TY - JOUR
T1 - Particle swarm optimization based energy efficient clustering and sink mobility in heterogeneous wireless sensor network
AU - Sahoo, Biswa Mohan
AU - Amgoth, Tarachand
AU - Pandey, Hari Mohan
PY - 2020/9/1
Y1 - 2020/9/1
N2 - In a WSN, sensor node plays a significant role. Working of sensor node depends upon its battery's life. Replacements of batteries are found infeasible once they are deployed in a remote or unattended area. Plethora of research had been conducted to address this challenge, but they suffer one or the other way. In this paper, a particle swarm optimization (PSO) algorithm integrated with an energy efficient clustering and sink mobility ((PSO-ECSM) is proposed to deal with both cluster head selection problem and sink mobility problem. Extensive computer simulations are conducted to determine the performance of the PSO-ECSM. Five factors such as residual energy, distance, node degree, average energy and energy consumption rate (ECR) are considered for CH selection. An optimum value of these factors is determined through PSO-ECSM algorithm. Further, PSO-ECSM addresses the concern of relaying the data traffic in a multi-hop network by introducing sink mobility. PSO-ECSM's performances are tested against the state-of-the-art algorithms considering five performance metrics (stability period, network, longevity, number of dead nodes against rounds, throughput and network's remaining energy). Statistical tests are conducted to determine the significance of the performance. Simulation results show that the PSO-ECSM improves stability period, half node dead, network lifetime and throughput vis-à-vis ICRPSO by 24.8%, 31.7%, 9.8 %, and 12.2%, respectively.
AB - In a WSN, sensor node plays a significant role. Working of sensor node depends upon its battery's life. Replacements of batteries are found infeasible once they are deployed in a remote or unattended area. Plethora of research had been conducted to address this challenge, but they suffer one or the other way. In this paper, a particle swarm optimization (PSO) algorithm integrated with an energy efficient clustering and sink mobility ((PSO-ECSM) is proposed to deal with both cluster head selection problem and sink mobility problem. Extensive computer simulations are conducted to determine the performance of the PSO-ECSM. Five factors such as residual energy, distance, node degree, average energy and energy consumption rate (ECR) are considered for CH selection. An optimum value of these factors is determined through PSO-ECSM algorithm. Further, PSO-ECSM addresses the concern of relaying the data traffic in a multi-hop network by introducing sink mobility. PSO-ECSM's performances are tested against the state-of-the-art algorithms considering five performance metrics (stability period, network, longevity, number of dead nodes against rounds, throughput and network's remaining energy). Statistical tests are conducted to determine the significance of the performance. Simulation results show that the PSO-ECSM improves stability period, half node dead, network lifetime and throughput vis-à-vis ICRPSO by 24.8%, 31.7%, 9.8 %, and 12.2%, respectively.
KW - Clustering, Energy Consumption Rate (ECR)
KW - Energy Efficiency
KW - Optimization
KW - PSO-based CH selection
KW - Sink mobility
KW - Wireless sensor network
UR - http://www.scopus.com/inward/record.url?scp=85086438635&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85086438635&partnerID=8YFLogxK
U2 - 10.1016/j.adhoc.2020.102237
DO - 10.1016/j.adhoc.2020.102237
M3 - Article (journal)
AN - SCOPUS:85086438635
SN - 1570-8705
VL - 106
JO - Ad Hoc Networks
JF - Ad Hoc Networks
M1 - ADHOC_2020_225_R4
ER -