Cluster‐based information processing in wireless sensor networks: an energy‐aware approach

Emerging Wireless Sensor Network (WSN) applications demand considerable computation capacity for in‐network processing in resource limited WSN environments. To achieve the required processing capacity under energy consumption constraints, collaboration among sensors through parallel processing methods emerges as a promising solution. Although such methods have been extensively studied in wired networks of processors, its counterpart for WSNs remains largely unexplored. In this paper, a localized task mapping and scheduling solution for energy‐constrained applications in WSNs, Energy‐constrained Task Mapping and Scheduling (EcoMapS), is presented. EcoMapS guarantees energy consumption constraints while minimizing schedule length. EcoMapS incorporates channel modeling, concurrent task mapping, communication and computation scheduling, and sensor failure handling algorithms. Simulation results show significant performance improvements of EcoMapS over existing mechanisms in terms of minimizing schedule lengths subject to energy consumption constrains.