Publication | Closed Access
An immune orthogonal learning particle swarm optimisation algorithm for routing recovery of wireless sensor networks with mobile sink
47
Citations
29
References
2012
Year
EngineeringWireless RoutingWireless Sensor SystemEdge ComputingWireless Sensor NetworksSink MovementRouting Recovery ProblemComputer EngineeringMobile ComputingInternet Of ThingsComputer ScienceSensor OptimizationSensor ConnectivityMulti-hop RoutingMobile SinkRouting Protocol
The growth of mobile handheld devices promotes sink mobility in an increasing number of wireless sensor networks (WSNs) applications. The movement of the sink may lead to the breakage of existing routes of WSNs, thus the routing recovery problem is a critical challenge. In order to maintain the available route from each source node to the sink, we propose an immune orthogonal learning particle swarm optimisation algorithm (IOLPSOA) to provide fast routing recovery from path failure due to the sink movement, and construct the efficient alternative path to repair the route. Due to its efficient bio-heuristic routing recovery mechanism in the algorithm, the orthogonal learning strategy can guide particles to fly on better directions by constructing a much promising and efficient exemplar, and the immune mechanism can maintain the diversity of the particles. We discuss the implementation of the IOLPSOA-based routing protocol and present the performance evaluation through several simulation experiments. The results demonstrate that the IOLPSOA-based protocol outperforms the other three protocols, which can efficiently repair the routing topology changed by the sink movement, reduce the communication overhead and prolong the lifetime of WSNs with mobile sink.
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