Parallel Mapping with Time Optimization for SLA-Aware Compositional Services in the Business Grid

Service Level Agreements (SLAs) are currently one of the major research topics in Grid computing. Among many system components for supporting of SLA-aware Grid jobs, the SLA mapping module holds an important position and the capability of the mapping module depends on the runtime of the mapping algorithm. With the previously proposed algorithm to optimize the execution time of the workflow, the mapping module may develop into the bottleneck of the system if many requests come in during a short period of time. This paper presents a parallel mapping algorithm to optimize the execution time of the workflow, which can reduce the runtime of the mapping algorithm without reducing the quality of the mapping solutions. Performance measurements thereby deliver evaluation results showing the quality of the method. The speedup of the algorithms and the quality of the solutions are significantly improved when using eight CPUs comparing to using one CPU.