Scalable, Low complexity, and fast greedy scheduling heuristics for highly heterogeneous distributed computing systems

Forheterogeneousdistributedcomputingsystems,importantdesignissues are scalability and system optimization. Given such systems, it is crucial to develop low computational complexity algorithms to schedule tasks in a manner that exploits the heterogeneity of the resources and applications. In this paper, we report and evalu- ate three scalable, and fast scheduling heuristics for highly heterogeneous distributed computing systems. We conduct a comprehensive performance evaluation study us- ing simulation. The benchmarking outlines the performance of the schedulers, rep- resenting scalability, makespan, flowtime, computational complexity, and memory utilization. The set of experimental results shows that our heuristics perform as good as the traditional approaches, for makespan and flowtime, while featuring lower com- plexity, lower running time, and lower used memory. The experimental results also detail the various scenarios under which certain algorithms excel and fail.