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Asynchronous neighbor discovery with unreliable link in wireless mobile networks

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Abstract

In wireless mobile networks, neighbor discovery is fundamental to many useful applications. The limited energy of mobile devices stresses the need for effective and energy-saving asynchronous neighbor discovery protocols. The neighbor discovery would fail due to some uncontrollable factors such as hardware errors or sudden interruptions, which are considered as the unreliable link in this paper. Existing works do not take the unreliable link into consideration and the performances with unreliable link can still be improved. In this paper, we assume a certain probability that unreliable link would happen, and design a novel deterministic Quorum System (QS)—E-grid(k) QS and a novel probabilistic QS—Plain(k) QS and propose two algorithms based on these two QSs to solve the asynchronous neighbor discovery problem in wireless mobile networks with unreliable link. Extensive simulations are conducted to evaluate our algorithms. We use the cumulative distribution function (CDF) of the discovery latency and the Valid Overlapped Time Slots (VOTS) of QS in the evaluation. Simulation results show that Plain(k) and E-grid(k) QSs outperform most existing neighbor discovery protocols in both P2P model and clique model with unreliable or reliable link.

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References

  1. 1.

    Bakht M, Trower M, Kravets RH (2012) Searchlight: won’t you be my neighbor? In: Proceedings of the 18th annual international conference on mobile computing and networking. Istanbul, pp 185–196

  2. 2.

    Bracciale L, Loreti P, Bianchi G (2016) The sleepy bird catches more worms: revisiting energy efficient neighbor discovery. IEEE Trans Mob Comput 15(7):1812–1825

    Article  Google Scholar 

  3. 3.

    Chen L, Li Y, Vasilakos AV (2016) Oblivious neighbor discovery for wireless devices with directional antennas. In: Proceedings of the IEEE international conference on computer communications. San Francisco, pp 1–9

  4. 4.

    Chen S, Russell A, Jin R, Qin Y, Wang B, Vasudevan S (2015) Asynchronous neighbor discovery on duty-cycled mobile devices: integer and non-integer schedules. In: Proceedings of the 16th ACM international symposium on mobile Ad Hoc networking and computing. Hangzhou, pp 47–56

  5. 5.

    Duan X, Zhao C, He S, Cheng P, Zhang J (2017) Distributed algorithms to compute walrasian equilibrium in mobile crowdsensing. IEEE Trans Ind Electron 64(5):4048–4057

    Article  Google Scholar 

  6. 6.

    Dutta P, Culler D (2008) Practical asynchronous neighbor discovery and rendezvous for mobile sensing applications. In: Proceedings of the 6th ACM conference on embedded network sensor systems. Raleigh, pp 71–84

  7. 7.

    Hardy GH, Wright EM (1979) An introduction to the theory of numbers. Oxford University Press

  8. 8.

    He S, Li X, Chen J, Cheng P, Sun Y, Simplot-Ryl D (2013) Emd: energy-efficient p2p message dissemination in delay-tolerant wireless sensor and actor networks. IEEE J Selected Areas Commun 31(9):75–84

    Article  Google Scholar 

  9. 9.

    Jiang JR (2008) Expected quorum overlap sizes of quorum systems for asynchronous power-saving in mobile ad hoc networks. Comput Netw 52(17):3296–3306

    Article  MATH  Google Scholar 

  10. 10.

    Jiang JR, Tseng YC, Hsu CS, Lai TH (2005) Quorum-based asynchronous power-saving protocols for ieee 802.11 ad hoc networks. Mobile Netw Appl 10(1–2):169–181

    Article  Google Scholar 

  11. 11.

    Kandhalu A, Lakshmanan K, Rajkumar RR (2010) U-connect: a low-latency energy-efficient asynchronous neighbor discovery protocol. In: Proceedings of the 9th ACM/IEEE international conference on information processing in sensor networks. Stockholm, pp 350–361

  12. 12.

    Lang S, Mao L (1998) A torus quorum protocol for distributed mutual exclusion. In: Proceedings of the 10th international conference on parallel and distributed computing and systems. Las Vegas, pp 635–638

  13. 13.

    Li Z, Zhang J, Shen X, Fan J (2017) Prediction based indoor fire escaping routing with wireless sensor network. Peer-to-Peer Network Appl 10(3):697–707

    Article  Google Scholar 

  14. 14.

    Luk WS, Wong TT (1997) Two new quorum based algorithms for distributed mutual exclusion. In: Proceedings of the 17th International conference on distributed computing systems. Baltimore, pp 100–106

  15. 15.

    Maekawa M (1985) A \(\sqrt {n}\) algorithm for mutual exclusion in decentralized systems. ACM Trans Comput Syst 3(2):145–159

    Article  Google Scholar 

  16. 16.

