Abstract
To address problems of fault-tolerant routing recovery and routings’ quality maintenance in energy harvesting wireless sensor networks (EH-WSNs), we proposed an improved immune system-inspired routing recovery algorithm (ISRRA) to provide an intelligent scheme for EH-WSNs. The ISRRA could maintain k best disjoint path from each source node to the sink. It investigates the optimal alternative strategies for the faulty routing and recovers the problems with four units (the surveillance unit, the response unit, the learn unit and the memory unit) as imitating the immune system, especially for the same fault routing happened again. Moreover, during the routing recovery process, ISRRA also check other candidate routings to decide whether to update the backup routings, which is used to maintain routings’ quality and also greatly improve the fault-tolerant ability of EH-WSNs. In order to overcome the limited diversity of antibody population and prematurity of clone selection algorithm used in the learn unit, an improved clone and mutation scheme inspired by the regulation laws of hormone in endocrine system is proposed in ISRRA. Finally, to verify the effectiveness of the proposed ISRRA, a series of simulation experiments are conducted and compared with two other routing recovery schemes. The simulation results have verified that the ISRRA-based protocol can provide reliable communication with effective routing recovery scheme and highlight the better performance of the proposed approach than that of similar techniques.
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References
Abbasi AA, Younis MF, Baroudi UA (2013) Recovering from a node failure in wireless sensor–actor networks with minimal topology changes. IEEE Trans Veh Technol 62(1):256–271
Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) A survey on sensor networks. IEEE Commun Mag 40(8):102–114
Al-Azzawi W, Al-Akaidi M (2015) Robust stability of solar-power wireless network control system with stochastic time delays based on H\(\infty \)-norm. Int J Syst Sci 46(5):896–907
Bagci H, Korpeoglu I, YAZICI A (2015) A Distributed Fault-Tolerant Topology Control Algorithm for Heterogeneous Wireless Sensor Networks. IEEE Trans Parallel Distrib Syst 26(4):914–923
Cardei M, Yang S, Wu J (2008) Algorithms for fault-tolerant topology in heterogeneous wireless sensor networks. IEEE Trans Parallel Distrib Syst 19(4):545–558
Cheetham W, Watson I (2005) Fielded applications of case-based reasoning. Knowl Eng Rev 20(3):321–323
Dasgupta D (2006) Advances in artificial immune systems. IEEE Comput Intell Mag 1(4):40–49
Dasgupta D, Yu S, Nino F (2011) Recent advances in artificial immune systems: models and applications. Appl Soft Comput 11(2):1574–1587
Ding Y, Gao L (2011) Macrodynamics analysis of migration behaviors in large-scale mobile agent systems for the future Internet. IEEE Trans Syst Man Cybern Part A Syst Hum 41(5):1032–1036
Ding YS, Lu XJ, Hao KR et al (2011) Target coverage optimisation of wireless sensor networks using a multi-objective immune co-evolutionary algorithm. Int J Syst Sci 42(9):1531–1541
Ding S, Li H, Su C et al (2013) Evolutionary artificial neural networks: a review. Artif Intell Rev 39(3):251–260
Ding Y, Xu N, Ren L et al (2015) Data-driven neuroendocrine ultrashort feedback-based cooperative control system. IEEE Trans Control Syst Technol 23(3):1205–1212
Farhy LS (2004) Modeling of oscillations in endocrine networks with feedback. Methods Enzymol 384:54–81
Gao L, Ding Y, Ren L (2004) A novel ecological network-based computation platform as a grid middleware system. Int J Intell Syst 19(10):859–884
Gao L, Ding Y, Ying H (2006) An adaptive social network-inspired approach to resource discovery for the complex grid systems. Int J Gen Syst 35(3):347–360
Han X, Cao X, Lloyd EL et al (2010) Fault-tolerant relay node placement in heterogeneous wireless sensor networks. IEEE Trans Mob Comput 9(5):643–656
Hu YF, Ding YS, Hao KR (2012) An immune cooperative particle swarm optimization algorithm for fault-tolerant routing optimization in heterogeneous wireless sensor networks. Math Probl Eng 2012:743728. doi:10.1155/2012/743728
Hu Y, Ding Y, Hao K et al (2014) An immune orthogonal learning particle swarm optimisation algorithm for routing recovery of wireless sensor networks with mobile sink. Int J Syst Sci 45(3):337–350
