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Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this paper, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g., response time) are assured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided inadequate solutions that achieve both objectives at the same time.
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