A Comprehensive Analysis of CBCDACP in Wireless Sensor Networks

Abstract

As wireless sensor networks are equipped with sensor nodes which have a limited energy and sensing capabilities, a good routing protocol must be designed to make the network energy efficient. In [1] we proposed a centralized routing protocol called Central Base Station Controlled Density Aware Clustering Protocol (CBCDACP) where the base station centrally performs the cluster formation task. In CBCDACP, an optimum set of cluster heads is selected by using a new cluster head selection algorithm focusing on both the density of the sensor nodes and the minimum distances among the cluster head and its neighbor nodes. It calculates the optimum set of cluster head by first selecting the candidate node, then calculating the minimum distance and also calculates the density and finally executing the main BS setup algorithm. In this paper, a comprehensive analysis of CBCDACP algorithm is stated varying the simulation parameters to demonstrate the robustness of this algorithm and explaining the algorithm blocks of CBCDACP. The simulation performance of CBCDACP is then compared with some clustering-based schemes such as Static-Clustering, Low Energy Adaptive Clustering Hierarchy (LEACH), Centralized LEACH (LEACH-C). Simulation results show that CBCDACP can improve system life time and energy efficiency in terms of different simulation performance metrics over its comparatives . As wireless sensor networks are equipped with sensor nodes which have a limited energy and sensing capabilities, a good routing protocol must be designed to make the network energy efficient. In [1] we proposed a centralized routing protocol called Central Base Station Controlled Density Aware Clustering Protocol (CBCDACP) where the base station centrally performs the cluster formation task. In CBCDACP, an optimum set of cluster heads is selected by using a new cluster head selection algorithm focusing on both the density of the sensor nodes and the minimum distances among the cluster head and its neighbor nodes. It calculates the optimum set of cluster head by first selecting the candidate node, then calculating the minimum distance and also calculates the density and finally executing the main BS setup algorithm. In this paper, a comprehensive analysis of CBCDACP algorithm is stated varying the simulation parameters to demonstrate the robustness of this algorithm and explaining the algorithm blocks of CBCDACP. The simulation performance of CBCDACP is then compared with some clustering-based schemes such as Static-Clustering, Low Energy Adaptive Clustering Hierarchy (LEACH), Centralized LEACH (LEACH-C). Simulation results show that CBCDACP can improve system life time and energy efficiency in terms of different simulation performance metrics over its comparatives .