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Formal Modeling and Analysis of Learning-Based Routing in Mobile Wireless Sensor Networks

  • Fatemeh Kazemeyni
  • Olaf Owe
  • Einar Broch Johnsen
  • Ilangko Balasingham
Chapter
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 263)

Abstract

Limited energy supply is a major concern when dealing with wireless sensor networks (WSNs). Therefore, routing protocols for WSNs should be designed to be energy efficient. This chapter considers a learning-based routing protocol for WSNs with mobile nodes, which is capable of handling both centralized and decentralized routing. A priori knowledge of the movement patterns of the nodes is exploited to select the best routing path, using a Bayesian learning algorithm. While simulation tools cannot generally prove that a protocol is correct, formal methods can explore all possible behaviors of network nodes to search for failures. We develop a formal model of the learning-based protocol and use the rewriting logic tool Maude to analyze both the correctness and efficiency of the model. Our experimental results show that the decentralized approach is twice as energy-efficient as the centralized scheme. It also outperforms the power-sensitive AODV (PS-AODV), an efficient but non-learning routing protocol. Our formal model of Bayesian learning integrates a real data-set which forces the model to conform to the real data. This technique seems useful beyond the case study of this chapter.

Keywords

Wireless sensor networks Mobility Learning Routing Formal modeling and analysis Probabilistic modeling Rewriting logic Maude 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Fatemeh Kazemeyni
    • 1
    • 2
  • Olaf Owe
    • 1
  • Einar Broch Johnsen
    • 1
  • Ilangko Balasingham
    • 2
    • 3
  1. 1.Department of InformaticsUniversity of OsloOsloNorway
  2. 2.The Intervention CenterOslo University Hospitals, University of OsloOsloNorway
  3. 3.Department of Electronics and TelecommunicationNorwegian University of Science and TechnologyTrondheimNorway

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