Skip to main content

Advertisement

SpringerLink
Log in

An immune clone selection based power control strategy for alleviating energy hole problems in wireless sensor networks

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

In wireless sensor networks (WSNs), the creation of energy holes is extremely difficult to be avoided because the data flow usually follows a many-to-one and multi-hop pattern. Since energy holes exhaust their energy faster than other nodes, network partitions might be created, which might lead to failure of the network. Cluster-based WSNs have been widely used because of their good performance, and power control strategies are an effective way to improve energy efficiency in WSNs. In this paper, we first propose a power-based energy consumption model and a cluster-based coronal model for analyzing the energy hole problem in WSNs. Then, on the basis of the proposed models, we investigate the feasibility and effectiveness of the existing approaches for solving the energy hole problem in WSNs. Furthermore, an immune clone selection-based power control (ICSPC) strategy for alleviating the energy hole problem in WSNs is proposed. In the ICSPC strategy, the immune clone selection algorithm is used to optimize the transmission ranges of sensors in various coronas to balance the energy consumption rates of the coronas. Finally, simulation results are analyzed to show that the energy hole problem in WSNs has been largely alleviated by the ICSPC strategy, and the network lifetime is greatly prolonged.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • Ammari HM, Das SK (2008) Promoting heterogeneity, mobility, and energy-aware voronoi diagram in wireless sensor networks. IEEE Trans Parallel Distrib Syst 19(7):995–1008

    Article  Google Scholar 

  • Asharioun H, Asadollahi H, Wan TC, Gharaei N (2015) A survey on analytical modeling and mitigation techniques for the energy hole problem in corona-based wireless sensor network. Wirel Pers Commun 81(1):161–187

    Article  Google Scholar 

  • Azad AKM, Kamruzzaman J (2011) Energy-balanced transmission policies for wireless sensor networks. IEEE Trans Mob Comput 10(7):927–940

    Article  Google Scholar 

  • Bandyopadhyay S, Coyle EJ (2004) Minimizing communication costs in hierarchically-clustered networks of wireless sensors. Comput Netw 44(1):1–16

    Article  Google Scholar 

  • Bi Y, Sun L, Ma J, Li N, Khan IA, Chen C (2007) HUMS: an autonomous moving strategy for mobile sinks in data-gathering sensor networks. EURASIP J Wirel Commun Netw 2007(1):1–15

    Article  Google Scholar 

  • Brazil MN, Ras CJ, Thomas DA (2013) Relay augmentation for lifetime extension of wireless sensor networks. IET Wirel Sens Syst 3(2):145–152

    Article  Google Scholar 

  • Çam H, Özdemir S, Nair P, Muthuavinashiappan D, Sanli HO (2006) Energy-efficient secure pattern based data aggregation for wireless sensor networks. Comput Commun 29(4):446–455

    Article  Google Scholar 

  • Chen Y, Li Q, Fei L, Gao Q (2012) Mitigating energy holes in wireless sensor networks using cooperative communication. In: 2012 IEEE 23rd international symposium on personal, indoor and mobile radio communications, Sydney, NSW, Australia, 9–12 September 2012, pp 857–862

  • Esseghir M, Bouabdallah N, Pujolle G (2007) Energy provisioning model for maximizing wireless sensor network lifetime. In: 2007 First international global information infrastructure symposium, Marrakech, Morocco, 2–6 July 2007, pp 80–84

  • Fei L, Chen Y, Gao Q, Peng XH, Li Q (2015) Energy hole mitigation through cooperative transmission in wireless sensor networks. Int J Distrib Sens Netw 11(2):1–14

    Article  Google Scholar 

  • Ferng HW, Hadiputro MS, Kurniawan A (2010) Design of novel node distribution strategies in corona-based wireless sensor networks. IEEE Trans Mob Comput 10(9):1297–1311

    Article  Google Scholar 

  • Halder S, Ghosal A, Bit SD (2011) A pre-determined node deployment strategy to prolong network lifetime in wireless sensor network. Comput Commun 34(11):1294–1306

    Article  Google Scholar 

  • Heinzelman WB, Chandrakasan AP, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 1(4):660–670

    Article  Google Scholar 

  • Hou YT, Shi Y, Sherali HD, Midkiff SF (2005) On energy provisioning and relay node placement for wireless sensor networks. IEEE Trans Wirel Commun 4(5):2579–2590

