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The Time-Free Comparison Model for Fault Diagnosis in Wireless Ad Hoc Networks

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Abstract

This paper describes a new comparison-based model for fault diagnosis in wireless ad hoc networks. Fault diagnosis is crucial for ensuring the dependability of systems. Wireless ad hoc networks are highly prone to faults as consequence of their dynamical conditions. The comparison approach is a practical diagnosis model that has been used to develop self-diagnosis systems in wired and wireless networks. This approach can detect and diagnose hard and soft faults in systems. The traditional fault diagnostic models were designed for static networks. Thus, they cannot provide complete and correct fault diagnosis in mobile wireless networks. In this paper, we introduce a time-free self-diagnosis model that respects the design requirements of mobile wireless networks. That is, it adapts to the topology’s changes, it imposes no known bounds on time delays, and it requires limited network information. Further, we develop a fault diagnosis protocol that can correctly diagnose faulty nodes undergoing static and dynamic faults in mobile ad-hoc networks (MANETs). Both an analytical model and a simulation study have been used to prove and evaluate the efficiency of our protocol under various scenarios. Furthermore, the performance of our protocol is compared with related protocols. The results show that our proposed protocol is efficient in terms of communication and time complexity.

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References

  1. Casteigts A et al. (2011) Time-varying graphs and dynamic networks. In International Conference on Ad-Hoc Networks and Wireless. Springer

  2. Rasheed A et al (2017) Vehicular ad hoc network (VANET): a survey, challenges, and applications. Springer Singapore, Singapore

    Google Scholar 

  3. Qiu T, Chen N, Li K, Qiao D, Fu Z (2017) Heterogeneous ad hoc networks: architectures, advances and challenges. Ad Hoc Netw 55:143–152

    Article  Google Scholar 

  4. Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Comput Netw 52(12):2292–2330

    Article  Google Scholar 

  5. Miranda K, Molinaro A, Razafindralambo T (2016) A survey on rapidly deployable solutions for post-disaster networks. IEEE Commun Mag 54(4):117–123

    Article  Google Scholar 

  6. Sarkar SK, Basavaraju TG, Puttamadappa C (2016) Ad hoc mobile wireless networks: principles, protocols, and applications. CRC Press

  7. Jarrah H, Sarkar NI, Gutierrez J (2016) Comparison-based system-level fault diagnosis protocols for mobile ad-hoc networks: a survey. J Netw Comput Appl 60:68–81

    Article  Google Scholar 

  8. Azar HN, Malazi HT (2018) Decentralized detection of hybrid faults in mobile sensor nodes. Simul Model Pract Theory 87:210–225

    Article  Google Scholar 

  9. Avizienis A, Laprie JC, Randell B, Landwehr C (2004) Basic concepts and taxonomy of dependable and secure computing. IEEE Trans Dependable Secure Comput 1(1):11–33

    Article  Google Scholar 

  10. Muhammed T, Shaikh RA (2017) An analysis of fault detection strategies in wireless sensor networks. J Netw Comput Appl 78:267–287

    Article  Google Scholar 

  11. Zhang Z, Mehmood A, Shu L, Huo Z, Zhang Y, Mukherjee M (2018) A survey on fault diagnosis in wireless sensor networks. IEEE Access 6:11349–11364

    Article  Google Scholar 

  12. Novotny P, Ko BJ, Wolf AL (2018) Locating faults in MANET-hosted software systems. IEEE Trans Dependable Secure Comput 3:452–465

    Article  Google Scholar 

  13. Yue Y-G, He P (2018) A comprehensive survey on the reliability of mobile wireless sensor networks: taxonomy, challenges, and future directions. Information Fusion 44:188–204

    Article  Google Scholar 

  14. Mahapatro A, Khilar PM (2013) Fault diagnosis in wireless sensor networks: a survey. IEEE Commun Surveys Tutor 15(4):2000–2026

    Article  Google Scholar 

  15. Preparata FP, Metze G, Chien RT (1967) On the connection assignment problem of diagnosable systems. IEEE Trans Electron Comput EC-16(6):848–854

    Article  Google Scholar 

  16. Malek M (1980) A comparison connection assignment for diagnosis of multiprocessor systems. In Proceedings of the 7th annual symposium on Computer Architecture. ACM

  17. Duarte EP, Ziwich JRP, Albini LCP (2011) A Survey of Comparison-Based System-Level Diagnosis. ACM Comput Surveys (CSUR) 43(3):1–56

