The complexity of Markov decision processes
Mathematics of Operations Research
A Survey of solution techniques for the partially observed Markov decision process
Annals of Operations Research
A survey of algorithmic methods for partially observed Markov decision processes
Annals of Operations Research
Optimal adaptive policies for Markov decision processes
Mathematics of Operations Research
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
On the Effect of Large-Scale Deployment of Parallel Downloading
WIAPP '03 Proceedings of the The Third IEEE Workshop on Internet Applications
Exact and approximate algorithms for partially observable markov decision processes
Exact and approximate algorithms for partially observable markov decision processes
Planning and control in stochastic domains with imperfect information
Planning and control in stochastic domains with imperfect information
On processor sharing and its applications to cellular data network provisioning
Performance Evaluation
Deployable multipath communication scheme with sufficient performance data distribution method
Computer Communications
Guest Editorial: Concurrent multipath transport
Computer Communications
Approximating optimal policies for partially observable stochastic domains
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Effective load for flow-level performance modelling of file transfers in wireless LANs
Computer Communications
A heuristic variable grid solution method for POMDPs
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Region-based approximations for planning in stochastic domains
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Fundamental limitations on increasing data rate in wireless systems
IEEE Communications Magazine
IEEE Communications Magazine
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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.