  The paper investigates theoretical issues in applying the universal swarming
technique to efficient content distribution. In a swarming session, a file is
distributed to all the receivers by having all the nodes in the session
exchange file chunks. By universal swarming, not only all the nodes in the
session, but also some nodes outside the session may participate in the chunk
exchange to improve the distribution performance. We present a universal
swarming model where the chunks are distributed along different Steiner trees
rooted at the source and covering all the receivers. We assume chunks arrive
dynamically at the sources and focus on finding stable universal swarming
algorithms. To achieve the throughput region, universal swarming usually
involves a tree-selection subproblem of finding a min-cost Steiner tree, which
is NP-hard. We propose a universal swarming scheme that employs an approximate
tree-selection algorithm. We show that it achieves network stability for a
reduced throughput region, where the reduction ratio is no more than the
approximation ratio of the tree-selection algorithm. We propose a second
universal swarming scheme that employs a randomized tree-selection algorithm.
It achieves the throughput region, but with a weaker stability result. The
proposed schemes and their variants are expected to be useful for
infrastructure-based content distribution networks with massive content and
relatively stable network environment.
