Abstract
Nodes of wireless sensor networks due to environmental influences and deliberate attacks by nodes in the network, nodes of wireless sensor network are prone to death. In this paper, based on the idea of algorithm fusion, this paper proposes a research method for survivability of wireless sensor networks based on tenacity. A hybrid algorithm based on simulated annealing algorithm and particle swarm optimization algorithm is used to calculate the value of the tenacity of the network node. The optimized algorithm reduces the time and complexity of calculating tenacity. In this paper, the wireless sensor network is simulated and verified. The experimental results demonstrate the feasibility of evaluating the survivability of wireless sensor networks. The proposed method can effectively improve network lifetime and data transmission capability.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Akyildiz IF, Weilian Su, Sankarasubramaniam Y et al (2002) A survey on sensor networks. IEEE Commun Mag 40(8):102–114
Albert R, Jeong H, Barabási A (2012) Error and attack tolerance of complex networks. In: Proc, Conf. Elsevier BV, 200
Chao Yang, Jianfeng Ma (2004) Formal definition of survivable network system. Electron Technol 4:1–4
Chao Wang, Jianfeng Ma, Jianming Zhu (2006) A review of the survivability of network systems. Netw Security Technol Appl 6:15–17
Choudum SA, Priya N (1999) Tenacity of complete graph products and grids. Networks 34(3):192–196
Deng LH, Lei L et al (2018) Survivability evaluation of wireless sensor networks. Comput Appl Res 35(8):2450–2453
De S, Qiao C, Wu H (2003) Meshed multipath routing: an efficient strategy in sensor networks. Proc Conf Wireless Commun Netw 3:1912–1917
Ellison RJ, Fisher BD, Linge R et al (1997) Survivable network systems technical report CMU/SEI-97-TR-01. Institute Cacnegie Mellon University
Hailong H (2015) Research on improved algorithm of WSN clustering routing based on particle swarm optimization. Unpublished master’s dissertation, Taiyuan University of Technology
Jia S, Gao Y (2009) Hybrid partical swarm optimization algorithm merging simulated annealing and chaos. Comput Eng Appl 45(7):52–55
Limin S, Jianzhong L, Chen Y, Hongsong Z (2005) Wireless sensor network. Tsinghua University Press, Beijing
Mahmood MA, Seah WKG, Welch I (2015) Reliability in wireless sensor networks: a survey and challenges ahead. Comput Netw 79(3):166–187
Moussi R, Euchi J, Yassine A et al (2015) A hybrid ant colony and simulated annealing algorithm to solve the container stacking problem at seaport terminal. Int J Oper Res 24(4):399–422
Neumann PG, Hollway A, Bnames A (1993) Srvivable computer-communication systems: the problem and working group commendations. Technical Report US Army Research Labora sands Missile Rang
Pan Q, Wang W, Zhu J (2006) Effective hybrid heuristics based on partical swarm optimization and simulated annealing algorithm for job shop scheduling. China Mech Eng 17(10):1004–1008
Pin C, Min W (2017) A virtual force-oriented genetic algorithm for wireless sensor network optimization deployment strategy. Electron Des Eng 25(7):87–91
Tan YJ, Jun WU, Deng HZ et al (2006) Invulnerability of complex networks: a survey. Syst Eng 24(11):1–5
Venkatesan L, Shanmugavel S, Subramaniam C (2013) A survey on modeling and enhancing reliability of wireless sensor network. Wireless Sens Netw 05(3):41–51
Yang C, Chin KW (2016) On complete targets coverage and connectivity in energy harvesting wireless sensor networks. Proc, Conf. international conference on telecommunications, pp 391–397
Younis O, Fahmy S (2004) Robust communications for sensor networks in hostile environments. Qual Service IWQOS 10–19
Zhiping W, Cairong L, Guang R et al (2001) The structure of toughness and network graph. J Liaoning Univ (Nat Sci Edn) 28(3):206–210
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Fund project: Funded by the National Natural Science Foundation of China (61171196) and the Harbin Science and Technology Innovation Talent Project (2017RALXJ007).
Rights and permissions
About this article
Cite this article
Yu, J., Yu, Z., Ding, M. et al. Research on the tenacity survivability of wireless sensor networks. J Ambient Intell Human Comput 11, 3535–3544 (2020). https://doi.org/10.1007/s12652-019-01491-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-019-01491-z