Volunteer computing (VC) is a distributed computing paradigm, which provides\nunlimited computing resources in the form of donated idle resources for many large-scale scientific\ncomputing applications. Task scheduling is one of the most challenging problems in VC. Although,\ndynamic scheduling problem with deadline constraint has been extensively studied in prior studies\nin the heterogeneous system, such as cloud computing and clusters, these algorithms canâ??t be fully\napplied to VC. This is because volunteer nodes can get offline whenever they want without taking\nany responsibility, which is different from other distributed computing. For this situation, this paper\nproposes a dynamic task scheduling algorithm for heterogeneous VC with deadline constraint,\ncalled deadline preference dispatch scheduling (DPDS). The DPDS algorithm selects tasks with the\nnearest deadline each time and assigns them to volunteer nodes (VN), which solves the dynamic\ntask scheduling problem with deadline constraint. To make full use of resources and maximize the\nnumber of completed tasks before the deadline constraint, on the basis of the DPDS algorithm,\nimproved dispatch constraint scheduling (IDCS) is further proposed. To verify our algorithms, we\nconducted experiments, and the results show that the proposed algorithms can effectively solve the\ndynamic task assignment problem with deadline constraint in VC.
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