Adaptive Management of Shared Resource Pools with Decentralized Optimization and Epidemics

Abstract

Shared resource pools are facilities featuring a certain amount of resources which can be used by different applications. For managing resources in such pools, the demand of each application can be used. Such a demand, however, is driven by the workload, which varies over time. For that reason, adaptive approaches have been proposed for the management of shared resources pools. Whereas a number of solutions exist in this context, they are either not truly decentralized or do not apply to the problem we are dealing with. In this paper, we then present Darma, an approach for managing shared resource pools in a truly decentralized, adaptive, and optimal way.