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An algorithm on fairness verification of mobile sink routing in wireless sensor network

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Abstract

Congestion and starvation will occur among some nodes due to the emerging serious unfairness, which is derived from the limited communication capabilities of all nodes and sink or in the case of a mobile sink moving to a new place. The problem to be solved is to balance the network and keep the fairness for all nodes. For this purpose, this paper focuses on verifying the fairness of mobile sink routing based on both state and action, which is realized mainly by composing Labeled Kripke Transition Systems (LKTS). First, an approach is presented by LKTS to model node behaviors. Second, a notion of Fair Computational Tree Logic (CTL) is introduced to describe the fairness formulae in branching time transitions, and four kinds of fairness assumptions are defined for fairness verification. Moreover, in order to avoid the problem of state-space explosion, Bounded model Checking to explore states and transitions on-the-fly until a witness is found, while Strong Connected Components algorithm is used to pick up fair paths under fairness constraints of Fair CTL. The experimental results show the superiority of our method by the savings in memory and time consumptions during the mobile sink routing process.

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References

  1. Zhao X, Makki SK, Pissinou N (2007) Self-adaptable routing scheme for in-network processing. Int J Smart Home 1(1):40–48

    Google Scholar 

  2. Ye F, Luo H, Cheng J, Lu S, Zhang L (2002) A two-tier data dissemination model for large-scale wireless sensor networks. In: Proceedings of ACM/IEEE MOBICOM, MOBICOM’02

  3. Lee J, Hwang M, Park S, Jang H, Kim B (2007) A routing scheme of mobile sink in sensor networks, computational science and its applications—ICCSA 2007. Lecture notes in computer science 4706/2007, pp 751–763. doi:10.1007/978-3-540-74477-1_68

  4. Chang SH, Merabti M, Mokhtar HM (2007) Coordinate magnetic routing for mobile sinks wireless sensor networks. In: 21st international conference on advanced information networking and applications workshops (AINAW’07), vol 1, pp 846–851

  5. Wang G, Wang T, Jia W, Guo M, Chen HH, Guizani M (2007) Local update-based routing protocol in wireless sensor networks with mobile sinks. IEEE international conference on communications, ICC ‘07, pp 3094–3099

  6. Kim JW, In JS, Hur K, Kim JW, Eom DS (2010) An intelligent agent-based routing structure for mobile sinks in WSNs. IEEE Trans Consum Electron 56(4):1090–1097

    Google Scholar 

  7. Kumar D, Aseri TC, Patel RB (2011) Multi-hop communication routing (MCR) protocol for heterogeneous wireless sensor networks. IJITCC 1(2):130–145. doi:10.1504/IJITCC.2011.039281

    Article  Google Scholar 

  8. Misra S, Mohanta D (2010) Adaptive listen for energy-efficient medium access control in wireless sensor networks. Multimed Tools Appl 47:121–145

    Article  Google Scholar 

  9. Fonda WJ (2008) Energy efficient wireless sensor network protocols for monitoring and prognostics of large scale systems. PhD Dissertation, University of Missouri-Rolla

  10. Sridharan A, Krishnamachari B (2007) Maximizing network utilization with max-min fairness in wireless sensor networks. In: Proceedings of the 5th international symposium on modeling and optimization in mobile, ad hoc and wireless networks and workshops, WiOpt 2007, pp 1–9

  11. Brahma S, Chatterjee M, Kevin AK (2010) Congestion control and fairness in wireless sensor networks. In: Proceedings of PerCom workshops’2010, pp 413–418

  12. Han B, Simon G (2007) Fair capacity sharing among multiple sinks in wireless sensor networks. In: Proceedings of the IEEE MASS conference, pp 1–9

  13. Chen S, Zhang Z (2006) Localized algorithm for aggregate fairness in wireless sensor networks, MobiCom’06, Los Angeles, California, USA, pp 274–285

  14. Ee CT, Bajcsy R (2004) Congestion control and fairness for many-to-one routing in sensor networks. In SenSys ‘04: Proceedings of the 2nd international conference on embedded networked sensor systems, ACM, New York, pp 148–161

  15. Malakuti S, Aksit M, Bockisch C (2011) Runtime verification in distributed computing. JoC 2(1):1–10

    Google Scholar 

  16. Kim Y, Jeong S, Kim D, López TS (2009) An efficient scheme of target classification and information fusion in wireless sensor networks. Pers Ubiquit Comput 13(7):499–508

    Article  Google Scholar 

  17. Chaki S, Clarke EM, Ouaknine J, Sharygina N (2004) State/event-based software model checking. Integr Formal Methods 2004:128–147

    Article  Google Scholar 

  18. Reinbacher T, Horauer M, Schlich B, Brauer J, Scheuer F (2011) Model checking embedded software of an industrial knitting machine. IJITCC 1(2):186–205

    Article  Google Scholar 

  19. Sarkar P, Saha A (2011) Security enhanced communication in wireless sensor networks using reed-muller codes and partially balanced incomplete block designs. JoC 2(1):23–30

