Optimal precomputation for mapping service level agreements in grid computing

A complicated task running on the grid system is usually made up of many services, each of which typically offers a better service quality at a higher cost. Mapping service level agreements (SLAs) optimally is to find the most appropriate quality level for each service such that the overall SLA of a task is achieved at the minimum cost. This paper considers mapping the execution time SLA in the case of the discrete cost function, which is an NP-hard problem. Due to the high computation of mapping SLAs, we propose a precomputation scheme that makes the selection of each individual service level in advance for every possible SLA requirement, which can reduce the request response time greatly. We use a (1+ε)(1+ε)-approximation method, whose solution for any time bound is at most (1+ε)(1+ε) times of the optimal cost. Simulation results demonstrate the superiority of our method compared with others.