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In this paper, the author investigates several offline and online data transfer scheduling problems and propose efficient algorithms and techniques for addressing them. In the offline case, he present a novel, heuristic, algorithm for scheduling files with divisible sizes on multiple disjoint paths, in order to maximize the total profit (the problem is equivalent to the multiple knapsack problem with divisible item sizes). The author then considers a cost optimization problem for transferring a sequence of identical files, subject to time constraints imposed by the data transfer providers. For the online case he proposes an algorithmic framework based on the block partitioning method, which can speed up the process of resource allocation and reservation.
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