Energy-constrained task mapping and scheduling in wireless sensor networks

Collaboration among sensors through parallel processing mechanisms emerges as a promising solution to achieve high processing power in resource-restricted wireless sensor networks (WSN). Although task mapping and scheduling in wired networks of processors has been well studied in the past, their application to WSNs remains largely unexplored. Due to the limitations of WSNs, existing algorithms cannot be directly implemented in WSNs. In this paper, a task mapping and scheduling solution for energy-constrained applications in WSNs, energy-constrained task mapping and scheduling (EcoMapS), is presented. EcoMapS incorporates channel modeling, concurrent task mapping, communication and computation scheduling, and sensor failure handling algorithm. The performance of EcoMapS is evaluated through simulations with randomly generated directed acyclic graphs (DAG). Simulation results show significant performance improvements compared with an existing mechanism in terms of minimizing schedule lengths subject to energy consumption constrains