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Using a History-Based Approach to Predict Topology Control Information in Mobile Ad Hoc Networks

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8729))

Abstract

Several social computing participation strategies, such as crowdsensing and crowdsourcing, use mobile ad hoc or opportunistic networks to support the users activities. The unreliability and dynamism of these communication links make routing protocols a key component to achieve efficient and reliable data communication in physical environments. Often these routing capabilities come at expenses of flooding the network with a huge amount of topology control information (TCI), which can overload the communication links and dramatically increase the energy consumption of the participating devices. In previous works the authors have shown that predicting the network topology in these work scenarios helps reduce the number of control packets delivered through the network. This saves energy and increases the available bandwidth. This paper presents a study that extends the authors’ previous works, by identifying the impact of predicting the TCI generated by routing protocols in these networks. The prediction process is done following a history-based approach that uses information of the nodes past behavior. The paper also determines the predictability limits of this strategy, assuming that a TCI message can be correctly predicted if it appeared at least once in the past. The results show that the upper-bound limit of the history-based prediction approach is high, and that realistic prediction mechanisms can achieve significant ratios of accuracy. Mobile collaborative applications and routing protocols using mobile ad hoc or opportunistic networks can take advantage of this prediction approach to reduce network traffic, and consequently, the energy consumption of their devices.

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References

  1. Spyropoulos, T., et al.: Routing for Disruption Tolerant Networks: Taxonomy and Design. Wireless Networks 16(8) (2010)

    Google Scholar 

  2. Zeng, Y., et al.: Directional Routing and Scheduling for Green Vehicular Delay Tolerant Networks. Wireless Networks 19(2) (2013)

    Google Scholar 

  3. Vasilakos, A., et al.: Delay Tolerant Networks: Protocols and Applications. CRC Press (2012)

    Google Scholar 

  4. Youssef, M., et al.: Routing Metrics of Cognitive Radio Networks: A Survey. IEEE Communications Surveys and Tutorials 16(1) (2014)

    Google Scholar 

  5. Clausen, T., Jacquet, P.: Optimized Link State Routing Protocol (OLSR). IETF RFC 3626 (October 2003)

    Google Scholar 

  6. Medina, E., Meseguer, R., Molina, C., Royo, D.: OLSRp: Predicting Control Information to Achieve Scalability in OLSR Ad Hoc Networks. In: Pentikousis, K., Agüero, R., García-Arranz, M., Papavassiliou, S. (eds.) MONAMI 2010. LNICST, vol. 68, pp. 225–236. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  7. Meseguer, R., et al.: Reducing Energy Consumption in Human-Centric Wireless Sensor Networks. In: Procs. IEEE Int. Conf. on Systems, Man, & Cybernetics (October 2012)

    Google Scholar 

  8. Meseguer, R., et al.: Energy-Aware Topology Control Strategy for Human-Centric Wireless Sensor Networks. Sensors Journal 14 (February 2014)

    Google Scholar 

  9. Maleki, M., Dantu, K., Pedram, M.: Lifetime Prediction Routing in Mobile Ad Hoc Networks. In: Wireless Communication& Networking, pp. 1185–1190. IEEE Press (2003)

    Google Scholar 

  10. Kim, D., et al.: Routing Mechanisms for Mobile Ad Hoc Networks Based on the Energy Drain Rate. IEEE Trans. on Mobile Computing (April 2003)

    Google Scholar 

  11. Chen, B., et al.: Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks. Journal of Wireless Networks 5 (2002)

    Google Scholar 

  12. Ye, F., et al.: Peas: A Robust Energy Conserving Protocol for Long-Lived Sensor Networks. In: Proc. of the 23rd Int. Conf. on Distributed Computing Systems (May 2003)

    Google Scholar 

  13. De Rosa, F., et al.: Disconnection Prediction in Mobile Ad Hoc Networks for Supporting Cooperative Work. IEEE Pervasive Computing (2005)

    Google Scholar 

  14. Su, W., Lee, S.J., Gerla, M.: Mobility Prediction and Routing in Ad Hoc Wireless Networks. International Journal of Network Management 11 (2001)

    Google Scholar 

  15. Millan, P., et al.: Tracking and Predicting Link Quality in Wireless Community Networks. Tech. Report UPC-DAC-RR-2014-10. DAC-UPC, Spain (June 2014)

    Google Scholar 

  16. Koksal, C.E., Balakrishnan, H.: Quality-Aware Routing Metrics for Time-Varying Wireless Mesh Networks. J. Selected Areas in Communications (2006)

    Google Scholar 

  17. NS-3, A Discrete-Event Network Simulator for Internet Systems, http://www.nsnam.org/

  18. Vergara, C., Ochoa, S.F., Gutierrez, F., Rodriguez-Covili, J.: Extending social networking services toward a physical interaction scenario. In: Bravo, J., López-de-Ipiña, D., Moya, F. (eds.) UCAmI 2012. LNCS, vol. 7656, pp. 208–215. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  19. Camp, T., Boleng, J., Davies, V.: A Survey of Mobility Models for Ad Hoc Network Research. Wirel. Commun. Mob. Comput. (2002)

    Google Scholar 

  20. Lee, K., Hong, S., Kim, S.J., Rhee, I., Chong, S.: Slaw: A New Mobility Model for Human Walks. In: Proceedings of INFOCOM 2009 (April 2009)

    Google Scholar 

  21. Aschenbruck, N., et al.: BonnMotion: A Mobility Scenario Generation and Analysis Tool. In: Procs. 3rd Int. ICST Conf. Simulation Tools & Techniques (March 2010)

    Google Scholar 

  22. Fu, X., Li, W., Fortino, G.: A utility-oriented routing algorithm for community based opportunistic networks. In: Proc. of the 2013 IEEE 17th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2013), June 27-29, pp. 675–680 (2013)

    Google Scholar 

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Millán, P., Molina, C., Meseguer, R., Ochoa, S.F., Santos, R. (2014). Using a History-Based Approach to Predict Topology Control Information in Mobile Ad Hoc Networks. In: Fortino, G., Di Fatta, G., Li, W., Ochoa, S., Cuzzocrea, A., Pathan, M. (eds) Internet and Distributed Computing Systems. IDCS 2014. Lecture Notes in Computer Science, vol 8729. Springer, Cham. https://doi.org/10.1007/978-3-319-11692-1_21

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  • DOI: https://doi.org/10.1007/978-3-319-11692-1_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11691-4

  • Online ISBN: 978-3-319-11692-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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