An evolutionary computational approach for optimizing broadcasting in disaster response scenarios

D. G. Reina, S. L. Toral, J. M. Leon-Coca, F. Barrero, N. Bessis, E. Asimakopoulou

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)peer-review

7 Citations (Scopus)

Abstract

Rescue teams require exchanging tactical information to efficiently adapt their behavior to the particular disaster response scenario conditions. Broadcasting is the main technique used to disseminate messages throughout nodes in ad hoc networks. Ad hoc networks are one of the most appealing networks to be used in disaster response scenario due to their decentralized and self-organizing features. While many broadcasting techniques have been presented for ad hoc networks, there are not adaptive broadcasting schemes for disaster response scenarios so far. The complexity of designing broadcasting protocols for disaster response scenarios is high due to the large number of factors affecting the communications among nodes, such as mobility, density, message collisions, etc. In this paper we propose an evolutionary computational approach for designing and optimizing a probability-based broadcast scheme using topological features of nodes. The validity of the proposed approach is shown through simulations.

Original languageEnglish
Title of host publicationProceedings - 7th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2013
Pages94-100
Number of pages7
DOIs
Publication statusPublished - 19 Sep 2013
Event7th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2013 - Taichung, Taiwan, Province of China
Duration: 3 Jul 20135 Jul 2013

Publication series

NameProceedings - 7th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2013

Conference

Conference7th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2013
Country/TerritoryTaiwan, Province of China
CityTaichung
Period3/07/135/07/13

Keywords

  • Broadcasting
  • Disaster Scenarios
  • Genetic Algorithms
  • MANETs
  • Similarity Coefficients

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