Applying genetic algorithm for optimizing broadcasting process in ad-hoc network

Said Elaiwat, Ammar Alazab, Sitalakshmi Venkatraman, Mamoun Alazab

Research output: Contribution to journalArticlepeer-review


Optimizing broadcasting process in mobile ad hoc network (MANET) is considered as a main challenge due to many problems, such as Broadcast Storm problem and high complexity in finding the optimal tree resulting in an NP-hard problem. Straight forward techniques like simple flooding give rise to Broadcast Storm problem with a high probability. In this work, genetic algorithm (GA) that searches over a population that represents a distinguishable 'structure' is adopted innovatively to suit MANETs. The novelty of the GA technique adopted here to provide the means to tackle this MANET problem lies mainly on the proposed method of searching for a structure of a suitable spanning tree that can be optimized, in order to meet the performance indices related to the broadcasting problem. In other words, the proposed genetic model (GM) evolves with the structure of random trees (individuals) 'genetically' generated using rules that are devised specifically to capture MANET behaviour in order to arrive at a minimal spanning tree that satisfies certain fitness function. Also, the model has the ability to give different solutions depending on the main factors specified such as, 'time' (or speed) in certain situations and 'reachability' in certain others.
Original languageEnglish
Pages (from-to)68-72
Number of pages5
JournalInternational journal on recent trends in engineering and technology
Issue number1
Publication statusPublished - 2010
Externally publishedYes


  • network
  • genetic algorithm
  • optimisation
  • spanning tree


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