Object Distribution with Local Information

We investigate the problem of distributing communicating objects across wide-area environments. Our goals are to balance load, minimize network communication, and use resources efficiently. However, applications running in such environments are often dynamic and highly unpredictable. Furthermore, synchronous communication is usually too expensive to be used in disseminating load information. We therefore investigate policies that use local information to approximate desired global behaviors. Our results with Java applications show that simple, local approaches are surprisingly effective in capturing load information and object relationships, and in making migration and clustering decisions based on profiled information.