Title :
Multiobjective energy-aware node selection
Author :
Le, Qiang ; Kaplan, Lance M. ; McClellan, James H.
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA
Abstract :
This work develops a resource management strategy for a wireless sensor network of bearings-only sensors. Specifically, the resource manager determines which nodes actively sense and communicate during each snapshot in order to achieve a tolerable level of geolocalization accuracy while attempting to maximize the effective lifetime of the network. Unlike other methods that use the total energy consumed for the given snapshot as an energy-based metric, a new energy-based (EB) metric can achieve load balancing of the nodes without resorting to computationally demanding non-myopic optimization. Simulation results show that EB provides longer lifetime than an existing geometry-based (GB) metric. We consider an adaptive transmission range control based upon the remaining battery level and the physical location knowledge of nodes in the network. The activation decision is performed in a decentralized manner over the active set of nodes. Each active node transmits just far enough to reach all the active nodes for information sharing and the potentially active nodes for information handoff. In determining the active set, both global and local approaches are considered. The global approach assumes each node knows the physical location of every other node in the network. On the other hand, the local approach assumes that a node only knows the location of itself, the previous active set, and neighboring nodes
Keywords :
resource allocation; scheduling; telecommunication network routing; wireless sensor networks; activation decision; adaptive transmission range control; bearings-only sensors; energy-based metric; geolocalization accuracy; geometry-based metric; information handoff; information sharing; multiobjective energy-aware node selection; nonmyopic optimization; resource management; wireless sensor network; Computer networks; Energy consumption; Entropy; Laboratories; Military computing; Power engineering and energy; Resource management; Routing; Signal processing algorithms; Wireless sensor networks;
Conference_Titel :
Aerospace Conference, 2006 IEEE
Conference_Location :
Big Sky, MT
Print_ISBN :
0-7803-9545-X
DOI :
10.1109/AERO.2006.1655945