Implementation of Layered Server-Client Model for Asynchronous Parallel Distributed GA

K. Kojima and M. Ishigame (Japan)


Genetic Algorithm, Asynchronous, Parallel Distributed GA, Layered, Server-Client Model, Load Distribution


In Parallel Distributed Genetic Algorithm (PDGA), many studies have been done by using Coarse-grained paral lelization. Among these studies, many researchers are using Synchronized Ring model (Stepping Stone model), Random Exchange model and Sigma Exchange model. However, the communication does not occur efficiently in Synchronized Ring model, it is difficult to implement in Random Exchange and Sigma Exchange, and it is diffi cult to coordinate a parameter in Sigma Exchange model. To solve these problems, we proposed a implementation method for Asynchronous PDGA by using Server-Client model. This model consists of a server program and some client programs. A client program executes GA indepen dently and a server manages the elites of clients. It is easy to implement this model and it is able to communicate asynchronously. But, in huge search space problems, this model needs a lot of client and high traffic loads to server. This paper introduces a implementation method of Layered Server-Client Model for Asynchronous PDGA. This model consists of a master server program, some server program and some client program managed by a server. This means that there is a master server program above some server programs and this system may dis tributes traffic load.

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