    Malkhi D, Reiter MK, Wool A, Wright RN (2001) Probabilistic quorum systems. Inf Comput 170 (2):184–206

    MathSciNet  Article  MATH  Google Scholar 

  17. 17.

    Margolies R, Grebla G, Chen T, Rubenstein D, Zussman G (2016) Panda: neighbor discovery on a power harvesting budget. IEEE J Selected Areas Commun 34(12):3606–3619

    Article  Google Scholar 

  18. 18.

    McGlynn MJ, Borbash SA (2001) Birthday protocols for low energy deployment and flexible neighbor discovery in ad hoc wireless networks. In: Proceedings of the 2nd ACM international symposium on mobile ad hoc networking & computing. Long Beach, pp 137–145

  19. 19.

    Meng T, Wu F, Chen G (2016) Code-based neighbor discovery protocols in mobile wireless networks. IEEE/ACM Trans Network 24(2):806–819

    Article  Google Scholar 

  20. 20.

    Qiu Y, Li S, Xu X, Li Z (2016) Talk more listen less: Energy-efficient neighbor discovery in wireless sensor networks. In: Proceedings of the IEEE international conference on computer communications. San Francisco, pp 1–9

  21. 21.

    Rahman MR, Tseng L, Nguyen S, Gupta I, Vaidya N (2017) Characterizing and adapting the consistency-latency tradeoff in distributed key-value stores. ACM Trans Autonom Adapt Syst 11(4):20

    Google Scholar 

  22. 22.

    Vasudevan S, Adler M, Goeckel D, Towsley D (2013) Efficient algorithms for neighbor discovery in wireless networks. IEEE/ACM Trans Network 21(1):69–83

    Article  Google Scholar 

  23. 23.

    Wang X, Sun H, Deng T, Huai J (2015) On the tradeoff of availability and consistency for quorum systems in data center networks. Comput Netw 76:191–206

    Article  Google Scholar 

  24. 24.

    Yang Q, He S, Li J, Chen J, Sun Y (2015) Energy-efficient probabilistic area coverage in wireless sensor networks. IEEE Trans Veh Technol 64(1):367–377

    Article  Google Scholar 

  25. 25.

    Zhang H, Zheng WX (2018) Denial-of-service power dispatch against linear quadratic control via a fading channel. IEEE Transactions on Automatic Control. https://doi.org/10.1109/TAC.2018.2789479

  26. 26.

    Zhang H, Qi Y, Zhou H, Zhang J, Sun J (2017a) Testing and defending methods against dos attack in state estimation. Asian Jof Control 19(4):1295–1305

  27. 27.

    Zhang H, Qi Y, Wu J, Fu L, He L (2018) Dos attack energy management against remote state estimation. IEEE Trans Control Netw Syst 5(1):383–394

    MathSciNet  Article  MATH  Google Scholar 

  28. 28.

    Zhang J, Tang S, Shen X, Dai G, Nayak A (2011) Quorum-based localized scheme for duty cycling in asynchronous sensor networks. In: Proceedings of the IEEE 8th international conference on mobile Adhoc and sensor systems. Valencia, pp 440–449

  29. 29.

    Zhang J, Li Z, Tang S (2016) Value of information aware opportunistic duty cycling in solar harvesting sensor networks. IEEE Trans Indus Inform 12(1):348–360

    Article  Google Scholar 

  30. 30.

    Zhang J, Li Z, Lin X, Jiang F (2017) Composite task selection with heterogeneous crowdsourcing. In: Proceedings of the 14th Annual IEEE international conference on sensing, communication, and networking. San Diego, pp 1–9

  31. 31.

    Zhang Z, Zhang H, He S, Cheng P (2017c) Bilateral privacy-preserving utility maximization protocol in database-driven cognitive radio networks. IEEE Transactions on Dependable and Secure Computing. https://doi.org/10.1109/TDSC.2017.2781248

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Acknowledgements

This work is under the support of the general program of the National Natural Science Foundation of China (NSFC) under Grants No. 61473109, 61671193, 61572164 and 61772472, the Natural Science Foundation of Zhejiang Province under Grant No. LY17F020020, the Key Research and Development Plan of Zhejiang Province under Grant No. 2018C04012, the Graduate Scientific Research Foundation and the Excellent Dissertation Fostering Foundation of Hangzhou Dianzi University.

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Correspondence to Jianhui Zhang.

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This article is part of the Topical Collection: Special Issue on Network Coverage

Guest Editors: Shibo He, Dong-Hoon Shin, and Yuanchao Shu

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Li, W., Zhang, J., Jiang, F. et al. Asynchronous neighbor discovery with unreliable link in wireless mobile networks. Peer-to-Peer Netw. Appl. 12, 635–646 (2019). https://doi.org/10.1007/s12083-018-0672-y

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Keywords

  • Neighbor discovery
  • Wireless mobile network
  • Quorum system
  • Unreliable link