TY - GEN
T1 - Improve Charging Capability for Wireless Rechargeable Sensor Networks Using Resonant Repeaters
AU - Wang, Cong
AU - Li, Ji
AU - Ye, Fan
AU - Yang, Yuanyuan
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/22
Y1 - 2015/7/22
N2 - Wireless charging has provided a convenient alternative to renew sensors' energy in wireless sensor networks. Due to physical limitations, previous works have only considered recharging a single node at a time, which has limited efficiency and scalability. Recent advance on multi-hop wireless charging is gaining momentum to provide fundamental support to address this problem. However, existing single-node charging designs do not consider and cannot take advantage of such opportunities. In this paper, we propose a new framework to enable multi-hop wireless charging using resonant repeaters. First, we present a realistic model that accounts for detailed physical factors to calculate charging efficiencies. Second, to achieve balance between energy efficiency and data latency, we propose a hybrid data gathering strategy that combines static and mobile data gathering to overcome their respective drawbacks and provide theoretical analysis. Then we formulate multi-hop recharge schedule into a bi-objective NP-hard optimization problem. We propose a two-step approximation algorithm that first finds the minimum charging cost and then calculates the charging vehicles' moving costs with bounded approximation ratios. Finally, upon discovering more room to reduce the total system cost, we develop a post-optimization algorithm that iteratively adds more stopping locations for charging vehicles to further improve the results. Our extensive simulations show that the proposed algorithms can handle dynamic energy demands effectively, and can cover at least three times of nodes and reduce service interruption time by an order of magnitude compared to the single-node charging scheme.
AB - Wireless charging has provided a convenient alternative to renew sensors' energy in wireless sensor networks. Due to physical limitations, previous works have only considered recharging a single node at a time, which has limited efficiency and scalability. Recent advance on multi-hop wireless charging is gaining momentum to provide fundamental support to address this problem. However, existing single-node charging designs do not consider and cannot take advantage of such opportunities. In this paper, we propose a new framework to enable multi-hop wireless charging using resonant repeaters. First, we present a realistic model that accounts for detailed physical factors to calculate charging efficiencies. Second, to achieve balance between energy efficiency and data latency, we propose a hybrid data gathering strategy that combines static and mobile data gathering to overcome their respective drawbacks and provide theoretical analysis. Then we formulate multi-hop recharge schedule into a bi-objective NP-hard optimization problem. We propose a two-step approximation algorithm that first finds the minimum charging cost and then calculates the charging vehicles' moving costs with bounded approximation ratios. Finally, upon discovering more room to reduce the total system cost, we develop a post-optimization algorithm that iteratively adds more stopping locations for charging vehicles to further improve the results. Our extensive simulations show that the proposed algorithms can handle dynamic energy demands effectively, and can cover at least three times of nodes and reduce service interruption time by an order of magnitude compared to the single-node charging scheme.
KW - hybrid data gathering
KW - mobile data gathering
KW - mobile energy replenishment
KW - multi-hop wireless charging
KW - resonant repeater
KW - Wireless sensor networks
UR - https://www.scopus.com/pages/publications/84944326596
U2 - 10.1109/ICDCS.2015.22
DO - 10.1109/ICDCS.2015.22
M3 - Conference contribution
AN - SCOPUS:84944326596
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 133
EP - 142
BT - Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems, ICDCS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th IEEE International Conference on Distributed Computing Systems, ICDCS 2015
Y2 - 29 June 2015 through 2 July 2015
ER -