Abstract
Wireless Sensor Network (WSN) consists of small low-cost, low-power multifunctional nodes interconnected to efficiently aggregate and transmit data to sink. Cluster-based approaches use some nodes as Cluster Heads (CHs) and organize WSNs efficiently for aggregation of data and energy saving. A CH conveys information gathered by cluster nodes and aggregates/compresses data before transmitting it to a sink. However, this additional responsibility of the node results in a higher energy drain leading to uneven network degradation. Low Energy Adaptive Clustering Hierarchy (LEACH) offsets this by probabilistically rotating cluster heads role among nodes with energy above a set threshold. CH selection in WSN is NP-Hard as optimal data aggregation with efficient energy savings cannot be solved in polynomial time. In this work, a modified firefly heuristic, synchronous firefly algorithm, is proposed to improve the network performance. Extensive simulation shows the proposed technique to perform well compared to LEACH and energy-efficient hierarchical clustering. Simulations show the effectiveness of the proposed method in decreasing the packet loss ratio by an average of 9.63% and improving the energy efficiency of the network when compared to LEACH and EEHC.
Highlights
Wireless Sensor Network (WSN) finds extensive application in both civilian and military applications
Simulations were carried out using Low Energy Adaptive Clustering Hierarchy (LEACH), EEHC, firefly, and synchronous firefly algorithm
LEACH protocol needs the user to specify probability for use with a threshold function to determine whether a node will become a Cluster Heads (CHs) or not leading to NP problem
Summary
Wireless Sensor Network (WSN) finds extensive application in both civilian and military applications. It has been extensively used in target tracking, surveillance, monitor natural disasters, biomedical applications, habitat monitoring, and building management systems [1]. Sensor nodes in natural disasters sense/detect an environment to forecast disasters. Sensors ad hoc deployment in a volcanic area detects earthquakes/eruptions [2]. WSNs monitor specific areas using sensors collect data and send to base station (BS). To save energy some nodes selected based on the objective function act as Cluster Head (CH) and aggregate data from its entire neighbor. The CH sends the data to the BS and reduces network overheads to save energy in each node
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