Mapping SLA-based workflows onto Grid resources with parallel processing technology

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 mapping algorithms, the mapping module may develop into the bottleneck of the system if many requests come in during a short period of time. Besides that, the mapping module may also miss some high quality mapping solutions. This Chapter presents parallel mapping algorithms, which can either reduce the runtime of the mapping algorithms without reducing the quality of the mapping solutions or increase the quality of the mapping solutions without increasing the runtime of the mapping algorithms. 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 8 CPUs comparing to using 1 CPU.