Measurement-based Efficient Resource Allocation with Demand-Side Adjustments

The problem of efficient resource allocation has drawn significant attention in many scientific disciplines due to its direct societal benefits, such as energy savings. Traditional approaches in addressing online resource allocation problems neglect the potential benefit of feedback information available from the running tasks/loads as well as the potential flexibility of a task to adjust its operation/service level in order to increase efficiency. The present paper builds upon recent developments in the area of bandwidth allocation in computing systems and proposes a unified design approach for efficient resource allocation which is based upon a measurement- or utility-based learning scheme. We demonstrate through analysis the potential of the proposed scheme in providing efficient allocation of resources in a large class of resource allocation problems and when only measurements of the performances of the tasks are available.