Load Balancing Technique Based on Broadcasting and Residual Energy Using Adaptive Clustering Hierarchy Protocol (LBEACH)
- 1 Al Albayt University, Jordan
- 2 Amman Arab University, Jordan
Copyright: © 2020 Abdullah Soliman Alshraa and Venus Wazeer Samawi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
One of the important factors of Wireless Sensor Networks (WSNs) is sensors lifetime. Elongating sensors lifetime increases the benefits from the network capabilities as much as possible. To elongate WSNs lifetime, power consumption should be reduced. To do so, load balance technique is applied to distribute the energy consumption among cluster’s nodes in the WSN. In each cluster, the node that acts as Cluster Head (CH) is the one that significantly suffers from power consumption problem. To elongate the WSNs lifetime, different sensor node is elected to act as CH for a period of time (round). Choosing the proper CH per round greatly affects the energy efficiency in the network. In this study, a new protocol for clustered heterogeneous WSNs (called LBEACH) is suggested to reduce power consumption and prolong the network lifetime. Distributed clustering methodology, with a novel algorithm to elect cluster heads in each round, is applied and tested. The elected CH is the node that has the minimal estimated broadcast cost and the highest residual energy. The estimated broadcast cost of each node is the estimated cost needed for sending a message to all other nodes within the same cluster and to the base-station. LBEACH performance is measured using network lifetime, power consumption and throughput. By comparing LBEACH performance with other protocols, Low Energy Adaptive Clustering Hierarchy (LEACH) and Stable Election Protocol (SEP) protocols, it was found that LBEACH shows a significant improvement in the network lifetime, power consumption and throughputs toward Base-Station (BS).
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- Wireless Sensor Networks
- Cluster Head Election
- Load Balance
- Broadcast-Cost Estimation
- Power Consumption