Abstract
In this paper, cluster-based routing (CBR) protocols for addressing issues pertinent to energy consumption, network lifespan, resource allocation and network coverage are reviewed. The paper presents an indepth performance analysis and critical review of selected CBR algorithms. The study is domain-specific and simulation-based with emphasis on the tripartite trade-off between coverage, connectivity and lifespan. The rigorous statistical analysis of selected CBR schemes was also presented. Network simulation was conducted with Java-based Atarraya discrete-event simulation toolkit while statistical analysis was carried out using MATLAB. It was observed that the Periodic, Event-Driven and Query-Based Routing (PEQ) schemes performs better than Low-Energy Adaptive Clustering Hierarchy (LEACH), Threshold-Sensitive Energy-Efficient Sensor Network (TEEN) and Geographic Adaptive Fidelity (GAF) in terms of network lifespan, energy consumption and network throughput.Keywords: Wireless sensor network, Hierarchical topologies, Cluster-based routing, Statistical analysis, Network simulation
Highlights
Wireless sensor network (WSN) is a rapidly evolving field of study which has paved the way for innovative solutions in the area of near and remote sensing and real-time event monitoring (Ingelrest et al, 2005; Crnjin, 2011)
Network simulation was conducted with Javabased Atarraya discrete-event simulation toolkit demonstrated in (Wightman and Labrador, 2009) while statistical analysis was carried out using MATLAB
Statistical analyses were conducted for sparse WSN (SWSN), medium WSN (M-WSN) and dense WSN (D-WSN) scenarios
Summary
Wireless sensor network (WSN) is a rapidly evolving field of study which has paved the way for innovative solutions in the area of near and remote sensing and real-time event monitoring (Ingelrest et al, 2005; Crnjin, 2011). There are a lot of routing algorithms proposed for WSN but the goal of realizing an energy-efficient and optimal routing protocol still remains an open study problem due to the tripartite trade-off between network coverage, connectivity and lifespan (Hou et al, 2005; Akgul et al, 2009; Wang, 2010). The implication of this trade-off is that in an effort to optimize network performance for any one of these factors, there is consequential performance degradation with respect to the two residual factors (Hayajneh and Khasawneh, 2011; Abdelzaher, 2011). Network simulation was conducted with Javabased Atarraya discrete-event simulation toolkit demonstrated in (Wightman and Labrador, 2009) while statistical analysis was carried out using MATLAB
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