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The aim of this paper is to propose a scheduling method to consider reliability along with makespan in grid computing systems. The reliability of task execution is considered in the proposed method to increase the chance of running large-scale and computationally intensive workflows successfully. To handle situations in which a resource failure in a possible scheduling solution occurs, the proposed method finds a collection of scheduling solutions instead of only one solution to run the workflow. It leads to have chance to run an alternative scheduling solution that is not using the failed resource. To find the most optimized scheduling solutions, we exploit the lately developed... 

This paper addresses scheduling problem of independent tasks in the market-based grid environment. In market-based grids, resource providers can charge users based on the amount of resource requested by them. In this case, scheduling algorithms should consider users' willingness to execute their applications in most economical manner. As a solution to this problem, a hybrid genetic algorithm and variable neighborhood search is presented to reduce overall cost of task executions without noticeable increment in system makespan. Simulation results show that our algorithm performs much better than other algorithms in terms of cost of task executions. Considering the negative correlation between...