TY - GEN
T1 - Maximizing charging throughput in rechargeable sensor networks
AU - Ren, Xiaojiang
AU - Liang, Weifa
AU - Xu, Wenzheng
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2014/9/25
Y1 - 2014/9/25
N2 - Energy is one of the most critical optimization objectives in wireless sensor networks. Compared with renewable energy harvesting technology, wireless energy transfer based on magnetic resonant coupling is able to provide more reliable energy supplies for sensors in wireless rechargeable sensor networks. The adoption of wireless mobile chargers (mobile vehicles) to replenish sensors' energy has attracted much attention recently by the research community. Most existing studies assume that the energy consumption rates of sensors in the entire network lifetime are fixed or given in advance, and no constraint is imposed on the mobile charger (e.g., its travel distance per tour). In this paper, we consider the dynamic sensing and transmission behaviors of sensors, by providing a novel charging paradigm and proposing efficient sensor charging algorithms. Specifically, we first formulate a charging throughput maximization problem. Since the problem is NP-hard, we then devise an offline approximation algorithm and online heuristics for it. We finally conduct extensive experimental simulations to evaluate the performance of the proposed algorithms. Experimental results demonstrate that the proposed algorithms are efficient.
AB - Energy is one of the most critical optimization objectives in wireless sensor networks. Compared with renewable energy harvesting technology, wireless energy transfer based on magnetic resonant coupling is able to provide more reliable energy supplies for sensors in wireless rechargeable sensor networks. The adoption of wireless mobile chargers (mobile vehicles) to replenish sensors' energy has attracted much attention recently by the research community. Most existing studies assume that the energy consumption rates of sensors in the entire network lifetime are fixed or given in advance, and no constraint is imposed on the mobile charger (e.g., its travel distance per tour). In this paper, we consider the dynamic sensing and transmission behaviors of sensors, by providing a novel charging paradigm and proposing efficient sensor charging algorithms. Specifically, we first formulate a charging throughput maximization problem. Since the problem is NP-hard, we then devise an offline approximation algorithm and online heuristics for it. We finally conduct extensive experimental simulations to evaluate the performance of the proposed algorithms. Experimental results demonstrate that the proposed algorithms are efficient.
UR - http://www.scopus.com/inward/record.url?scp=84908181272&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84908181272&origin=recordpage
U2 - 10.1109/ICCCN.2014.6911792
DO - 10.1109/ICCCN.2014.6911792
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781479935727
T3 - Proceedings - International Conference on Computer Communications and Networks, ICCCN
BT - 2014 23rd International Conference on Computer Communication and Networks, ICCCN Proceedings
PB - IEEE
T2 - 2014 23rd International Conference on Computer Communication and Networks, ICCCN 2014
Y2 - 4 August 2014 through 7 August 2014
ER -
