Genetic Algorithm in Resource Provider Selection for Personal Live Content Delivery in User-Provided Platform

Providing the personal live content delivery service using end user provided network resource is useful in many application situations due to its fast deployment. Together with service level agreement, the platform has to acquire sufficient network resources. Such resource acquisition can be realized by remuneration schemes for resource providers. From the perspective of service operators, selecting providers that effectively fulfilling SLA and efficiently reducing costs are their primary goals. We illustrate the feasibility of deploying Genetic Algorithms in searching resource providers economically. Our simulations showed that the effectiveness in satisfying the commitment on the resource provision stated in SLA and minimizing the related costs is highly related to its coding method and sensitive to the penalty factor. We find that the systematic choice of binary coding can improve the effectiveness of cost optimization in GA-based resource search.