Autonomic service hosting for large-scale distributed MOVE-services

Massively Online Virtual Environments (MOVEs) have been gaining popularity for several years. Today, these complex networked applications are serving thousands of clients simultaneously. However, these MOVEs are typically hosted on specialized server clusters and rely on internal knowledge of the services to optimize the load balancing. This makes running MOVEs an expensive undertaking as it cannot be outsourced to third party hosting providers. This paper details two Integer Linear Programming approaches to optimize the MOVE deployment through load balancing and minimizing the delay experienced by the end-users. Optimization includes assigning MOVE components to resources and replication of components to increase the scalability. One approach assuming full application knowledge of a dedicated MOVE and one with no internal knowledge and geared toward a generic MOVE hosting platform. For both cases an optimizing heuristic is evaluated and the obtained results are compared.