Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Wireless Networks
Published in: Wireless Networks 7/2022

08-07-2022 | Original Paper

A cluster based charging schedule for wireless rechargeable sensor networks using gravitational search algorithm

Authors: Sk Md Abidar Rahaman, Md Azharuddin

Published in: Wireless Networks | Issue 7/2022

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Wireless sensor networks have a short network lifetime due to limited battery life. External power supplies are utilised to extend the life of sensor nodes. The previous works of charging scheduling lack charging efficiency, resulting in early node energy exhaustion. There are certain limitations in designing the scheduling path when sensor nodes consume diversified energy. Previous charging schedule approaches or charging path designs aimed to reduce the mobile charger’s travel distance as well as the charging time delay. In this paper, we show how to build a charging path that reduces not only the mobile charger’s maximum working time, but also the charging time delay or charging latency, as well as the mobile charger’s or Mobile Charging Vehicle’s (MCV) travel distance . Here first we cluster the sensor nodes based on their location, then we derive a path using Gravitational Search Algorithm inside the clusters. We stimulate the proposed work and compare the working time of the MCV with some existing algorithms to show the efficiency.
previous article Resource management in UAV-assisted MEC: state-of-the-art and open challenges

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
Kurs, Andre, Karalis, Aristeidis, Moffatt, Robert, Joannopoulos, John D., Fisher, Peter, & Soljačić, Marin. (2007). Wireless power transfer via strongly coupled magnetic resonances. science, 317(5834), 83–86.MathSciNetCrossRef
2.
Romer, Kay, & Mattern, Friedemann. (2004). The design space of wireless sensor networks. IEEE wireless communications, 11(6), 54–61.CrossRef
3.
Dehwah, Ahmad H., Elmetennani, Shahrazed, & Claudel, Christian. (2017). Ud-wcma: An energy estimation and forecast scheme for solar powered wireless sensor networks. Journal of Network and Computer Applications, 90, 17–25.CrossRef
4.
Dondi, Denis, Bertacchini, Alessandro, Brunelli, Davide, Larcher, Luca, & Benini, Luca. (2008). Modeling and optimization of a solar energy harvester system for self-powered wireless sensor networks. IEEE Transactions on industrial electronics, 55(7), 2759–2766.CrossRef
5.
Cammarano, Alessandro, Petrioli, Chiara, & Spenza, Dora (2012). Pro-energy: A novel energy prediction model for solar and wind energy-harvesting wireless sensor networks. In 2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2012), pp 75–83. IEEE.
6.
Kansal, Aman, Hsu, Jason, Zahedi, Sadaf, & Srivastava, Mani B. (2007). Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems (TECS), 6(4), 32–es.
7.
Liu, Ren-Shiou, Sinha, Prasun, & Koksal, Can Emre. (2010). Joint energy management and resource allocation in rechargeable sensor networks. In 2010 Proceedings IEEE INFOCOM, pp 1–9. IEEE.
8.
Sansoy, Meenakshi, Buttar, Avtar Singh, & Goyal, Rakesh. (2020). Design and implementation of solar energy harvesting with double booster circuit in wireless sensor networks. In 2020 7th International Conference on Signal Processing and Integrated Networks (SPIN), pp 414–416. IEEE.
9.
Xie, Liguang, Shi, Yi., Thomas Hou, Y., & Sherali, Hanif D. (2012). Making sensor networks immortal: An energy-renewal approach with wireless power transfer. IEEE/ACM Transactions on networking, 20(6), 1748–1761.CrossRef
10.
Xie, Liguang., Shi, Yi., Thomas Hou, Y., Lou, Wenjing., Sherali, Hanif D., & Midkiff, Scott F. (2013). Bundling mobile base station and wireless energy transfer: Modeling and optimization. In 2013 Proceedings IEEE INFOCOM, pp 1636–1644. IEEE.
11.
