JAID: An algorithm for data fusion and jamming avoidance on distributed sensor networks

  • Authors:
  • Aristides Mpitziopoulos;Damianos Gavalas;Charalampos Konstantopoulos;Grammati Pantziou

  • Affiliations:
  • Department of Cultural Technology and Communication, University of the Aegean, Lesvos, Greece;Department of Cultural Technology and Communication, University of the Aegean, Lesvos, Greece;Research Academic Computer Technology Institute, Patras, Greece;Department of Informatics, Technological Educational Institution of Athens, Athens, Greece

  • Venue:
  • Pervasive and Mobile Computing
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Mobile Agent (MA) technology has been recently proposed in Wireless Sensor Networks (WSNs) literature to answer the scalability problem of client/server model in data fusion applications. In this paper, we describe the critical role MAs can play in the field of security and robustness of a WSN in addition to data fusion. The design objective of our Jamming Avoidance Itinerary Design (JAID) algorithm is twofold: (a) to calculate near-optimal routes for MAs that incrementally fuse the data as they visit the nodes; (b) in the face of jamming attacks against the WSN, to modify the itineraries of the MAs to bypass the jammed area(s) while not disrupting the efficient data dissemination from working sensors. If the number of jammed nodes is small, JAID only modifies the pre-jamming scheduled itineraries to increase the algorithm's promptness. Otherwise, JAID re-constructs the agent itineraries excluding the jammed area(s). Another important feature of JAID is the suppression of data taken from sensors when the associated successive readings do not vary significantly. Data suppression also occurs when sensors' readings are identical to those of their neighboring sensors. Simulation results confirm that JAID enables retrieval of information from the working sensors of partially jammed WSNs and verifies its performance gain over alternative approaches in data fusion tasks.