on the
assumption that each node can reach the sink node directly. This
is not a realistic assumption, because sensor nodes have limited
transmission range and it is not feasible for all sensor nodes to
reach the sink node directly.
SPIN [34] is a data-centric protocol that avoids passing redundant data and saves energy by performing negotiation among
the nodes. To achieve this, SPIN protocol names the data (metadata), and distributes the meta-data in the network through advertising. However, nodes advertise the data to only interested
neighbors. In SPIN, there is no specific format for meta-data
definition as it varies from application to application.
In [33], the authors’ present hybrid energy efficient distributed
(HEED) clustering approach. HEED extends the network lifetime by selecting cluster heads on the basis of node’s residual
energy. To further enhance the performance, it considers intracluster communication cost as a secondary clustering parameter.
HEED outperforms many of the clustering protocols. However,
it has some pitfalls which include complex cluster head selection
process (based on probabilistic methods) and support for static
networks only.
The non position-based protocols that we have selected for
the performance comparison are DECA [35] and DEMC [9].
Both of these protocols are hierarchal clustering based and are
specifically designed for mobile sensor networks.
2.2.1
Distributed Efficient Clustering Approach (DECA)
In DECA [35], each node has a weight that is computed on the
basis of node residual energy, connectivity, and node identifier.
The positive point about this protocol is that each node transmits
only one message, rather than going through rounds of iterations of probabilistic message announcements (as in LEACH
and HEED). The process of message exchange during the protocol operation consumes more energy as compared to sensing
and computation [28]. Therefore, by reducing the number of
messages during formation of clusters lead to high energy efficiency [36]. To do so, each node maintains a neighbouring list
(table) that is updated through periodic Hello messages. Therefore, upon receiving the clustering messages, a node decides
whether it should select a cluster head or become a cluster head
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ROUTING PROTOCOLS FOR MOBILE SENSOR NETWORKS: A COMPARATIVE STUDY
itself. Simulation results show that DECA has outperformed
many clustering protocols including HEED. However, DECA
has some pitfalls. For instance, it uses periodic hello messages
for table maintenance that requires a considerable amount of
energy and processing. The transmission frequency periodic
hello messages increase with the increase in mobility. Consequently, it is not a good approach to maintain a table in highly
mobile/dynamic environments. Nevertheless, cases may occur,
where the neighbouring cluster heads move out of the transmission range of each other and incur packet loss during the
inter-cluster communication phase.
2.2.2
Distributed Efficient Multi-hop Clustering protocol(DEMC)
DEMC focuses optimum cluster head selection to maximize network coverage. In this protocol, each node sends less than one
message during the clustering phase. The difference between
DEMC and DECA is that in DEMC nodes do not send periodic
hello messages. Therefore, DEMC does not maintain a complete neighbour list. By doing so, DEMC reduces the number
of transmissions (Hello messages) per node, resulting in better
energy efficiency and low processing overhead. Moreover, both
protocols vary in weight calculation process for the cluster head
selection, and the nodes response mechanism after receiving the
cluster head announcement message. During the cluster head
selection process of DEMC, each node calculates the weight
based on its residual energy and unique node identifier. The
weight calculation equation of DEMC is mentioned as follows:
weight = w1 × E + w2 × I
Where
2
i=1
(3)
wi = 1 and 0 < w2 < w1 .
E is the residual energy of sensor node, and I is the node identifier that is used to break the tie in case two nodes have the same
residual energy. For cluster head selection, each node sets a timer
based on its calculated weight. Therefore, the timer of nodes that
have more weight expires first, and they broadcast cluster head
announcements. Consequently, when a node receives a cluster head announcement having a weight that is greater than its
own weight, then for that specific round the receiving node will
not send its cluster head announcement. This technique makes
DEMC more energy efficient compared to DECA, as it requires
less communication. Moreover, DEMC uses a recovery strategy during the inter-cluster communication phase and achieves
robustness against packet loss that occurs due to node mobility.
3.
COMPARISON STRATEGY
A variety of routing protocols are available for sensor networks.
Among these, clustering based protocols are proven to be energy efficient and scalable. However, mobile sensor networks
pose some different challenges for routing protocols due to their
dynamic topology. The mobility and changing topology causes
packet loss in two ways. Firstly, during the intra-cluster communication phase, when ordinary nodes are unable to send their information to the cluster head. Secondly, during the inter-cluster
communication phase, when a cluster head cannot send the aggregated data of the whole round to another cluster head. In
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position based protocols, the first case can be handled by using
the location information of nodes during the selection of cluster
heads, as proposed in GRC. Alternatively, in non position-based
protocols, this case is difficult to handle due to unavailability of
location information. Consequently, large packet loss occurs in
non location based protocols.
