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Source Routing in Time-Varing Lossy Networks

  • Dacfey Dzung
  • Rachid Guerraoui
  • David KozhayaEmail author
  • Yvonne-Anne Pignolet
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9466)

Abstract

This paper addresses the path selection problem arising in multi-hop sensor networks, e.g., Smart Grids. A set of multi-hop paths, of varying transmission quality, connect source and destination nodes. The source must select one path for each message to send without knowing the state of the hops. It can however use information deduced from earlier transmissions to decide on a good path for the current message. The goal is to maximize the discounted number of successfully delivered messages. We prove that the myopic routing policy, arguably the most appealing known way to tackle this problem, can permanently ignore good paths. We also generalize an empirically proven good approach, the Whittle index, and show its intractability for the problem at hand. We propose a new tractable metric, Harmonic Discounted Index (HDI), as a measure of attractiveness of transmitting over a path. We evaluate the performance of our HDI metric in a variety of simulation scenarios revealing a superior performance compared to all alternative index policies.

Keywords

Source routing partially observable Markov decision process Time-varying lossy channels 

References

  1. 1.
    Ahmad, S., Liu, M., Javidi, T., Zhao, Q., Krishnamachari, B.: Optimality of myopic sensing in multichannel opportunistic access. IEEE Trans. Inf. Theor. 55(9), 4040–4050 (2009)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Bertsekas, D.P.: Dynamic Programming and Optimal Control, 2nd edn. Athena Scientific, Belmont (2000)Google Scholar
  3. 3.
    Bumiller, G., Lampe, L., Hrasnica, H.: Power line communication networks for large-scale control and automation systems. IEEE Commun. Mag. 48(4), 106–113 (2010)CrossRefGoogle Scholar
  4. 4.
    Chatterjee, K., Majumdar, R.: Discounting and averaging in games across time scales. Int. J. Found. Comput. Sci. 23(3), 609–625 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Johnson, D.M.D., Hu, Y.: The dynamic source routing protocol (DSR) for mobile Ad hoc networks for IPv4. Technical report, IETF (2007). http://tools.ietf.org/html/rfc4728
  6. 6.
    DLC+VIT4IP. Scenarios and requirements specification. Technical report, 1010. http://www.dlc-vit4ip.org/wb/media/Downloads
  7. 7.
    Dzung, D., Guerraoui, R., Kozhaya, D., Pignolet, Y.-A.: Dynamic path selection in source routing for time-varying lossy networks. Technical report, Extended version (2014). http://infoscience.epfl.ch/record/206986
  8. 8.
    Dzung, D., Pignolet, Y.-A.: Dynamic selection of wireless/powerline links using Markov decision processes. In: IEEE SmartGridComm (2013)Google Scholar
  9. 9.
    Elliott, E.O.: Estimates of error rates for codes on burst-noise channels. Bell Syst. Tech. J 42, 1977–1997 (1963)CrossRefGoogle Scholar
  10. 10.
    Gilbert, E.N., et al.: Capacity of a burst-noise channel. Bell Syst. Tech. J 39(9), 1253–1265 (1960)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Guha, S., Munagala, K., Shi, P.: Approximation algorithms for restless bandit problems. J. ACM 58(1), 1–50 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  12. 12.
    Hasslinger, G., Hohlfeld, O.: The gilbert-elliott model for packet loss in real time services on the internet. In: MMB, pp. 1–15, March 2008Google Scholar
  13. 13.
    Liu, K., Zhao, Q.: Indexability of restless bandit problems and optimality of whittle index for dynamic multichannel access. IEEE Trans. Inf. Theor. 56(10), 5547–5567 (2010)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Mitton, N., Sericola, B., Tixeuil, S., Fleury, E., Lassous, I.G.: Self-stabilization in self-organized wireless multihop networks? Ad Hoc Sens. Wireless Netw. 11(1–2), 1–34 (2011)Google Scholar
  15. 15.
    Nayyar, N., Gai, Y., Krishnamachari, B.: On a restless multi-armed bandit problem with non-identical arms. In: Allerton, pp. 369–376 (2011)Google Scholar
  16. 16.
    Ny, J., Dahleh, M., Feron, E.: Multi-uav dynamic routing with partial observations using restless bandit allocation indices. In: American Control Conference, pp. 4220–4225 (2008)Google Scholar
  17. 17.
    Rao, R., Akella, S., Guley, G.: Power line carrier (PLC) signal analysis of smart meters for outlier detection. In: IEEE SmartGridComm, pp. 291–296 (2011)Google Scholar
  18. 18.
    Tang, C., McKinley, P.K.: Modeling multicast packet losses in wireless lans. In: MSWIM 2003, pp. 130–133. ACM, New York (2003)Google Scholar
  19. 19.
    Vasseur, J.: Terminology in low power and lossy networks. Technical report, Cisco Systems Inc. (2013)Google Scholar
  20. 20.
    Vasseur, J.-P., Dunkels, A.: Interconnecting smart objects with IP: the next internet. Morgan Kaufmann Publishers, Inc. (2010)Google Scholar
  21. 21.
    Weber, R.R., Weiss, G.: On an index policy for restless bandits. Journal of Applied Probability, pp. 637–648 (1990)Google Scholar
  22. 22.
    Whittle, P.: Restless bandits: activity allocation in a changing world. J. Appl. Probab. 25, 287–298 (1988)MathSciNetCrossRefzbMATHGoogle Scholar
  23. 23.
    Winter, T., Thubert, P., Brandt, A., Hui, J., Kelsey, R., Levis, P., Pister, K., Struik, R., Vasseur, J., Alexander, R.: RPL: IPv6 routing protocol for low-power and lossy networks. Technical report, IETF (2012). http://tools.ietf.org/html/rfc6550
  24. 24.
    Zayen, B., Hayar, A., Noubir, G.: Game theory-based resource management strategy for cognitive radio networks. Multimedia Tools Appl. 70(3), 2063–2083 (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Dacfey Dzung
    • 2
  • Rachid Guerraoui
    • 1
  • David Kozhaya
    • 1
    Email author
  • Yvonne-Anne Pignolet
    • 2
  1. 1.EPFL IC IIF LPD, INR 315 (Bâtiment INR)LausanneSwitzerland
  2. 2.ABB Corporate ResearchRaleighSwitzerland

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