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Abstract-In recent studies, using mobile elements (MEs) as mechanical carriers of data has been shown to be an effective way of prolonging sensor network life time and relaying information in partitioned networks. As the data generation rates of sensors may vary, some sensors need to be visited more frequently than others. In this paper, a partitioning-based algorithm is presented that schedules the movements of MEs in a sensor network such that there is no data loss due to buffer overflow. Simulation results show that the proposed Partitioning Based Scheduling (PBS) algorithm performs well in terms of reducing the minimum required ME speed to prevent data loss, providing high predictability in inter-visit durations, and minimizing the data loss rate for the cases when the ME is constrained to move slower than the minimum required ME speed.

Abstract-Although task mapping and scheduling in wired networks of processors has been extensively studied, their application to WSNs remains largely unexplored. Existing algorithms cannot be directly implemented in WSNs due to limited resource availability and shared communication medium. In this work, an application-independent task mapping and scheduling solution in multi-hop WSNs is presented that provides realtime guarantees. Using a novel multi-hop channel model and a communication scheduling algorithm, computation tasks and associated communication events are scheduled simultaneously with a dynamic critical-path scheduling algorithm. Dynamic Voltage Scaling (DVS) mechanism is implemented to further optimize energy consumption. According to the simulation results, the proposed solution outperforms existing mechanisms in terms of guaranteeing application deadlines with minimum energy consumption.