    Article  Google Scholar 

  • Jan N, Javaid N, Javaid Q, Alrajeh N, Alam M, Khan ZA, Niaz IA (2017) A balanced energy-consuming and hole-alleviating algorithm for wireless sensor networks. IEEE Access 5:6134–6150

    Article  Google Scholar 

  • Khan A, Ahmedy I, Anisi MH, Javaid N, Ali I, Khan N, Alsaqer M, Mahmood H (2018) A localization-free interference and energy holes minimization routing for underwater wireless sensor networks. Sensors 18(1):1–17

    Article  Google Scholar 

  • Li J, Mohapatra P (2005) An analytical model for the energy hole problem in many-to-one sensor networks. In: 2005 IEEE 62nd vehicular technology conference, Dallas, TX, USA, 28 September 2005, pp 2721–2725

  • Li J, Mohapatra P (2007) Analytical modeling and mitigation techniques for the energy hole problem in sensor networks. Pervasive Mob Comput 3(3):233–254

    Article  Google Scholar 

  • Lian J, Chen L, Naik K, Agnew GB (2004) Modeling and enhancing the data capacity of wireless sensor networks. IEEE Monogr Sens Netw Oper 2:91–138

    Google Scholar 

  • Lian J, Naik K, Agnew GB (2006) Data capacity improvement of wireless sensor networks using non-uniform sensor distribution. Int J Distrib Sens Netw 2(2):121–145

    Article  Google Scholar 

  • Liu T (2013) Avoiding energy holes to maximize network lifetime in gradient sinking sensor networks. Wirel Pers Commun 70(2):581–600

    Article  Google Scholar 

  • Liu X (2016) A novel transmission range adjustment strategy for energy hole avoiding in wireless sensor networks. J Netw Comput Appl 67:43–52

    Article  Google Scholar 

  • Liu Y, Ngan H, Ni LM (2006) Power-aware node deployment in wireless sensor networks. Int J Distrib Sens Netw 3(2):225–241

    Article  Google Scholar 

  • Liu J, Lu K, Cai X, Murthi MN (2009) Regenerative cooperative diversity with path selection and equal power consumption in wireless networks. IEEE Trans Wirel Commun 8(8):3926–3932

    Article  Google Scholar 

  • Marta M, Cardei M (2008) Using sink mobility to increase wireless sensor networks lifetime. In: 2008 International symposium on a world of wireless, mobile and multimedia networks, Newport Beach, CA, USA, 23–26 June 2008, pp 1–10

  • Mohemed RE, Saleh AI, Abdelrazzak M, Samra AS (2017) Energy-efficient routing protocols for solving energy hole problem in wireless sensor networks. Comput Netw 114:51–66

    Article  Google Scholar 

  • Morteza S, Mortaza A (2018) Proposing a method to solve energy hole problem in wireless sensor networks. Alex Eng J 57(3):1585–1590

    Article  Google Scholar 

  • Nguyen KV, Nguyen PL, Vu QH, Do TV (2017a) An energy efficient and load balanced distributed routing scheme for wireless sensor networks with holes. J Syst Softw 123(1):92–105

    Article  Google Scholar 

  • Nguyen PL, Ji Y, Liu Z, Vu H, Nguyen KV (2017b) Distributed hole-bypassing protocol in WSNs with constant stretch and load balancing. Comput Netw 129:232–250

    Article  Google Scholar 

  • Potdar V, Sharif A, Chang E (2002) Wireless sensor networks: a survey. Comput Netw 38(4):393–422

    Article  Google Scholar 

  • Prabha KL, Selvan S (2018) Energy efficient energy hole repelling (EEEHR) algorithm for delay tolerant wireless sensor network. Wirel Pers Commun 101(3):1395–1409

    Article  Google Scholar 

  • Rahman AU, Hasbullah H, Sama N (2012) Impact of Gaussian deployment strategies on the performance of wireless sensor network. In: International conference on computer & information science (ICCIS), Kuala Lumpur, Malaysia, 12–14 June 2012, pp 771–776

  • Ren J, Zhang Y, Zhang K, Liu A, Chen J, Shen XS (2016) Lifetime and energy hole evolution analysis in data-gathering wireless sensor networks. IEEE Trans Ind Inform 12(2):788–800

    Article  Google Scholar 

  • Song C, Liu M, Cao J, Zheng Y, Gong H, Chen G (2009) Maximizing network lifetime based on transmission range adjustment in wireless sensor networks. Comput Commun 32(11):1316–1325

