  In this paper I investigate several offline and online data transfer
scheduling problems and propose efficient algorithms and techniques for
addressing them. In the offline case, I 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). I then consider 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 I
propose an algorithmic framework based on the block partitioning method, which
can speed up the process of resource allocation and reservation.
