Mobility-Aware Multi-Objective Task Allocation for Wireless Sensor Networks

This paper proposes a Multi-Objective Optimization Algorithm for dynamic task allocation within Internet of Things (IoT) and especially Wireless Sensor Networks (WSN) with mobile nodes. The algorithm employs a prediction of future node positions to optimize task deployment for possible network states. The resulting algorithm allows an IoT network to incorporate mobile nodes efficiently without sacrificing availability and reliability. To this end, task allocations, which optimize multiple network metrics, are evaluated and preemptively redeployed to account for the movement of the mobile nodes. Using a simulation environment, the algorithm is evaluated in multiple scenarios including different network sizes and mobility models and predictions, while measuring Network Lifetime, Latency and successful task execution. Comparing with an existing Multi-Objective algorithm designed for static optimization, the approach shows improved performance in both Latency and task execution, in addition to stable Network Lifetime on the larger network size.