Reliable workflow scheduling with less resource redundancy
Parallel Computing
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The distributed system made the large-scale scientific computing possible in a cost effective way. And the hardware resources in such systems are also getting much cheaper than years before. However, the problem of executing the job using minimum resources is still reasonable and important, especially for the cloud environment, who has to save energy and control cost. Unfortunately, only a few existing scheduling algorithms have taken into account the resource usage issue. In this study, with considering the realistic network topology and communication model, we firstly propose the Deadline, Reliability, Resources-aware (DRR) scheduling algorithm. The theory analysis fully demonstrate that, the output schedule of our algorithm can satisfy the user's requirement on reliability and deadline. Through the experiments, with setting the deadline less than the make span of the MaxRe algorithm's output schedule, we find that our algorithm can complete the job under this deadline. Besides, our algorithm can save almost 50% computation resources and 70% communication resources than FTSA (bl) and FTSA (tl+bl) algorithms.