Considering the aforesaid challenge, there is a need for a
mechanism to reduce the packet loss during inter-cluster communication. In [37], authors propose√to increase the transmission
range of nodes by a factor of (1 + 5) to ensure guaranteed connectivity. However, increase in the transmission range by such
factor will also increase the energy consumption substantially
that may result as a dramatic decline in the network lifetime.
Alternatively, a recovery strategy can be used during the intercluster communication to avoid the packet loss.
Currently, there are two main approaches for packet recovery,
namely hop-by-hop and end-to-end [38]. Hop-by-hop recovery
is more energy efficient compared to end-to-end approach due to
its shorter retransmission range. Therefore, in our experiments
we use hop-by-hop recovery strategy. In DEMC and GRC a
recovery strategy is applied between two cluster heads during
inter-cluster communication to increase robustness of the routing
protocol in terms of connectivity and resilience against the packet
loss.
In this study, we select total of 6 protocols from the categories of position and non position-based protocols. For non
position-based protocols, we select DECA, DEMC, and DEMC
with recovery. Similarly, for position-based protocols, we select
MAR, GRC, and GRC with recovery.
3.1
Performance Metrics
The following performance metrics are used for evaluating the
aforementioned protocols.
1) Percentage of Packet loss
The percentage of packet loss is calculated by dividing the
total number of lost packets by total number of transmitted
packets. This performance metric is used to measure the
robustness of protocol with respect to different node speeds.
A protocol that incurs less packet loss as compared to other
protocols is considered more robust against packet loss.
2) Packet delivery ratio
Packet delivery ratio is the ratio of the number of packets
that are successfully delivered to the destination to the total
number of packets that are sent by the source. This metric
provides an indication of the ability of a protocol to deliver
packets to the respective destination. Hence, high packet
delivery ratio indicates better protocol performance.
3) Network lifetime
Network lifetime is defined as the number of round when the
first node dies in the network. Network lifetime depends
on the average energy consumption of a node per round.
Therefore, the protocols that exhibit low average energy
consumption per round provides longer network lifetime.
4) Average number of control packets
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S. ALI ET AL
This parameter presents the average number of control messages that are required for protocol operation. As transmitting and receiving of packets consumes considerable
amount of energy, it has high impact on the network lifetime.
3.2
Network model
A mobile wireless sensor network is modelled as a set of V nodes
that are interconnected by a set of full-duplex E communication
links. A unique identifier is used for the identification of each
node. In geographic routing protocols, the nodes identify their
position by either using GPS or by using some other localization
mechanism. Moreover, two nodes are considered as neighbours
if they have a link between them and they are within the transmission range of each other. Furthermore, nodes may move at
any time, without any notice and may change the topology.
The problem of clustering can be defined as selection of cluster heads from a set of V nodes in such a way that the cluster
heads cover the whole network. In location based clustering
protocols, each node v in a set V located in zone zi (where ‘i’
is the number of zones), v must be a cluster head or associated
with a cluster head. Alternatively, in non location based clustering protocols, each node v in a set V must be a cluster head or
associated with only one cluster head. After cluster head selection, every normal node in the cluster must be able to directly
communicate with the cluster head with whom it is associated.
The clustering protocol must be completely distributed, where
no central control authority is required, and each node makes its
decision independently based on the location information.
4.
RESULTS & DISCUSSION
The simulations are performed in OMNET++ based simulation
framework called INET [39]. INET framework supports multiple mobility models [40] and is well suited for simulation of
wireless sensor networks. In this experiment, we use disk graph
model for the communication links, which means that if node
‘X’ can reach node ‘Y’, then node ‘Y’ can also reach node ‘X’.
