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Distributed Coevolutionary Genetic Algorithm for Optimal Design of Ad Hoc Injection Networks
| Content Provider | Semantic Scholar |
|---|---|
| Author | Danoy, Grégoire Bouvry, Pascal Alba, Enrique Guzmánde-De |
| Copyright Year | 2007 |
| Abstract | Multi-hop ad-hoc networks allow establishing local groups of communicating devices in a selforganizing way. However, in a global setting such networks fail to work properly due to network partitioning. This means that users locally interacting could eventually spread and move away from each other and consequently loose their connections. Considering that devices are capable of communicating both locally (e.g. using Wi-Fi or Bluetooth) and additionally with remote devices (e.g. using GSM/UMTS links) the objective of our work is to optimize the way of inter-linking multiple network partitions. To this end we rely on smallworld network properties, that consist in using special attributes like the clustering coefficient and the characteristic path length. In this paper we investigate the use of a distributed Cooperative Coevolutionary Genetic Algorithm (CCGA) and compare its performance to a generational and a steady state genetic algorithm (genGa and ssGA) for optimizing one instance of this topology control problem and present initial evidence of its ca- |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.scs-europe.net/conf/ecms2007/ecms2007-cd/ecms2007/ecms2007%20pdf/hpc_PGC-01.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