Nitesh, Kumar, Azharuddin, Md., & Jana, Prasanta K. (2018). A novel approach for designing delay efficient path for mobile sink in wireless sensor networks. Wireless Networks, 24(7), 2337–2356.CrossRef
12.
He, Liang, Fu, Lingkun, Zheng, Likun, Gu, Yu., Cheng, Peng, Chen, Jiming, & Pan, Jianping. (2014). Esync: An energy synchronized charging protocol for rechargeable wireless sensor networks. In Proceedings of the 15th ACM international symposium on Mobile ad hoc networking and computing, pp 247–256.
13.
Menglan, Hu., Chen, Ziyi, Peng, Kai, Ma, Xiaoqiang, Zhou, Pan, & Liu, Jiangchuan. (2018). Periodic charging for wireless sensor networks with multiple portable chargers. IEEE Access, 7, 2612–2623.
14.
Liang, Weifa, Wenzheng, Xu., Ren, Xiaojiang, Jia, Xiaohua, & Lin, Xiaola. (2016). Maintaining large-scale rechargeable sensor networks perpetually via multiple mobile charging vehicles. ACM Transactions on Sensor Networks (TOSN), 12(2), 1–26.CrossRef
15.
Liang, Weifa, Xu, Zichuan, Xu, Wenzheng, Shi, Jiugen, Mao, Guoqiang, & Das, Sajal K. (2017). Approximation algorithms for charging reward maximization in rechargeable sensor networks via a mobile charger. IEEE/ACM Transactions on Networking, 25(5), 3161–3174.CrossRef
16.
Zheng, Huanyang, & Wu, Jie. (2017). Cooperative wireless charging vehicle scheduling. In 2017 IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), pp 224–232. IEEE.
17.
Rashedi, Esmat, Nezamabadi-Pour, Hossein, & Saryazdi, Saeid. (2009). Gsa: a gravitational search algorithm. Information sciences, 179(13), 2232–2248.CrossRef
18.
Azharuddin, Md., & Jana, Prasanta K. (2015). A distributed algorithm for energy efficient and fault tolerant routing in wireless sensor networks. Wireless Networks, 21(1), 251–267.CrossRef
19.
Liu, Tang., Wu, Baijun, Zhang, Shihao, Peng, Jian, & Xu, Wenzheng. (2020). An effective multi-node charging scheme for wireless rechargeable sensor networks. In IEEE INFOCOM 2020-IEEE Conference on Computer Communications, pp 2026–2035. IEEE.
20.
Tong, Bin., Li, Zi., Wang, Guiling, & Zhang, Wensheng. (2010). How wireless power charging technology affects sensor network deployment and routing. In 2010 IEEE 30th International Conference on Distributed Computing Systems, pp 438–447. IEEE.
21.
Xie, Liguang, Shi, Yi., Thomas Hou, Y., Lou, Wenjing, Sherali, Hanif D., & Midkiff, Scott F. (2012). On renewable sensor networks with wireless energy transfer: The multi-node case. In 2012 9th annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks (SECON), pp 10–18. IEEE.
22.
Li, Zi., Peng, Yang, Zhang, Wensheng, & Qiao, Daji. (2011). J-roc: A joint routing and charging scheme to prolong sensor network lifetime. In 2011 19th IEEE International Conference on Network Protocols, pp 373–382. IEEE.
23.
Li, Ke., Luan, Hao., & Shen, Chien-Chung. (2012). Qi-ferry: Energy-constrained wireless charging in wireless sensor networks. In 2012 IEEE Wireless Communications and Networking Conference (WCNC), pp 2515–2520. IEEE.
24.
Dai, Haipeng, Xu, Lijie, Wu, Xiaobing, Dong, Chao., & Chen, Guihai. (2013). Impact of mobility on energy provisioning in wireless rechargeable sensor networks. In 2013 IEEE Wireless Communications and Networking Conference (WCNC), pp 962–967. IEEE.
25.
He, Liang, Linghe Kong, YuGu., Pan, Jianping, & Zhu, Ting. (2014). Evaluating the on-demand mobile charging in wireless sensor networks. IEEE Transactions on Mobile Computing, 14(9), 1861–1875.CrossRef
26.
Liang, Weifa., Xu, Wenzheng., Ren, Xiaojiang, Jia, Xiaohua., & Lin, Xiaola, (2014). Maintaining sensor networks perpetually via wireless recharging mobile vehicles. In 39th Annual IEEE Conference on Local Computer Networks, pp 270–278. IEEE.
27.
Ren, Xiaojiang., Liang, Weifa., & Xu, Wenzheng. (2014). Maximizing charging throughput in rechargeable sensor networks. In 2014 23rd International Conference on Computer Communication and Networks (ICCCN), pp 1–8. IEEE.