    Article  Google Scholar 

  18. Chwa K-Y, Hakimi SL (1981) Schemes for fault-tolerant computing: a comparison of modularly redundant and t-diagnosable systems. Inf Control 49(3):212–238

    Article  MathSciNet  Google Scholar 

  19. Somani AK (1997) System level diagnosis: A review. Technique Report, Dependable Computer Laboratory, Iowa State University

  20. Chessa S, Santi P (2001) Comparison-based system-level fault diagnosis in ad hoc networks. In: Proceedings 20th IEEE Symposium on Reliable Distributed Systems. IEEE, New Orleans

    Google Scholar 

  21. Elhadef M, Boukerche A, Elkadiki H (2006) Diagnosing mobile ad-hoc networks: two distributed comparison-based self-diagnosis protocols. In Proceedings of the 4th ACM international workshop on Mobility management and wireless access. ACM

  22. Jarrah H et al. (2016) A Time-Free Comparison-Based System-Level Fault Diagnostic Model for Highly Dynamic Networks. In Proceedings of the 11th International Conference on Queueing Theory and Network Applications. ACM

  23. Greve F, Arantes L, Sens P (2011) What model and what conditions to implement unreliable failure detectors in dynamic networks? In Proceedings of the 3rd International Workshop on Theoretical Aspects of Dynamic Distributed Systems. ACM

  24. Greve F, et al. (2011) Asynchronous implementation of failure detectors with partial connectivity and unknown participants

  25. Greve F et al. (2012) A Time-Free Byzantine Failure Detector for Dynamic Networks. In Proceedings of the 2012 Ninth European Dependable Computing Conference. IEEE Comput Soc

  26. Mostefaoui A et al (2005) From static distributed systems to dynamic systems. in 24th IEEE Symposium on Reliable Distributed Systems (SRDS 2005). IEEE, Orlando

    Google Scholar 

  27. Aguilera MK (2004) A pleasant stroll through the land of infinitely many creatures. ACM Sigact News 35(2):36–59

    Article  Google Scholar 

  28. Santoro N (2006) Design and analysis of distributed algorithms, vol 56. John Wiley & Sons

  29. Elhadef M, Boukerche A, Elkadiki H (2008) A distributed fault identification protocol for wireless and mobile ad hoc networks. J Parallel Distrib Comput 68(3):321–335

    Article  Google Scholar 

  30. Elhadef M, Grira S (2016) Comparison-based system level fault diagnosis using game theory. In 2016 Fourth International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE

  31. Hsu G-H, Tan JJ (2007) A local diagnosability measure for multiprocessor systems. IEEE Trans Parallel Distrib Syst 18(5)

  32. Lin C-K, Teng YH, Tan JJM, Hsu LH (2013) Local diagnosis algorithms for multiprocessor systems under the comparison diagnosis model. IEEE Trans Reliab 62(4):800–810

    Article  Google Scholar 

  33. Koo C-Y (2004) Broadcast in radio networks tolerating byzantine adversarial behavior. In Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing. ACM

  34. Bhandari V, Vaidya NH (2010) Reliable broadcast in radio networks with locally bounded failures. IEEE Trans Parallel Distrib Syst 21(6):801–811

    Article  Google Scholar 

  35. Sengupta A, Dahbura AT (1992) On self-diagnosable multiprocessor systems: diagnosis by the comparison approach. IEEE Trans Comput 41(11):1386–1396

    Article  MathSciNet  Google Scholar 

  36. Fidge CJ (1987) Timestamps in message-passing systems that preserve the partial ordering

  37. Arantes L et al. (2013) Eventual leader election in evolving mobile networks, in Principles of Distributed Systems. Springer, p 23–37

  38. Varga A (2019) A practical introduction to the OMNeT++ simulation framework, in Recent Advances in Network Simulation. Springer, p 3–51

  39. Sarkar NI, Gutiérrez JA (2014) Revisiting the issue of the credibility of simulation studies in telecommunication networks: highlighting the results of a comprehensive survey of IEEE publications. IEEE Commun Mag 52(5):218–224

    Article  Google Scholar 

  40. Zarrad A, Alsmadi I (2017) Evaluating network test scenarios for network simulators systems. Int J Distrib Sens Networks 13(10):1550147717738216

    Google Scholar 

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Correspondence to Hazim Jarrah.

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Jarrah, H., Ali, G.G.M.N., Kumar, A. et al. The Time-Free Comparison Model for Fault Diagnosis in Wireless Ad Hoc Networks. Mobile Netw Appl 27, 469–482 (2022). https://doi.org/10.1007/s11036-020-01691-4

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