Moreover, the nodes use MAC (implemented using CSMA-CA
scheme) and physical layer of 802.11. However, more efficient
MAC schemes, such as [41] can also be used. Furthermore,
we use an energy consumption model to monitor the network
lifetime of selected protocols. According to this model [42],
the energy consumed in transmission of a k bit message over a
distance d is calculated as:
ET x (k, d) = ET x − elec(k) + ET x − amp(k, d)
ET x (k, d) = Eelec × k + Eamp × k × d 2
(4)
Moreover, the energy consumed in receiving a packet is given
by:
ERx (k) = ERx − elec(k)
(5)
ERx (k) = Eelec × k
Where ET x (k, d) is the energy required to transmit a ‘k’ bit
message over a distance of d meters and ERx (k) is the energy
required to receive a k bit message. Moreover, Eelec is the energy consumed for running the transceiver circuitry, and Eamp is
vol 29 no 1 March 2014
the energy consumed by the amplifier to achieve an acceptable
Signal to Noise Ratio (SNR).
Initially, 100 nodes are randomly distributed in the network
field having dimensions of 1000m × 1000m. In addition, we
use Mass Mobility model for simulations, which is a variant of
random waypoint mobility model, and is provided by the INET
framework. This mobility model is designed to model nodes
movement during which the nodes have a mass and momentum.
Therefore, the nodes do not start, stop, or turn abruptly. Table 1
shows the simulation parameters that are used for simulations.
Figure 1 presents packet delivery ratio with respect to different number of nodes having speed of 5 meter/second. The result
shows that location based protocols attain high packet delivery
ratio compared to non position based protocols. In both the categories, GRC with recovery and DEMC with recovery supersede
their respective contenders. The reason for high packet delivery
ratio of both the protocols is that they use recovery strategies
during the intercluster communication phase. Besides, recovery
strategy of GRC makes better use of location information during
the cluster head selection. Consequently, the packet loss during
the intracluster communication phase is low, which leads to increased packet delivery ratio. However, the location based routing itself reduces packet loss by a huge margin. Therefore, case
may occur, where a protocol with recovery strategy may provide
similar packet delivery ratio as without a recovery strategy.
Figure 2 presents packet delivery ratio with respect to different node speeds. The result shows that the packet delivery ratio
of the routing protocols decreases with the increase in mobility.
However, the position-based routing protocols provide better delivery ratio as compared to non position based routing protocols.
It is evident from Figure 3 that GRC with recovery provides
highest delivery ratio among the selected protocols. Moreover,
in non position-based protocols, DEMC with recovery provides
the best connectivity. It can be concluded from the result that
there is a need for a recovery strategy in cluster based routing
protocols, as it helps to improve the packet delivery ratio during
mobility.
Figure 3 shows percentage of packets lost with respect to different node speeds. The result shows that packet loss increases
with the increase in mobility. It is observed during the simulations that the majority of packets are lost during the intra-cluster
communications when normal nodes send information to their
respective cluster heads. However, due to the node mobility,
either the cluster head moves out of the transmission range of a
normal node, or a normal node moves out of the transmission
range of a cluster head. It is evident from the figure that positionbased routing protocols perform well in terms of packet loss under variably mobility. Moreover, using recovery strategy during
the inter-cluster communication phase reduces the packet loss.
In non position-based routing protocols, DEMC with recovery
incurs the least packet loss as compared to DECA and DEMC
without recovery. Similarly, in position-based protocols, GRC
with recovery incurs least packet loss as compared to MAR and
GRC. It is observed that usage of recovery strategy can minimize
75% to 90% packet loss during the inter-cluster communication.
Figure 4 shows percentage of packets lost with respect to different number of nodes. The result shows that position-based
protocols perform well as compared to non position-based protocols. The primary reason behind this is that the location based
routing protocols make better use of the location information
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ROUTING PROTOCOLS FOR MOBILE SENSOR NETWORKS: A COMPARATIVE STUDY
Table 1 Simulation Parameters.
Type
Network
Application
Radio model
Parameter
Area
Node energy at startup
Node deployment
Number of zones
(for position-based protocols)
Data packet size
Broadcast packet size
Packet header size
Eelec
Eamp
Value
1000×1000
3 J/battery
Random
16
100 bytes
25 bytes
25 bytes
50nJ/bit
0.0013 pJ / bit / m4
Figure 1 Packet delivery ratio with respect to different number of nodes.
Figure 2 Packet delivery ratio with respect to different node speeds.
while performing the clustering process. GRC with recovery
performs well as compared to other protocols, because it selects
a cluster head on the basis of center-ness. This factor ensures that
a node is selected as cluster head that is located either at the center or near to the center of a zone. Selecting such cluster heads
96
provide better coverage and thus reduces packet loss during the
inter-cluster communication phase. Moreover, during intercluster communication, a recovery strategy is applied to avoid packet
loss. As a result, GRC with recovery provides better packet delivery ratio compared to respective contender protocols.
