Adaptive workload distribution for local and remote clouds

Abstract

Cloud systems include both locally based servers at user premises and remote servers and multiple Clouds that can be reached over the Internet. This paper describes a smart distributed system that combines local and remote Cloud facilities. It operates with a task allocation system that takes decisions to allocate tasks dynamically to the service that offers the best overall Quality of Service and a routing overlay which optimizes network delay for data transfer between clouds. Internet-scale experiments exhibit the effectiveness of our approach in adaptively distributing workload across multiple clouds.