Joint Network Resource and Service Optimization in Distributed Computing Networks

Abstract

To support elastic services with flexible processing configurations in distributed computing networks, we propose a joint network resource and service control policy that optimizes routing, scheduling, processing locations, and the selection of processing configurations. The flexibility of service configurations introduces a new degree of freedom for improving network performance. First, we formulate the maximum elastic service flow problem and develop a polynomial-time algorithm to compute the network’s maximum throughput for supporting elastic services that can be processed by any available chain of service functions. Under stochastic service arrivals, we design a dynamic control policy that, upon each service arrival, chooses the service configuration, processing locations, and routing. In addition, we develop a scheduling policy to maximize network throughput. Furthermore, we extend the policy to maximize network utility by assigning a utility value to each service configuration. We prove that this utility maximization policy achieves an expected total network utility that is near-optimal.