The paper presents the proposed protocol a hybrid approach is applied for clustering of sensor networks combining BBO and K-means algorithm. The performance of the protocol is compared with SEP, IHCR and ERP in terms of stability period, network life time, residual energy and throughput. The simulation results show that the proposed protocol named as KBBO has improved the performance of these parameters significantly.
Słowa kluczowe: clustering, network life time, stability period, optimization
Abstract
W pracy przedstawiono protokół, w którym stosuje się podejście hybrydowe do grupowania sieci czujników łączących algorytm BBO i K-średnich. Jego wydajność jest porównywana z SEP, IHCR i ERP pod względem okresu stabilności, żywotności sieci, energii resztkowej I przepustowości. Wyniki symulacji pokazują, że prezentowany protokół nazwany KBBO znacznie poprawił wydajność tych parametrów.
Keywords: grupowanie, żywotność sieci, okres stabilności, optymalizacja
A WSN consists of a large number of sensor nodes which can sense physical properties of environment such as humidity, temperature, sound, etc. , collect sensed data and transmit it to the base station through a wireless link. Sensor nodes are characterized by limited energy, low processing capability, low communication range and low memory capacity. Sensor nodes have become more smarter and cheaper in recent days due to development in Micro-Electro-Mechanical Systems (MEMS) [1]. Due to availability of smarter and cheaper sensors, WSN has received wide acceptability with potential application in a large domains: environment monitoring, disaster warning system, health system and military application [2]. Unlike a traditional network, the major research challenge in WSN is how to maximize the network lifetime by reducing energy consumption of the sensor nodes. Clustering is a key technique to reduce energy consumption and extend the lifetime of the network. Besides reduction in energy consumption and extending network life time , clustering technique has many other advantages: scalability, latency reduction, collision avoidance, less overhead and load balancing [3] .Selection of cluster heads (CHs) in energy efficient clustering mechanisms depends upon several factors: residual energy of a node, initial energy, average energy of a network and energy consumption of the node [4]. Clustering is also a key technique for implementing energy efficient routing in WSN. LEACH [5], SEP [6], HEED [7] and PEGASIS [8] are some prominent clustering based routing protocols. The probabilistic models are used to select CHs in these protocols which may result in random selection of CHs irrespective of distribution of nodes and the residual energy of the network. In recent days a number of meta-heuristic techniques such as GA [9], PSO [10] and BBO [11] have been applied in design of energy efficient clustering based routing protocols for WSN. I [...]
Prenumerata
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