Probabilistic Availability based Task Scheduling Algorithm

In high performance computing environment such as grids and clouds, resource availability is highly dynamic, unpredictable and unreliable, due to various factors such as system load, system failure, available network bandwidth, network failure, introduction of new resources, contention among remote task and the local tasks of resources and so on. In such environments, the dynamic availability of resources can affect execution of parallel applications. Parallel applications modelled by Directed Acyclic Graphs (DAG) scheduled on a network of heterogeneous processors so as to minimize finish time is a known NP complete problem. The Heterogeneous Earliest Finish Time (HEFT) is a static task scheduling algorithm that assumes probability of resource availability is 100% whereas in real life situations the case is not true. The temporal availability of resources is to be considered in task scheduling decisions. We propose a new Probabilistic Availability based Task Scheduling Algorithm (PATSA) where tasks are scheduled not only based on earliest finish time of task but also on resource availability probability so as to minimize makespan. Our algorithm was compared with existing HEFT algorithm for a certain set of random DAGs based on performance metrics such as Makespan, Schedule Length Ratio and Speedup.