A Sleep Scheduling Algorithm for Target Tracking in Energy Harvesting Sensor Networks

Zeng, Qian; Chen, Hongbin; Zhao, Feng; Li, Xiaohuan

doi:10.1109/cyberc.2014.63

Cited by 5 publications

(4 citation statements)

References 21 publications

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“…For each sensor node, when it turns into sleep and the solar energy is available, it immediately harvests solar energy. If the target is about to be missed (i.e., it is unsuccessful to wake next-moment tracking nodes), the network will wake some nodes which are nearer to the target and have more residual energy to keep tracking the target [34]. Compared to the PPSS algorithm and the proposed algorithm without energy harvesting, the proposed sleep scheduling algorithm can improve the target tracking efficiency and increase the nodes' residual energy.…”

Section: Introductionmentioning

confidence: 99%

“…We used SS algorithm to represent the sleep scheduling algorithm in [34]. We first use PPSS algorithm to track the target, and we also add some communication processes of alarm nodes with their neighbor nodes.…”

Section: Improvement To the Ppss Algorithmmentioning

confidence: 99%

“…We will modify the PPSS algorithm to solve the first problem. We combine the PPSS algorithm with another sleep scheduling algorithm we proposed [34], to predict the target loss situation and try to avoid it, and use double-storage energy harvesting sensor nodes to prolong network lifetime. In this way, it can improve the tracking performance and solve the energy limitation problem.…”

Section: Improvement To the Ppss Algorithmmentioning

confidence: 99%

“…It is necessary to make the sleep scheduling algorithm adaptive to the energy harvesting situation. In this paper, first we combine the PPSS algorithm with another sleep scheduling algorithm we proposed [34] and make some improvement to it. Secondly, we utilize a double-storage energy harvesting architecture [22] to simplify the sleep scheduling process.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Sleep Scheduling Algorithm for Target Tracking in Double-Storage Energy Harvesting Sensor Networks

Chen

Zeng

Zhao

2016

International Journal of Distributed Sensor Networks

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Target tracking is a typical application in wireless sensor networks. Both energy efficiency and tracking performance are important issues that need to be considered. They are a pair of contradictions most of the time. Saving energy often sacrifices tracking performance, while enhancing tracking performance needs to consume more energy. In this paper, an efficient sleep scheduling algorithm is put forward to tackle the above problem in energy harvesting sensor networks. At first, we modify the probabilitybased prediction and sleep scheduling (PPSS) algorithm to track the target and further use another sleep scheduling algorithm we proposed to wake tracking nodes when the target is likely to be missed (i.e., it is unsuccessful to wake next-moment tracking nodes). Secondly, a double-storage energy harvesting architecture is employed to increase residual energy of sensor nodes and to extend network lifetime. Simulation results reveal that the proposed sleep scheduling algorithm can improve tracking performance and prolong network lifetime compared with the PPSS algorithm and the proposed algorithm without energy harvesting.

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Section: Introductionmentioning

confidence: 99%

Section: Improvement To the Ppss Algorithmmentioning

confidence: 99%

Section: Improvement To the Ppss Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations