IJCSN - International Journal of Computer Science and Network, Volume 8, Issue 1, February 2019 ISSN (Online) : 2277-5420 www.IJCSN.org Impact Factor: 1.5 91 Copyright (c) 2019 International Journal of Computer Science and Network. All Rights Reserved. Energy Efficient Hybrid FCM and Cuckoo optimization based clustering Technique for Wireless Multimedia Sensor Network 1 Addisalem Genta; 2 D K Lobiyal 1 School of Computer and System Sciences, Jawaharlal Nehru university New Delhi-110067, India 2 School of Computer and System Sciences, Jawaharlal Nehru university New Delhi-110067, India Abstract - One of the prime limitations of Wireless Multimedia Sensor Network (WMSN) is high energy consumption. The sensor nodes are powered by battery of finite energy which rapidly gets depleted during transmission of big size multimedia data like video, image and audio in the network. This process increases the rate of energy dissipation in the network and indirectly shortens the life span of the whole network. Since recharging of the battery of sensor nodes is not feasible, preserving the already available energy of the network is vital consideration in the design of various protocols. In this study, hybrid energy efficient FCM and cuckoo optimization based clustering algorithm is proposed. The fuzzy c-mean method is used in the cluster formation while cuckoo search algorithm is employed for CH election. The experimental results of MATLAB simulation of the proposed technique show that the technique is suitable for maintaining the energy of the network for longer time and it also outperforms the already existing algorithms in terms of network life time and minimum energy consumption. Keywords - WMSNs, Cuckoo search, FCM, network life time, energy consumption 1. Introduction ireless Multimedia sensor network contains spatially distributed battery powered nodes which with capability of retrieving information from their surroundings. This network is used mainly for tracking and monitoring environmental and physical conditions in the form of image, video or audio [1]. These sensor nodes are wirelessly connected and send their data to the central station. Environmental monitoring, remote health care, and infrastructure health monitoring are some of the potential application areas of the network [2]. The advancement in Micro Electro Mechanical System has promoted the invention of very small powerful sensors which are capable of high computation. However, due to limited battery power, the nodes are not performing for longer period and up to the application requirement too. This is why energy consumption becomes a crucial issue in the design of WSN. To improve the network life time and QoS, energy aware techniques should be considered during the design of WSN. One of the best solutions is to arrange the sensor nodes in cluster form and make the data transmission less energy consuming. In clustering technique, each node has its own separate cluster or group. The cluster member nodes forward collected data to their cluster head (CH). Besides, the cluster head aggregates all received data in to one single packet and send it to the sink node. Nevertheless, allocating nodes to their appropriate cluster where their energy consumption can be minimized and determining the optimal number of cluster for the network is still a hot research topic. One of the energy aware clustering methods is Low Energy Adaptive Clustering Hierarchy (LEACH) [3]. LEACH encompasses two stages- setup and steady state stage. All nodes generate a random number i.e. ( ) during the setup phase. This randomly generated number decides whether nodes can be cluster head or not in each round. The elected cluster head sends advertisement message to nodes within its radio range. RSSI is used to determine the nearest nodes to the cluster head. Once the cluster members are known, the CH assigns time division multiple accesses (TDMA) slot for all members in the cluster. Within the given slot period, the cluster members send their data during steady state to the cluster head. Since LEACH is fully dependent on probability for determination of CH, it suffers from the following drawbacks. The first problem is that LEACH W
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IJCSN - International Journal of Computer Science and Network, Volume 8, Issue 1, February 2019 ISSN (Online) : 2277-5420 www.IJCSN.org Impact Factor: 1.5
91
Copyright (c) 2019 International Journal of Computer Science and Network. All Rights Reserved.
Energy Efficient Hybrid FCM and Cuckoo optimization
based clustering Technique for Wireless Multimedia
Sensor Network
1Addisalem Genta; 2D K Lobiyal
1 School of Computer and System Sciences, Jawaharlal Nehru university
New Delhi-110067, India
2 School of Computer and System Sciences, Jawaharlal Nehru university
New Delhi-110067, India
Abstract - One of the prime limitations of Wireless Multimedia Sensor Network (WMSN) is high energy consumption. The sensor
nodes are powered by battery of finite energy which rapidly gets depleted during transmission of big size multimedia data like video,
image and audio in the network. This process increases the rate of energy dissipation in the network and indirectly shortens the life span
of the whole network. Since recharging of the battery of sensor nodes is not feasible, preserving the already available energy of the
network is vital consideration in the design of various protocols. In this study, hybrid energy efficient FCM and cuckoo optimization
based clustering algorithm is proposed. The fuzzy c-mean method is used in the cluster formation while cuckoo search algorithm is
employed for CH election. The experimental results of MATLAB simulation of the proposed technique show that the technique is
suitable for maintaining the energy of the network for longer time and it also outperforms the already existing algorithms in terms of
network life time and minimum energy consumption.