    Article  Google Scholar 

  • Suganthi K, Sundaram VB (2012) A constraint based relay node deployment in heterogeneous wireless sensor networks for lifetime maximization. In: 2012 fourth international conference on advanced computing (ICoAC), Chennai, India, 13–15 December 2012, pp 1–6

  • Thanigaivelu K, Murugan K (2012) K-level based transmission range scheme to alleviate energy hole problem in WSN. In: Proceedings of the second international conference on computational science, engineering and information technology, Coimbatore UNK, India, 26–28 October 2012, pp 476–483

  • Wang Q, Xu K, Takahara G, Hassanein H (2006) On lifetime-oriented device provisioning in heterogeneous wireless sensor networks: approaches and challenges. IEEE Netw 20(3):26–33

    Article  Google Scholar 

  • Wang K, Shao Y, Shu L, Han G, Zhu C (2015) LDPA: a local data processing architecture in ambient assisted living communications. IEEE Commun Mag 53(1):56–63

    Article  Google Scholar 

  • Wang K, Gao H, Xu X, Jiang J, Yue D (2016a) An energy-efficient reliable data transmission scheme for complex environmental monitoring in underwater acoustic sensor networks. IEEE Sens J 16(11):4051–4062

    Article  Google Scholar 

  • Wang K, Shao Y, Shu L, Zhu C, Zhang Y (2016b) Mobile big data fault-tolerant processing for ehealth networks. IEEE Netw 30(1):36–42

    Article  Google Scholar 

  • Wang K, Wang Y, Sun Y, Guo S, Wu J (2016c) Green industrial internet of things architecture: an energy-efficient perspective. IEEE Commun Mag 54(12):48–54

    Article  Google Scholar 

  • Wang K, Gu L, He X, Guo S, Sun Y, Vinel A, Shen J (2017) Distributed energy management for vehicle-to-grid networks. IEEE Netw 31(2):22–28

    Article  Google Scholar 

  • Wu X, Chen G, Das SK (2006) On the energy hole problem of nonuniform node distribution in wireless sensor networks. In: 2006 IEEE international conference on mobile ad hoc and sensor systems, Vancouver, BC, Canada, 9–12 October 2006, pp 180–187

  • Wu X, Chen G, Das SK (2007) Avoiding energy holes in wireless sensor networks with nonuniform node distribution. IEEE Trans Parallel Distrib Syst 19(5):710–720

    Google Scholar 

  • Xia C, Guan N, Deng Q, Yi W (2014) Maximizing lifetime of three-dimensional corona-based wireless sensor networks. Int J Distrib Sens Netw 10(5):1–13

    Article  Google Scholar 

  • Xu K, Hassanein H, Takahara G, Wang Q (2010) Relay node deployment strategies in heterogeneous wireless sensor networks. IEEE Trans Mob Comput 9(2):145–159

    Article  Google Scholar 

  • Younis O, Fahmy S (2004) HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans Mob Comput 3(4):366–379

    Article  Google Scholar 

  • Zhang J, Ci S, Sharif H, Alahmad M (2009) A battery-aware deployment scheme for cooperative wireless sensor networks. In: 2009 IEEE global telecommunications conference, Honolulu, HI, USA, 30 November–4 December 2009, pp 1–5

Download references

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 61672299, in part by the Natural Science Foundation of Jiangsu Province of China under Grant BK20160913, in part by the China Postdoctoral Science Foundation funded project under Grant 2018M640509.

Author information

Authors and Affiliations

  1. Key Laboratory of Broadband Wireless Communication and Sensor Network Technology of the Ministry of Education, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China

    Xuejian Zhao, Zhe Sun, Xinhui Zhang & Zhixin Sun

  2. Research and Development Center of Postal Industry Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China

    Xuejian Zhao, Zhe Sun, Xinhui Zhang & Zhixin Sun

  3. School of Modern Posts, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China

    Xiaoxiao Xiong

Authors
  1. Xuejian Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoxiao Xiong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhe Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xinhui Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhixin Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xuejian Zhao.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, X., Xiong, X., Sun, Z. et al. An immune clone selection based power control strategy for alleviating energy hole problems in wireless sensor networks. J Ambient Intell Human Comput 11, 2505–2518 (2020). https://doi.org/10.1007/s12652-019-01300-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-019-01300-7

Keywords

Search

Navigation