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Figure 3 Percentage of packets lost with respect to different node speeds.
Figure 4 Percentage of packets lost with respect to different number of nodes.
Figure 5 shows the average number of packets sent per node
during the cluster head selection phase. In DECA, the average
number of packets sent per node is one (at all times), whereas
for other protocols (DEMC, MAR, and GRC), the number of
packets decreases with the increase in the number of nodes. It
is because, when a node receives a cluster head announcement
that has more weight than its own, then for that specific round
the node will not send its announcement. To do so, DEMC
uses aforesaid timers for sending cluster head announcements.
By using this technique, DEMC sends least average number of
packets during the cluster head selection phase, which not only
reduces the computational overhead but also helps to achieve
energy efficiency.
Figure 6 shows the network lifetime with respect to different
node densities. The network lifetime can be defined as a round,
in which the first node dies, or the number of dead nodes reaches
a pre-defined percentage, or the number of dead nodes reaches
a level where the routing to the destination is no more possible.
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However, as we are experimenting with the clustering based protocols, in which the energy is evenly distributed throughout the
mobile network, we consider the first scenario for the definition of the network lifetime. It is because, when the first node
dies, the number of dead nodes increases in the later rounds, and
within 5-10 rounds the whole network becomes nonoperational.
According to results, non position-based routing protocols outperform position-based protocols in terms of network lifetime.
The primary reason for this behaviour is that location-based protocols consume energy in terms of localization services. Moreover, the number of control messages plays a vital role in the
network lifetime. As DEMC is a non position-based based protocol and uses less control messages, it provides highest network
lifetime among selected protocols, and it further increases with
the increase in the number of nodes.
Figure 7 presents the network lifetime with respect to different node speeds. The result shows that the network lifetime
of non location-based routing protocols (DECA, DEMC, and
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ROUTING PROTOCOLS FOR MOBILE SENSOR NETWORKS: A COMPARATIVE STUDY
Figure 5 Average number of packets sent during cluster head selection.
Figure 6 Network lifetime with respect to different number of nodes.
DEMC with recovery) is high as compared to position-based
protocols. The reason behind this is that the nodes positionupdate frequency increases with the increase in mobility, which
is an energy consuming process. Alternatively, in non positionbased protocols (DECA and DEMC), the speed of nodes does
not have a major impact on the network lifetime. However, the
recovery strategy factor is worth consideration, as it is an energy
consuming process. As shown in Figure 7, the need for recovery
strategy increases with the increase in mobility and affects the
overall network lifetime. This behaviour is shown by the curves
of DEMC with recovery and GRC with recovery protocols.
5.
CONCLUSIONS & FUTURE WORK
In this paper we present performance comparison of position
and non position-based hierarchal clustering protocols for mo-
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bile sensor networks. Through extensive simulations and analysis, we conclude that mobile sensor networks require a recovery strategy during inter-cluster communication, because during
high mobility the cluster heads goes out of the transmission range
of each other. Moreover, position-based routing protocols incur
less packet loss and provide high packet delivery ratio as compared to non position-based protocols, due to optimal cluster
head selection. However, position-based protocols rely on location information for their operation. Therefore, they require
localization mechanisms, which are considered costly in terms of
energy consumption. Consequently, such protocols may deliver
low network lifetime.
Considering the sensor network application and trade off between performance parameters (packet loss, packet delivery ratio, and network lifetime), the routing protocols must be selected accordingly. If the desired objective is to increase the network lifetime under moderate node mobility, then non positionbased protocols, such as DEMC with recovery is the best choice.
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S. ALI ET AL
Figure 7 Network lifetime with respect to different node speeds.
DEMC is suitable for multiple applications, such as monitoring
growth of plants, soil moisture, or habitat monitoring. Alternatively, if an application requires high packet delivery ratio and
there are no severe energy constraints, then usage of positionbased protocols is recommended. GRC is suitable time critical
applications, such as military surveillance, fire, seismic and flood
detection.
For future work, we aim to implement cross layer design for
mobile sensor networks to achieve enhanced energy efficiency
and robustness against packet loss. Moreover, we intend to evaluate the performance of the aforementioned routing protocols
using different mobility models [43, 44].
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