A power efficient cluster-based routing algorithm for wireless sensor networks: Honeybees swarm intelligence based approach

The design of low-power scalable wireless sensor networks remains a key challenge of the research. Clustering and routing have been widely studied for extending the lifetime of a network, which is a critical issue in sensor networks. Routing involves non-negligible operations, which considerably affect the network lifetime and the throughput. The clustering technique with data aggregation on cluster heads has an influence on the overall performance of the network since it is favoring a maximum network lifetime. This paper presents a novel cluster-based routing protocol called ABC-SD. The proposed protocol exploits the biologically inspired fast and efficient searching features of the Artificial Bee Colony metaheuristic to build low-power clusters. For the choice of cluster heads, a multi-objective fitness function is designed by using a Linear Programming formulation. The routing problem is addressed by a cost-based function that makes a trade-off between the energy efficiency and the number of hops of the path. The clustering process is achieved at the Base Station with a centralized control algorithm, which exploits energy levels and the neighborhood information of location-unaware sensors. As for the routing of gathered data, it is realized in a distributed manner. Furthermore, unlike the existing protocols in the literature, a realistic energy model is adopted in the considered network model. The proposed protocol is intensively experimented with a number of topologies in various network scenarios and the results are compared with the well-known cluster-based routing protocols that include the swarm intelligence based protocols. The obtained results demonstrate the effectiveness of the proposed protocol in terms of network lifetime, network coverage and the amount of packets delivered to the Base Station. •LP formulation of the clustering problem.•Routing problem addressed by a CF.•ABC-based clustering algorithm with a tradeoff between the energy consumption and the quality of the communication link.•Pre-established routing mechanism in which routing paths are less costly in terms of power consumption.•Integration of a realistic energy model and realistic network settings and simulation of the proposed protocol to demonstrate its performance compared to some existing protocols.