Dynamic power management in new architecture of wireless sensor networks

被引:53
作者
Lin, Chuan [2 ]
Xiong, Naixue [1 ]
Park, Jong Hyuk [3 ]
Kim, Tai-hoon [4 ]
机构
[1] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30303 USA
[2] Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China
[3] Kyungnam Univ, Dept Comp Sci & Engn, Masan, South Korea
[4] Hannam Univ, Div Multimedia Engn, Taejon, South Korea
基金
美国国家科学基金会;
关键词
wireless sensor networks; cubic and cross-layer architecture; dynamic power management; optimal geographical density control (OGDC); data fusion; SYSTEMS;
D O I
10.1002/dac.989
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Dynamic power management (DPM) technology has been widely used in sensor networks. Though many specific technical challenges remain and deserve much further study, the primary factor currently limiting progress in sensor networks is not these challenges but is instead the lack of an overall sensor network architecture. In this paper, we first develop a new architecture of sensor networks. Then we modify the sleep state policy developed by Sinha and Chandrakasan in (IEEE Design Test Comput. 2001; 18(2):62-74) and deduce that a new threshold satisfies the sleep-state transition policy. Under this new architecture, nodes in deeper sleep states consume lower energy while asleep, but require longer delays and higher latency costs to awaken. Implementing DPM with considering the battery status and probability of event generation will reduce the energy consumption and prolong the whole lifetime of the sensor networks. We also propose a new energy-efficient DPM, which is a modified sleep state policy and combined with optimal geographical density control (OGDC) (Wireless Ad Hoc Sensor Networks 2005; 1(1-2):89-123) to keep a minimal number of sensor nodes in the active mode in wireless sensor networks. Implementing dynamic power management with considering the battery status, probability of event generation and OGDC will reduce the energy consumption and prolong the whole lifetime of the sensor networks. Copyright (C) 2008 John Wiley & Sons, Ltd.
引用
收藏
页码:671 / 693
页数:23
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