Computer Science ›› 2019, Vol. 46 ›› Issue (9): 120-124.doi: 10.11896/j.issn.1002-137X.2019.09.016

• Network & Communication • Previous Articles     Next Articles

RF Energy Source Deployment Schemes Maximizing Total Energy Harvesting Power

CHI Kai-kai, XU Xing-yuan, HU Ping   

  1. (School of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023,China)
  • Received:2018-08-13 Online:2019-09-15 Published:2019-09-02

Abstract: Radio frequency (RF) energy harvesting is one of the effective methods to deal with the energy limitation of wireless network nodes.The placement of RF energy sources (ESs) determines the energy harvesting power of each node.However,so far,almost no work has been done to study how to select appropriate deployment locations among the candidate deployment locations of ESs.Given the node locations,the number of ESs and candidate deployment locations of ESs,this paper studied and designed the ES deployment schemes which maximize the total energy harvesting power of nodes.Firstly,the problem is modeled as a 0-1 integer programming problem.Then a low-complexity approximation scheme with approximation ratio (1-1/e) and a genetic algorithm based deployment scheme with higher total energy harvesting power are proposed,respectively.Simulation results show that the proposed schemes improve the total energy harvesting power by about 50% compared to the scheme of randomly selecting the deployment locations,and the total energy harvesting power of genetic scheme can be 15% higher than that of approximation scheme.Therefore,the deployment scheme based on genetic scheme can be used for small and medium-sized ES deployment scenarios,while the approximation scheme can be used for large-scale ES deployment scenarios.

Key words: Energy harvesting power, Energy source deployment, Radio frequency energy harvesting

CLC Number: 

  • TN911.2
[1]DUNKELS A,OSTERLIND F,HE Z.An adaptive communication architecture for wireless sensor networks[C]//Proceedings of the 5th International Conference on Embedded Networked Sensor Systems.Sydney:ACM,2007:335-349.
[2]ULUKUS S,YENER A,ERKIP E,et al.Energy harvestingwireless communications:A review of recent advances[J].IEEE Journal on Selected Areas in Communications,2015,33(3):360-381.
[3]LU X,WANG P,NIYATO D,et al.Wireless networks with RF energy harvesting:A contemporary survey[J].IEEE Communications Surveys & Tutorials,2015,17(2):757-789.
[4]BI S,ZENG Y,ZHANG R.Wireless powered communicationnetworks:An overview[J].IEEE Wireless Communications,2016,23(2):10-18.
[5]HE S,CHEN J,JIANG F,et al.Energy provisioning in wireless rechargeable sensor networks [J].IEEE Transactions on Mobile Computing,2013,12(10):1931-1942.
[6]LI Y,FU L,CHEN M,et al.RF-based charger placement for duty cycle guarantee in battery-free sensor networks [J].IEEE Communications Letters,2015,19(10):1802-1805.
[7]ZHANG S,QIAN Z,KONG F,et al.P3:Joint optimization ofcharger placement and power allocation for wireless power transfer[C]//Proceedings of IEEE Conference on Computer Communications,HongKong:IEEE,2015:2344-2352.
[8]DAI H,LIU Y,LIU A,et al.Radiation constrained wirelesscharger placement[C]//Proceedings of IEEE Conference on Computer Communications.San Francisco:IEEE,2016:1-9.
[9]EJAZ W,NAEEM M,BASHARAT M,et al.Efficient wireless power transfer in software-defined wireless sensor networks[J].IEEE Sensors Journal,2016,16(20):7409-7420.
[10]DAI H,WANG X,LIU A,et al.Omnidirectional chargability with directional antennas[C]//Proceedings of IEEE International Conference on Network Protocols.Singapore:IEEE,2016:1-10.
[11]DAI H,WANG X,LIU A,et al.Optimizing wireless charger placement for directional charging[C]//Proceedings of IEEE Conference on Computer Communications.Atlanta:IEEE,2017:1-9.
[12]ZHANG S,WU J,LU S.Collaborative mobile charging[J].IEEE Transactions on Computers,2015,64(3):654-667.
[13]ZHANG S,QIAN Z,WU J,et al.Optimizing itinerary selection and charging association for mobile chargers[J].IEEE Transactions on Mobile Computing,2017,16(10):2833-2846.
[14]LIU T,WU B,WU H,et al.Low-cost collaborative mobile charging for large-scale wireless sensor networks[J].IEEE Transactions on Mobile Computing,2017,16(8):2213-2227.
[15]FUJISHIGE S.Submodular Functions and Optimization[M].Amsterdam:Elsevier,2005.
[1] TIAN Xian-zhong, YAO Chao, ZHAO Chen, DING Jun. 5G Network-oriented Mobile Edge Computation Offloading Strategy [J]. Computer Science, 2020, 47(11A): 286-290.
[2] CHI Kai-kai, XU Xin-chen, WEI Xin-chen. Minimal Base Stations Deployment Scheme Satisfying Node Throughput Requirement in Radio Frequency Energy Harvesting Wireless Sensor Networks [J]. Computer Science, 2018, 45(6A): 332-336.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!