Multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints

Erfu Yang, Ahmet T. Erdogan, Tughrul Arslan, Nick Barton

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

13 Citations (Scopus)

Abstract

Wireless sensor networks have emerged as a promising way to develop high security systems. This paper presents the optimizations of a space-based reconfigurable sensor network under hard constraints by employing an efficient multi-objective evolutionary algorithm (MOEA). First, a system model is proposed for cluster-based space wireless sensor networks. Second, the statement of multi-objective optimization problems is mathematically formulated under multiple constraints. Third, the MOEA is used to find multicriteria solutions in the sense of Parelo optimizations. Finally, simulation results are provided to illustrate the effectiveness of applying the MOEA to the multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints.

Original languageEnglish
Title of host publicationECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, 2007. BLISS 2007.
PublisherIEEE
Pages72-75
Number of pages4
ISBN (Print)0-7695-2919-4
DOIs
Publication statusPublished - 1 Dec 2007
Event2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007 - Edinburgh, United Kingdom
Duration: 9 Aug 200710 Aug 2007

Conference

Conference2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007
CountryUnited Kingdom
CityEdinburgh
Period9/08/0710/08/07

Keywords

  • evolutionary computation
  • high security systems
  • multiobjective evolutionary optimization
  • wireless sensor networks

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