Computer Science ›› 2018, Vol. 45 ›› Issue (8): 119-124.doi: 10.11896/j.issn.1002-137X.2018.08.021

• Network & Communication • Previous Articles     Next Articles

High-throughput and Load-balanced Node Access Scheme for RF-energy Harvesting Wireless Sensor Networks

CHI Kai-kai ,WEI Xin-chen, LIN Yi-min   

  1. School of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023,China
  • Received:2017-06-30 Online:2018-08-29 Published:2018-08-29

Abstract: For the traditional wireless sensor networks (WSNs),their practical applications are greatly restricted by the inconvenient or even impossible battery replacement.This paper considered the RF-energy harvesting WSNs where the positions of energy sources,nodes and base stations (i.e.,sinks) are given and studied how to arrange the access base stations for each node,aiming to maximize the total throughput of the entire network nodes while satisfying the load balancing constraints of all base stations.Firstly,the energy harvesting model and information transmission model were built.Then,this node access problem was modeled as a 0-1 integer programming problem.Next,a low-complexity algorithm and a greedy algorithm were proposed for solving this problem.Simulation results demonstrate that the node access scheme obtained by the greedy scheme is able to achieve higher total network throughput compared to the low-complexity scheme.Due to its relative high complexity,the greedy scheme can be used in scenarios where the number of nodes is not very large,whereas the low-complexity scheme can be used in scenarios with a large number of nodes.

Key words: Load balance, Node access, RF energy harvesting, Throughput, Wireless sensor networks

CLC Number: 

  • TN911.2
[1]OZEL,TUTUNCUOGLU K,YANG J.Transmission with Ene-rgy Harvesting Nodes in Fading Wireless Channels:Optimal Policies[J].IEEE Journal on Selected Areas in Communications,2011,29(8):1732-1743.
[2]LU X,WANG P,NIYATO D,et al.Wireless Networks WithRF Energy Harvesting:A Contemporary Survey[J].IEEE Communications Surveys & Tutorials,2015,17(2):757-789.
[3]ZUNGERU A M,ANG L M,PRABAHARAN S,et al.Radio Frequency Energy Harvesting and Management for Wireless Sensor Networks[M].Green mobile devices and networks:Ene-rgy optimization and scavenging techniques,Boca Raton:CRC Press,2012:341-368.
[4]NISHIMOTO H,KAWAHARA Y,ASAMI T.Prototype im-plementation of ambient RF energy harvesting wireless sensor networks[J].IEEE Sensors,2010,143(2):1282-1287.
[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]FU L,CHENG P,GU Y,et al.Minimizing charging delay inwireless rechargeable sensor networks[C]∥IEEE Conference on Computer Communications (INFOCOM).IEEE,2013:2922-2930.
[7]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.
[8]BI S,ZHANG R.Placement Optimization of Energy and Information Access Points in Wireless Powered Communication Networks[J].IEEE Transactions on Wireless Communications,2015,15(3):2351-2364.
[9]JU H,ZHANG R.Throughput Maximization in Wireless Po-wered Communication Networks[J].IEEE Transactions on Wireless Communications,2014,13(1):418-428.
[1] ZHANG Fan, GONG Ao-yu, DENG Lei, LIU Fang, LIN Yan, ZHANG Yi-jin. Wireless Downlink Scheduling with Deadline Constraint for Realistic Channel Observation Environment [J]. Computer Science, 2021, 48(9): 264-270.
[2] WANG Guo-wu, CHEN Yuan-yan. Improvement of DV-Hop Location Algorithm Based on Hop Correction and Genetic Simulated Annealing Algorithm [J]. Computer Science, 2021, 48(6A): 313-316.
[3] WANG Guo-peng, YANG Jian-xin, YIN Fei, JIANG Sheng-jian. Computing Resources Allocation with Load Balance in Modern Processor [J]. Computer Science, 2020, 47(8): 41-48.
[4] JIN Qi, WANG Jun-chang, FU Xiong. Cuckoo Hash Table Based on Smart Placement Strategy [J]. Computer Science, 2020, 47(8): 80-86.
[5] SU Fan-jun,DU Ke-yi. Trust Based Energy Efficient Opportunistic Routing Algorithm in Wireless Sensor Networks [J]. Computer Science, 2020, 47(2): 300-305.
[6] SONG Ying, ZHONG Xian, SUN Bao-lin, GUI Chao. Sliding Window-based Network Coding Cooperative Algorithm in MANET [J]. Computer Science, 2020, 47(11): 322-326.
[7] HOU Ming-xing,QI Hui,HUANG Bin-ke. Data Abnormality Processing in Wireless Sensor Networks Based on Distributed Compressed Sensing [J]. Computer Science, 2020, 47(1): 276-280.
[8] LIU Jing, LAI Ying-xu, YANG Sheng-zhi, Lina XU. Bilateral Authentication Protocol for WSN and Certification by Strand Space Model [J]. Computer Science, 2019, 46(9): 169-175.
[9] JI Bao-feng, WANG Yi-dan, XING Bing-bing, LI Yu-qi, GAO Hong-feng, HAN Cong-cheng. Enhancement Method of Throughput in Ultra-dense Network Based on Hierarchical Multi-hop Physical Layer Network Coding [J]. Computer Science, 2019, 46(7): 56-60.
[10] LIANG Ping-yuan, LI Jie, PENG Jiao, WANG Hui. Research on 3D Dynamic Clustering Routing Algorithm Based on Cooperative MIMO for UWSN [J]. Computer Science, 2019, 46(6A): 336-342.
[11] ZHOU Wei-xing, SHI Hai-he. Survey on Sequence Assembly Algorithms in High-throughput Sequencing [J]. Computer Science, 2019, 46(5): 36-43.
[12] LI Xiu-qin, WANG Tian-jing, BAI Guang-wei, SHEN Hang. Two-phase Multi-target Localization Algorithm Based on Compressed Sensing [J]. Computer Science, 2019, 46(5): 50-56.
[13] YANG Ying, YANG Wu-de, WU Hua-rui, MIAO Yi-sheng. Mobile Sink Based Data Collection Strategy for Farmland WSN [J]. Computer Science, 2019, 46(4): 106-111.
[14] WU Jian, SUN Bao-ming. Dictionary Refinement-based Localization Method Using Compressive Sensing inWireless Sensor Networks [J]. Computer Science, 2019, 46(4): 118-122.
[15] JIANG Rui, WU Qian, XU You-yun. 3D Node Localization Algorithm Based on Iterative Computation for Wireless Sensor Network [J]. Computer Science, 2019, 46(11): 65-71.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!