Using data mules for sensor network resiliency

Jon Crowcroft, Liron Levin, Michael Segal

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In this paper, we study the problem of efficient data recovery using the data mules approach, where a set of mobile sensors with advanced mobility capabilities re-acquire lost data by visiting the neighbors of failed sensors, thereby improving network resiliency. Our approach involves defining the optimal communication graph and mules' placements such that the overall traveling time and distance is minimized regardless to which sensors crashed. We explore this problem under different practical network topologies such as general graphs, grids and random linear networks and provide approximation algorithms based on multiple combinatorial techniques. Simulation experiments demonstrate that our algorithms outperform various competitive solutions for different network models, and that they are applicable for practical scenarios.

Original languageEnglish
Title of host publication2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages427-434
Number of pages8
ISBN (Electronic)9783901882746
DOIs
StatePublished - 6 Jul 2015
Event2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015 - Mumbai, India
Duration: 25 May 201529 May 2015

Publication series

Name2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015

Conference

Conference2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2015
Country/TerritoryIndia
CityMumbai
Period25/05/1529/05/15

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Optimization
  • Modeling and Simulation

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