The broadcast storm problem in a mobile ad hoc network
Wireless Networks - Selected Papers from Mobicom'99
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Ad hoc Networking
BeeAdHoc: an energy efficient routing algorithm for mobile ad hoc networks inspired by bee behavior
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Future combat system - scalable mobile network demonstration performance and validation results
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume II
A brief overview of ad hoc networks: challenges and directions
IEEE Communications Magazine - Part Anniversary
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Highly dynamic topology is an essential feature of mobile ad hoc networks. For this reason, maintaining a consistent state for routing purposes can be a very difficult task. The primary goal is correct and efficient route establishment between a pair of nodes. Although a more challenging goal is to provide energy efficient routing protocols. This paper presents a concept of an energy efficient routing algorithm based on applying genetic algorithm (GA). The aim of the algorithm is a prolongation of life time of the network. The life time of the network depends on nodes life, which is a function of battery energy nodes. A routing metric is a time measure from a moment when the network starts up, to the moment when the first battery in any nodes runs down. The purpose of the proposed algorithm is to maximize the life time of the network. To choose a path we propose to use one of a few different heuristics. In this paper we describe the GA-based approach to find a heuristic combination for solving power-aware routing problem. A problem solution is such a heuristic combination, which depends on an actual state of the network (energy of nodes) and will choose optimal paths.