Network Information Flow in Network of Queues

Two classic categories of models exist for computer networks: network information flow and network of queues. The network information flow model appropriately captures the multi-hop flow routing nature in general network topologies, as well as encodable and replicable properties of information flows. However, it assumes nodes in the network to be infinitely powerful and therefore does not accurately model queueing delay and loss at nodes. The network of queues model instead focuses on finite capacitied nodes and studies buffering and loss behaviors from a stochastic perspective. However, existing models on network of queues are mostly based on unrealistically simple topologies, and lacks the multi-hop flow routing dimension. In this work, we seek to combine advantages from both models. We start with the network information flow model and replace each infinitely powerful node with afinitely capacitied queue system instead. We show that the optimal routing problems for unicast, multiple unicasts and multicast can all be formulated as convex optimization problems. As a necessary step in validating the model for multicast routing, we show that network coding does not change the memoryless nature of traffic. We examine the correctness of the models through simulations and show that they behave differently than traditional link-cost based network flow models.