An Unequal Cluster-Based Routing Protocol in Wireless Sensor Networks

Topics: Routing, Wireless sensor network, Sensor node Pages: 40 (11110 words) Published: December 30, 2010
DOI 10.1007/s11276-007-0035-8
An unequal cluster-based routing protocol in wireless
sensor networks
Guihai Chen E Chengfa Li E Mao Ye E JieWu
Springer Science + Business Media, LLC 2007
Abstract Clustering provides an effective method for prolonging the lifetime of a wireless sensor network. Current
clustering algorithms usually utilize two techniques; selecting cluster heads with more residual energy, and rotating
cluster heads periodically to distribute the energy consumption among nodes in each cluster and extend the network
lifetime. However, they rarely consider the hot spot problem in multihop sensor networks. When cluster heads cooperate
with each other to forward their data to the base
station, the cluster heads closer to the base station are burdened with heavier relay traffic and tend to die much faster,
leaving areas of the network uncovered and causing network
partitions. To mitigate the hot spot problem, we propose
an Unequal Cluster-based Routing (UCR) protocol. It
groups the nodes into clusters of unequal sizes. Cluster heads closer to the base station have smaller cluster sizes than those farther from the base station, thus they can preserve some
energy for the inter-cluster data forwarding. A greedy geographic and energy-aware routing protocol is designed for
the inter-cluster communication, which considers the tradeoff between the energy cost of relay paths and the residual
energy of relay nodes. Simulation results show that UCR
mitigates the hot spot problem and achieves an obvious improvement on the network lifetime.
Keywords Wireless sensor networks . Unequal clustering .
Routing . Network lifetime . Hot spot problem
G. Chen () . C. Li . M. Ye
State Key Laboratory for Novel Software Technology, Nanjing
University Nanjing, 210093, P. R. China
J. Wu
Department of Computer Science and Engineering, Florida
Atlantic University Boca Raton, FL 33431, USA
1 Introduction
Rapid technological advances in micro-electro-mechanical
systems (MEMS) and low-power wireless communication
have enabled the deployment of large scale wireless sensor
networks. The potential applications of sensor networks
are highly varied, such as environmental monitoring, target
tracking, and battlefield surveillance [1, 2]. Sensors in
such a network are equipped with sensing, data processing
and wireless communication capabilities. Distinguished
from traditional wireless networks, sensor networks are characterized by severe power, computation, and memory constraints.
Due to limited and non-rechargeable energy provision,
the energy resource of sensor networks should be
managed wisely to extend the lifetime of sensors. Although
much attention has been paid to low-power hardware design
and collaborative signal processing techniques, energy efficient algorithms must be supplied at various networking
layers. In addition, it is very important to balance the energy consumption among all sensor nodes to prolong the network
We consider a network of energy-constrained sensors that
are deployed over a geographic area for monitoring the environment. Each sensor periodically produces information as
it monitors its vicinity. The basic operation in such a network is the systematic gathering and transmission of sensed data to a base station for further processing. In order to achieve high energy efficiency and increase the network scalability, sensor nodes can be organized into clusters. Data collected from

sensors are sent to the cluster head first, and then forwarded to the base station. The high density of sensor networks
may lead to multiple adjacent sensors generating redundant
sensed data, thus data aggregation can be used to eliminate
the data redundancy and reduce the communication load [3].
Wireless Netw (2009) 15:193.207
Published online: 3 April 2007
For periodical data-gathering applications, a method to group sensor nodes into clusters...

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