Creation and analysis of a JavaSpace-based genetic algorithm

The island model for distributed genetic algorithms (GAs) is a natural match for the master-worker paradigm in distributed computation. We explore the benefits and drawbacks of several distributed system architectures in developing an implementation of a distributed GA that exploits the Jini and JavaSpace technologies. Our results, using the knapsack problem as an illustration, show that there is an unavoidable price to pay in terms of decreasing computation-to-communication ratios as a function of instance size. However, we can diminish these effects by expanding the number of JavaSpaces beyond those required for the obvious implementation. Our results also indicate that as the number of remote machines increases the potential for a better solution also rises. Even though our distributed GAs did not always exploit this potential for a higher quality solution, we believe that the combination of Java, Jini, and JavaSpaces presents avenues for easily distributing the computation of genetic algorithms.