Multi economic agent interaction for optimizing the aggregate utility of grid users in computational grid

摘要

This paper investigates the interactions between agents representing grid users and the providers of grid resources to maximize the aggregate utilities of all grid users in computational grid. It proposes a price-based resource allocation model to achieve maximized utility of grid users and providers in computational grid. Existing distributed resource allocation schemes assume the resource provider to be capable of measuring user's resource demand, calculating and communicating price, none of which actually exists in reality. This paper addresses these challenges as follows. First, the grid user utility is defined as a function of the grid user's the resource units allocated. We formalize resource allocation using nonlinear optimization theory, which incorporates both grid resource capacity constraint and the job complete times. An optimal solution maximizes the aggregate utilities of all grid users. Second, this paper proposes a new optimization-based grid resource pricing algorithm for allocating resources to grid users while maximizing the revenue of grid providers. Simulation results show that our proposed algorithm is more efficient than compared allocation scheme.