28.
Madhja, Adelina., Nikoletseas, Sotiris, & Raptis, Theofanis P. (2013). Efficient, distributed coordination of multiple mobile chargers in sensor networks. In Proceedings of the 16th ACM international conference on Modeling, analysis & simulation of wireless and mobile systems, pp 101–108.
29.
Anwit, Raj, Tomar, Abhinav, & Jana, Prasanta K. (2020). Tour planning for multiple mobile sinks in wireless sensor networks: A shark smell optimization approach. Applied Soft Computing, 97, 106802.CrossRef
30.
Dai, Haipeng, Wu, Xiaobing, Xu, Lijie, Chen, Guihai, & Lin, Shan. (2013). Using minimum mobile chargers to keep large-scale wireless rechargeable sensor networks running forever. In 2013 22nd International Conference on Computer Communication and Networks (ICCCN), pp 1–7. IEEE.
31.
Fu, Lingkun, Cheng, Peng, Gu, Yu., Chen, Jiming., & He, Tian. (2013). Minimizing charging delay in wireless rechargeable sensor networks. In 2013 Proceedings IEEE INFOCOM, pp 2922–2930. IEEE.
32.
Lin, Shen, & Kernighan, Brian W. (1973). An effective heuristic algorithm for the traveling-salesman problem. Operations research, 21(2), 498–516.MathSciNetCrossRef
33.
Kumar, Naween, Dash, Dinesh, & Kumar, Mukesh. (2021). An efficient on-demand charging schedule method in rechargeable sensor networks. Journal of Ambient Intelligence and Humanized Computing, 12(7), 8041–8058.CrossRef
34.
Wang, Cong., Li, Ji., Ye, Fan, & Yang, Yuanyuan. (2013). Multi-vehicle coordination for wireless energy replenishment in sensor networks. In 2013 IEEE 27th International Symposium on Parallel and Distributed Processing, pp 1101–1111. IEEE.
35.
Wang, Qian, Cui, Zhihua, & Wang, Lifang. (2021). Charging path optimization for wireless rechargeable sensor network. Peer-to-Peer Networking and Applications, 14(2), 497–506.CrossRef
36.
Zhao, Chuanxin, Zhang, Hengjing, Chen, Fulong, Chen, Siguang, Changzhi, Wu., & Wang, Taochun. (2020). Spatiotemporal charging scheduling in wireless rechargeable sensor networks. Computer Communications, 152, 155–170.CrossRef
37.
Cao, Xianbo, Wenzheng, Xu., Liu, Xuxun, Peng, Jian, & Liu, Tang. (2021). A deep reinforcement learning-based on-demand charging algorithm for wireless rechargeable sensor networks. Ad Hoc Networks, 110, 102278.CrossRef
38.
He, Shibo, Chen, Jiming, Jiang, Fachang, Yau, David KY., Xing, Guoliang, & Sun, Youxian. (2012). Energy provisioning in wireless rechargeable sensor networks. IEEE transactions on mobile computing, 12(10), 1931–1942.CrossRef
39.
Baronti, Paolo, Pillai, Prashant, Chook, Vince WC., Chessa, Stefano, Gotta, Alberto, & Hu, Y Fun. (2007). Wireless sensor networks: A survey on the state of the art and the 802.15. 4 and zigbee standards. Computer communications, 30(7), 1655–1695.CrossRef
Metadata
Title
A cluster based charging schedule for wireless rechargeable sensor networks using gravitational search algorithm
Authors
Sk Md Abidar Rahaman
Md Azharuddin
Publication date
08-07-2022
Publisher
Springer US
Published in
Wireless Networks / Issue 7/2022
Print ISSN: 1022-0038
Electronic ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-022-03049-y

Other articles of this Issue 7/2022

Wireless Networks 7/2022 Go to the issue

Original Paper

Secure transmission in one-bit cell-free massive MIMO system with multiple non-colluding eavesdroppers

Original Paper

Analysis on functionalities and security features of Internet of Things related protocols

Original Paper

Resource management in UAV-assisted MEC: state-of-the-art and open challenges

Original Paper

Finding an appropriate radio propagation model for rate aware congestion control mechanism in wireless sensor networks

Original Paper

A state-of-the-art survey on wireless rechargeable sensor networks: perspectives and challenges

Original Paper

DDPG-based intelligent rechargeable fog computation offloading for IoT