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In traditional massive content distribution with multiple sessions, thesessions form separate overlay networks and operate independently, where somesessions may suffer from insufficient resources even though other sessions haveexcessive resources. To cope with this problem, we consider the universalswarming approach, which allows multiple sessions to cooperate with each other.We formulate the problem of finding the optimal resource allocation to maximizethe sum of the session utilities and present a subgradient algorithm whichconverges to the optimal solution in the time-average sense. The solutioninvolves an NP-hard subproblem of finding a minimum-cost Steiner tree. We copewith this difficulty by using a column generation method, which reduces thenumber of Steiner-tree computations. Furthermore, we allow the use ofapproximate solutions to the Steiner-tree subproblem. We show that theapproximation ratio to the overall problem turns out to be no less than thereciprocal of the approximation ratio to the Steiner-tree subproblem.Simulation results demonstrate that universal swarming improves the performanceof resource-poor sessions with negligible impact to resource-rich sessions. Theproposed approach and algorithm are expected to be useful forinfrastructure-based content distribution networks with long-lasting sessionsand relatively stable network environment.

Content Distribution by Multiple Multicast Trees and Intersession Cooperation: Optimal Algorithms and Approximations