Hu YF, Ding YS, Ren LH et al (2015) An endocrine cooperative particle swarm optimization algorithm for routing recovery problem of wireless sensor networks with multiple mobile sinks. Inf Sci 300:100–113
Lee JH, Jung IB (2010) Speedy routing recovery protocol for large failure tolerance in wireless sensor networks. Sensors 10(4):3389–3410
Liang X, Ding Y, Ren L et al (2014) Data-driven cooperative intelligent controller based on the endocrine regulation mechanism. IEEE Trans Control Syst Technol 22(1):94–101
Liu F, Wang L, Gao L et al (2014) A Web Service trust evaluation model based on small-world networks. Knowl Based Syst 57:161–167
Munir A, Antoon J, Gordon-Ross A (2015) Modeling and analysis of fault detection and fault tolerance in wireless sensor networks. ACM Trans Embed Comput Syst (TECS) 14(1):3
Ould-Ahmed-Vall E, Ferri BH, Riley GF (2012) Distributed fault-tolerance for event detection using heterogeneous wireless sensor networks. IEEE Trans Mob Comput 11(12):1994–2007
Pantazis NA, Nikolidakis SA, Vergados DD (2013) Energy-efficient routing protocols in wireless sensor networks: a survey. IEEE Commun Surv Tutor 15(2):551–591
Paradis L, Han Q (2007) A survey of fault management in wireless sensor networks. J Netw Syst Manag 15(2):171–190
Rault T, Bouabdallah A, Challal Y (2014) Energy efficiency in wireless sensor networks: a top-down survey. Comput Netw 67:104–122
Rawat P, Singh KD, Chaouchi H et al (2014) Wireless sensor networks: a survey on recent developments and potential synergies. J Supercomput 68(1):1–48
Shih HC, Ho JH, Liao BY et al (2013) Fault node recovery algorithm for a wireless sensor network. IEEE Sens J 13(7):2683–2689
Sitanayah L, Brown KN, Sreenan CJ (2014) A fault-tolerant relay placement algorithm for ensuring k vertex-disjoint shortest paths in wireless sensor networks. Ad Hoc Netw 23:145–162
Srivastava JR, Sudarshan TSB (2015) Energy-efficient cache node placement using genetic algorithm in wireless sensor networks. Soft Comput 19(11):3145–3158
Sudevalayam S, Kulkarni P (2011) Energy harvesting sensor nodes: survey and implications. IEEE Commun Surv Tutor 13(3):443–461
The National Solar Radiation Data Base. http://rredc.nrel.gov/solar/old_data/nsrdb/1991-2010/
Wang Y, Cao L, Dahlberg TA et al (2009) Self-organizing fault-tolerant topology control in large-scale three-dimensional wireless networks. ACM Trans Auton Adapt Syst 4(3):19–40
Watson I, Perera S (1997) Case-based design: a review and analysis of building design applications. Artif Intell Eng Des Anal Manuf 11(1):59–87
Xu N, Ding YS, Hao KR (2014) Immunological mechanism inspired iterative learning control. Neurocomputing 145:392–401
Yao G, Ding Y, Ren L et al (2016) An immune system-inspired rescheduling algorithm for workflow in Cloud systems. Knowl Based Syst 99:39–50
Yao Y, Giannakis GB (2005) Energy-efficient scheduling for wireless sensor networks. IEEE Trans Commun 53(8):1333–1342
Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Comput Netw 52(12):2292–2330
Yu M, Mokhtar H, Merabti M (2007) Fault management in wireless sensor networks. IEEE Wirel Commun 14(6):13–19
Zhang Z, Qian S (2011) Artificial immune system in dynamic environments solving time-varying non-linear constrained multi-objective problems. Soft Comput 15(7):1333–1349
Zuo X, Tan W, Lin H (2014) Cigarette production scheduling by combining workflow model and immune algorithm. IEEE Trans Autom Sci Eng 11(1):251–264
Acknowledgments
This work was supported in part by the Key Project of the National Nature Science Foundation of China (No. 61134009), the National Nature Science Foundation of China (Nos. 61473077, 61473078), Cooperative research funds of the National Natural Science Funds Overseas and Hong Kong and Macao scholars (No. 61428302), Program for Changjiang Scholars from the Ministry of Education, Specialized Research Fund for Shanghai Leading Talents, Project of the Shanghai Committee of Science and Technology (No. 13JC1407500), and Innovation Program of Shanghai Municipal Education Commission (No. 14ZZ067).
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Communicated by Y. Jin.
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Zhang, X., Yao, G., Ding, Y. et al. An improved immune system-inspired routing recovery scheme for energy harvesting wireless sensor networks. Soft Comput 21, 5893–5904 (2017). https://doi.org/10.1007/s00500-016-2222-y
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DOI: https://doi.org/10.1007/s00500-016-2222-y