Journal
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 65, Issue 1, Pages 278-291Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2015.2391119
Keywords
Charging delay; energy efficient; energy harvesting; mobile charging; sensor networks; wireless charging
Categories
Funding
- National Natural Science Foundation of China [61228302]
- ZJSF [LY14F030016]
- National Program for Special Support of Top Notch Young Professionals, Fundamental Research Funds for the Central Universities [2014XZZX001-03]
- Division Of Computer and Network Systems
- Direct For Computer & Info Scie & Enginr [0845994] Funding Source: National Science Foundation
Ask authors/readers for more resources
Recent years have witnessed several new promising technologies to power wireless sensor networks, which motivate some key topics to be revisited. By integrating sensing and computation capabilities to the traditional radio-frequency identification (RFID) tags, the Wireless Identification and Sensing Platform (WISP) is an open-source platform acting as a pioneering experimental platform of wireless rechargeable sensor networks. Different from traditional tags, an RFID-based wireless rechargeable sensor node needs to charge its onboard energy storage above a threshold to power its sensing, computation, and communication components. Consequently, such charging delay imposes a unique design challenge for deploying wireless rechargeable sensor networks. In this paper, we tackle this problem by planning the optimal movement strategy of the mobile RFID reader, such that the time to charge all nodes in the network above their energy threshold is minimized. We first propose an optimal solution using the linear programming (LP) method. To further reduce the computational complexity, we then introduce a heuristic solution with a provable approximation ratio of (1 + theta)/(1 - epsilon) by discretizing the charging power on a 2-D space. Through extensive evaluations, we demonstrate that our design outperforms the set-cover-based design by an average of 24.7%, whereas the computational complexity is O((N/epsilon)(2)). Finally, we consider two practical issues in system implementation and provide guidelines for parameter setting.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available