Computational Resource Exchanges for Distributed Resource Allocation

Appropriate abstractions, mechanisms, and policies for resource allocation is quickly emerging as the fundamental problem facing emerging computation and communication environments such as PlanetLab and the Grid. This paper explores the utility of one simple abstraction for global resource allocation with a number of appealing properties: a centralized auction that collects user descriptions of resource configurations and the values placed on these configurations. The task of the clearinghouse is to determine a set of winning bids and to assign appropriate subsets of global resources to individual users. One challenge with this model is the computational complexity associated with determining winners. To make the problem tractable, we propose appropriate bidding languages that constrain the type of bids that users can make, while maintaining required expressiveness. Computing optimal solutions to such auctions for scales of current interest (e.g., 1000 nodes) is intractable on current hardware, even given aggressive optimizations. Thus, we introduce a number of heuristics that appear to perform well in practice. Another challenge with auctions is the lag in clearing the auction and the uncertainty in whether resources will actually be acquired. We introduce a formulation for “Buy it Now” pricing to address some of these limitations.