A simple index rule for efficient traffic splitting over parallel wireless networks with partial information
Multi-path communication solutions provide a promising means to improve the network performance in areas covered by multiple wireless access networks. Today, little is known about how to effectively exploit this potential. We study a model where flows are transferred over multiple parallel networks, each of which is modeled as a processor sharing node. The goal is to minimize the expected transfer time of elastic data traffic by smartly dispatching the flows to the networks, based on partial information about the numbers of foreground and background flows in each of the nodes. In the case of full state information, the optimal policy can be derived via standard MDP-techniques, but for models with partial information an optimal solution is hard to obtain. An important requirement is that the splitting algorithm is efficient, yet simple, easy-to-implement, scalable in the number of parallel networks and robust against changes in the parameter settings. We propose a simple index rule for splitting traffic streams based on partial information, and benchmark the results against the optimal solution in the case of full state information. Extensive simulations with real networks show that this method performs extremely well under practical circumstances for a wide range of realistic parameter settings.
traffic splitting processor sharing concurrent access flow-level performance partial information model heuristic