The explosive growth of demands on big data processing imposes a heavy burden on computation, storage, and communication in data centers, which hence incurs considerable operational expenditure to data center providers. Therefore, cost minimization has become an emergent issue for the upcoming big data era. As a result, three factors, i.e., task assignment, data placement, and data movement, deeply in the operational expenditure of data centers. In this paper, the cost minimization problem via a joint optimization of these three factors for big data services in geo-distributed data centers considered. To describe the task completion time with the consideration of both data transmission and computation, to propose a 2-D Markov chain and derive the average task completion time in closed-form.
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