Title :
Topology Control for Reliable Sensor-to-Sink Data Transport in Sensor Networks
Author :
Wang, Jiong ; Medidi, Sirisha
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA
Abstract :
Wireless sensor networks (WSNs) are generally used for harsh environments involving military surveillance, emergency response, and habitat monitoring. Due to severe resource constraints in sensor nodes, including memory space, energy storage, and communication bandwidth, a need arises for an in-network aggregation of sensory data. We propose a sensor- to-sink transport protocol, which is suitable for data aggregation and provides reliable upstream packet delivery by dynamically configuring inactive nodes as "monitors" to assist in quick loss detection and recovery. To ensure energy efficiency, a minimum set of monitors is preferred; however, the problem of finding a minimum set of monitors is NP-complete. Thus, we propose a distributed greedy heuristic to solve this problem efficiently. Our ns-2-based simulations show significant performance improvements over other transport schemes in terms of throughput and data delivery rate under scenarios with intermittent traffic load and unpredictable node failures.
Keywords :
communication complexity; distributed algorithms; greedy algorithms; telecommunication network topology; wireless sensor networks; NP-complete problem; data aggregation; distributed greedy heuristic; ns-2-based simulations; quick loss detection; quick loss recovery; sensor-to-sink data transport protocol; topology control; upstream packet delivery; wireless sensor networks; Bandwidth; Communication system control; Energy efficiency; Energy storage; Monitoring; Network topology; Surveillance; Telecommunication network reliability; Transport protocols; Wireless sensor networks;
Conference_Titel :
Communications, 2008. ICC '08. IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2075-9
Electronic_ISBN :
978-1-4244-2075-9
DOI :
10.1109/ICC.2008.605