Computational intelligence based metaheuristic for energy-efficient routing in wireless sensor networks

Wireless Sensor Networks (WSNs) open up a new research horizon, with wide range of data oriented applications. Energy efficient routing is one such area of interest, which require non-conventional paradigm for design and development of protocols. Computational Intelligence (CI) based metaheuristic can be used for optimal routing of data, to deliver events in an energy constraint WSNs environment. In this paper, we present BeeSwarm, a CI based, energy-efficient hierarchical routing protocol for WSNs. Our protocol consists of three phases: 1) Set-up Phase-BeeCluster, 2) Route Discovery Phase-BeeSearch and 3) Data Transmission Phase-BeeCarrier. Integration of three phases for node clustering, data routing and transmission, is the key aspect of our proposed protocol, which ultimately contributes to its robustness. Evaluation of simulation results show that BeeSwarm perform better in terms of packet delivery, energy consumption and throughput with increased network life compared to other CI based hierarchical routing protocols.