Wireless sensor networks consist of a large number of sensor nodes with limited power and resource. To prolong network lifetime, the energy consumption must be somehow reduced In this paper, we propose a localized den...
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ISBN:
(纸本)9781424423019
Wireless sensor networks consist of a large number of sensor nodes with limited power and resource. To prolong network lifetime, the energy consumption must be somehow reduced In this paper, we propose a localized density control algorithm for energy savings. The goals are to maintain a minimal number of active sensor nodes and to reduce radio-traffic intensity while conserving the sensing coverage of the network. Our localized algorithm is based on a greedy solution of a weighted set-cover problem. Each node locally computes whether to sleep or to stay active. Given that the local decision might worsen the sensing coverage, we also introduce a voting scheme for selecting active nodes to assure that a node can sleep if and only if its, sensing area is completely covered by its active neighbors. We have implemented our localized algorithm and voting scheme on Tiny OS and evaluated on TOSSIM. The result indicates that our algorithm is efficient and viable for practical use.
Wireless sensor networks consist of a large number of sensor nodes with limited power and resource. To prolong network lifetime, the energy consumption must be somehow reduced. In this paper, we propose a localized de...
详细信息
ISBN:
(纸本)9781424423019
Wireless sensor networks consist of a large number of sensor nodes with limited power and resource. To prolong network lifetime, the energy consumption must be somehow reduced. In this paper, we propose a localized density control algorithm for energy savings. The goals are to maintain a minimal number of active sensor nodes and to reduce radio-traffic intensity while conserving the sensing coverage of the network. Our localized algorithm is based on a greedy solution of a weighted set-cover problem. Each node locally computes whether to sleep or to stay active. Given that the local decision might worsen the sensing coverage, we also introduce a voting scheme for selecting active nodes to assure that a node can sleep if and only if its sensing area is completely covered by its active neighbors. We have implemented our localized algorithm and voting scheme on Tiny OS and evaluated on TOSSIM. The result indicates that our algorithm is efficient and viable for practical use.
Cognitive radio has emerged as an efficient approach to implement reuse of the licensed spectrums. How to appropriately deploy and construct the secondary network plays a rather important role. In this paper, a novel ...
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ISBN:
(纸本)9781424481804
Cognitive radio has emerged as an efficient approach to implement reuse of the licensed spectrums. How to appropriately deploy and construct the secondary network plays a rather important role. In this paper, a novel deployment scheme, which integrates the radio environment map (REM) and primary exclusive zones (PEZ) together, is proposed. We first illustrate secondary users' achievable region around one primary receiver based on protocol interference model. Then we give the close-form of secondary users' density, which provides a standard for controlling number of secondary users in that achievable region. In other words, our analysis result presents how many secondary transmitters can exist around one primary receiver. We also give a density control algorithm to manage the number of secondary transmitters according to our standard. At last, the keep-out region is simulated and some related parameters are calculated. Meanwhile, the simulation result of secondary density well matches with the theoretical result from our analysis.
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