A Dynamic Task Allocation Algorithm Based on Weighted Velocity

Volunteer computing is a way of supporting people around the world who provide free computer resources, to participate in scientific calculation or data analysis on the Internet. This provides an effective solution to solve the problems of large scale of basic scientific computing and more computing resources requirements. Task allocation is a very important part of volunteer computing. An effective algorithm can significantly improve computational efficiency. At present, most of the existing tasks are divided in term of the computer hardware conditions or the initial state of the computer in the volunteer computing. It seems that this have no obvious impact to calculating efficiency in a short time, but this task will be less flexible when idle resources of the volunteer computing becomes less or more. To make full use of idle computer resources, a dynamic task allocation algorithm (TAA) based on weighted velocity was proposed in this work. The research results showed that the weighted velocity as a parameter can be used to test the computing performance of a computer, dynamically manage task allocation as well. Keywords: volunteer computing, task allocation, weighted average velocit

Robust task scheduling for volunteer computing systems

Performance perturbations are a natural phenomenon in volunteer computing systems. Scheduling parallel applications with precedence-constraints is emerging as a new challenge in these systems. In this paper, we propose two novel robust task scheduling heuristics, which identify best task-resource matches in terms of makespan and robustness. Our approach for both heuristics is based on a proactive reallocation (or schedule expansion) scheme enabling output schedules to tolerate a certain degree of performance degradation. Schedules are initially generated by focusing on their makespan. These schedules are scrutinized for possible rescheduling using additional volunteer computing resources to increase their robustness. Specifically, their robustness is improved by maximizing either the total allowable delay time or the minimum relative allowable delay time over all allocated volunteer resources. Allowable delay times may occur due to precedence constraints. In this paper, two proposed heuristics are evaluated with an extensive set of simulations. Based on simulation results, our approach significantly contributes to improving the robustness of the resulting schedules.19 page(s