GreedEx—a scalable clearing mechanism for utility computing

Scheduling becomes key in dynamic and heterogeneous utility computing settings. Market-based scheduling offers to increase efficiency of the resource allocation and provides incentives to offer computer resources and services. Current market mechanisms, however, are inefficient and computationally intractable in large-scale settings. The contribution of this paper is the proposal as well as analytical and numerical evaluation of GreedEx , an exchange for clearing utility computing markets, based on a greedy heuristic, that does achieve a distinct trade-off: GreedEx obtains fast and near-optimal resource allocations while generating prices that are truthful on the demand-side and approximately truthful on the supply-side.