    Google Scholar 

  20. Huang C, Cheng RH, Chen SR, Li CI (2010) Enhancing network availability by tolerance control in multi-sink wireless sensor networks. JoC 1(1):15–22

    Article  Google Scholar 

  21. Xie B, Kumar A, Zhao D, Reddy R, He B (2010) On secure communication in integrated heterogeneous wireless networks. IJITCC 1(1):4–23. doi:10.1504/IJITCC.2010.035224

    Article  Google Scholar 

  22. Cheikhrouhou O, Koubâa A, Dini G and Abid M (2011) RiSeG: a ring based secure group communication protocol for resource-constrained wireless sensor networks. Pers Ubiquit Comput 15:783–797. doi:10.1007/s00779-011-0365-5

    Google Scholar 

  23. Malhotra R, Garg M (2011) An adequacy based test data generation technique using genetic algorithms. J Inf Process Syst 7(2):363–384

    Google Scholar 

  24. Challa JS, Paul A, Dada Y, Nerella V, Srivastava PR, Singh AP (2011) Integrated software quality evaluation: a fuzzy multi-criteria approach. J Inf Process Syst 7(3):473–518

    Google Scholar 

  25. Kesten Y, Pnueli A, Raviv L, Shahar E (2006) Model checking with strong fairness. Formal Methods Syst Des 28(1):57–84

    Article  MATH  Google Scholar 

  26. Queille J, Sifakis J (1983) Fairness and related properties in transition systems-a temporal logic to deal with fairness. Acta Inform 19:195–220

    Article  MathSciNet  MATH  Google Scholar 

  27. Kwiatkowska MZ (1989) Survey of fairness notions. Inf Softw Technol 31(7):371–386

    Article  Google Scholar 

  28. Francez N (1988) Fairness. Springer, New York

    Google Scholar 

  29. Lehmann DJ, Pnueli A, Stavi J (1981) Impartiality, justice and fairness: the ethics of concurrent termination. In Proceedings of ICALP 1981, pp 264–277

  30. Larsen KG, Thomsen B (1988) A modal process logic. In: Third annual symposium on logic in computer science. IEEE Computer Society Press, pp 203–210

  31. Holzmann GJ (2003) The SPIN model checker: primer and reference manual. Addison Wesley, Reading

  32. Henzinger MR, Telle JA (1996) Faster algorithms for the nonemptiness of streett automata and for communication protocol pruning. In: Proceedings of SWAT 1996, pp 16–27

  33. Latvala T, Heljanko K (2000) Coping with strong fairness. Fundamenta Informaticae 43(1-4):175–193

    MathSciNet  MATH  Google Scholar 

  34. Biere A, Cimatti A, Clarke EM, Strichman O, Zhu YS (2003) Bounded model checking. Advances in computers, vol 58. Academic Press, London

  35. Schwoon S, Esparza J (2005) A note on on-the-fly verification algorithms. In: Tools and algorithms for the construction and analysis of systems (TACAS.05). Lecture notes in computer science, vol 3440, pp 174–190

  36. Clarke EM, Gupta A, Kukula J, Strichman O (2002) SAT based abstraction-refinement using ILP and machine learning techniques. In: Proceedings of 14th international conference on computer aided verification (CAV’02), vol 2404. Lecture notes in computer science, pp 265–279

  37. McMillan KL (1993) Symbolic model checking. Kluwer, Dordrecht, pp 369

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Acknowledgments

The authors would like to thank the editors and anonymous referees for their suggestions and the remarkable improvements they brought to this paper. This paper has been supported by the National Natural Science Foundation of China (No. 61003080, 61070202, 91018007, and 60970001), the Ph.D. Programs Foundation of Ministry of Education of China (No. 2009D5-0056), Tianjin Research Program of Application Foundation and Advanced Technology (No.10JCZDJC15700) and the program of the 985 project of Tianjin University.

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Authors and Affiliations

  1. Institute of Knowledge Science and Engineering, School of Computer Science and Technology, Tianjin University, 92 Weijin Road, Nankai District, Tianjin, 300072, People’s Republic of China

    Guangquan Xu, Rui Xu, Xiaohong Li & Zhiyong Feng

  2. College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, People’s Republic of China

    Weisheng Li

  3. Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin, People’s Republic of China

    Yingyuan Xiao

  4. Shanghai Key Laboratory of Computer Software Evaluating and Testing, Shanghai University, Shanghai, 201112, People’s Republic of China

    Honghao Gao

  5. Guangxi Economic Management Cadre College, Guangxi, People’s Republic of China

    Jia Mei

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  1. Guangquan Xu
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  2. Weisheng Li
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Correspondence to Guangquan Xu.

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Xu, G., Li, W., Xu, R. et al. An algorithm on fairness verification of mobile sink routing in wireless sensor network. Pers Ubiquit Comput 17, 851–864 (2013). https://doi.org/10.1007/s00779-012-0536-z

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