Keywords - WMSNs, Cuckoo search, FCM, network life time, energy consumption
1. Introduction
ireless Multimedia sensor network contains
spatially distributed battery powered nodes
which with capability of retrieving information
from their surroundings. This network is used mainly for
tracking and monitoring environmental and physical
conditions in the form of image, video or audio [1]. These
sensor nodes are wirelessly connected and send their data
to the central station. Environmental monitoring, remote
health care, and infrastructure health monitoring are some
of the potential application areas of the network [2]. The
advancement in Micro Electro Mechanical System has
promoted the invention of very small powerful sensors
which are capable of high computation. However, due to
limited battery power, the nodes are not performing for
longer period and up to the application requirement too.
This is why energy consumption becomes a crucial issue in
the design of WSN. To improve the network life time and
QoS, energy aware techniques should be considered during
the design of WSN. One of the best solutions is to arrange
the sensor nodes in cluster form and make the data
transmission less energy consuming. In clustering
technique, each node has its own separate cluster or group.
The cluster member nodes forward collected data to their
cluster head (CH). Besides, the cluster head aggregates all
received data in to one single packet and send it to the sink
node. Nevertheless, allocating nodes to their appropriate
cluster where their energy consumption can be minimized
and determining the optimal number of cluster for the
network is still a hot research topic. One of the energy
aware clustering methods is Low Energy Adaptive
Clustering Hierarchy (LEACH) [3].
LEACH encompasses two stages- setup and steady state
stage. All nodes generate a random number i.e.
( ) during the setup phase. This randomly
generated number decides whether nodes can be cluster
head or not in each round. The elected cluster head sends
advertisement message to nodes within its radio range.
RSSI is used to determine the nearest nodes to the cluster
head. Once the cluster members are known, the CH assigns
time division multiple accesses (TDMA) slot for all
members in the cluster. Within the given slot period, the
cluster members send their data during steady state to the
cluster head. Since LEACH is fully dependent on
probability for determination of CH, it suffers from the
following drawbacks. The first problem is that LEACH
[14] Yang, X.S. and Deb, S., 2009, December. Cuckoo
search via Lévy flights. In Nature & Biologically
Inspired Computing, 2009. NaBIC 2009. World
Congress on (pp. 210-214). IEEE.
[15] Khabiri, M. and Ghaffari, A., 2018. Energy-Aware
Clustering-Based Routing in Wireless Sensor Networks
Using Cuckoo Optimization Algorithm. Wireless
Personal Communications, 98(3), pp.2473-2495.
Addisalem Genta was born in Assela, Ethiopia, in 1985. He received the B.Sc. degree in electrical and computer engineering from Jimma University, Jimma, Ethiopia, in 2007, and the M.Sc. in computer engineering from Addisababa University, Addisababa, Ethiopia, in 2011. Currently, he is pursuing his PhD degree in computer engineering from Jawaharlal Nehru University, New Delhi, India since 2014. In 2007, he joined the Ethiopian Electric power Corporation as an Electrical power line design Engineer. In 2012, he joined Mettu university - Department of Electrical and computer Engineering as a Lecturer, and was assigned as dean of Faculty of Technology same year and served for two and half years. Later on in 2014, he joined Ambo University, Department of Electrical and Computer Engineering as lecturer and still he is working over there. His current research interests include ICT in Ethiopia, Role of ICT for development, multimedia data processing in wireless sensor network, energy efficient WMSN, energy harvesting for WMSN, and energy efficient routing protocol for WSN. Dr D K Lobiyal received his Ph.D and M. Tech (Computer Science & technology) from School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India in 1996 and 1991, respectively, and B. Tech. (Computer Science and Engineering) from Lucknow University, India in 1988. He is currently working as Professor in the School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India. His research interest includes Mobile Ad hoc Networks, Natural Language Processing, and Neurocomputing. Dr. Lobiyal has published papers in International journals and conferences including IEEE, Wiley and Sons, Springer, Inderscience, WSEAS, IGI Global, and ACTA Press.