Load Balancing Video Clients in Enterprise Wireless Networks

Given the increasing popularity of real-time video communication over enterprise wireless networks, ensuring good quality of experience is becoming critical. A common problem in such networks is that the clients typically adopt the strategy of associating to the access point with the highest signal strength, which can lead to load imbalance, unfair throughput allocation, and low overall video quality. In this paper, we propose to improve load balancing across video clients by selectively triggering directed roams of chosen clients, while explicitly accounting for the cost of roaming. We formulate the problem of identifying the directed roams to perform as an optimization problem where the objective function reflects both the overall utility of all video clients and the cost due to roaming. We subsequently apply relaxations to the original NP-Hard problem, and propose a three-stage algorithm that efficiently computes an approximate solution. Simulations show that by selectively roaming just 5% of the clients, we increase throughput relative to an initial strongest signal based association by at least 10% for over half of the clients and by at least 20% for over a quarter of the clients. We also increase aggregate throughput, improve fairness and thereby increase the overall video quality.

Media-Specific Rate Allocation in Multipath Networks

Pascal Frossard, Dan Jurca

We address the problem of joint path selection and rate allocation in multipath streaming in order to optimize a media specific quality of service. An optimization problem is proposed, which aims at minimizing a video distortion metric based on sequence-dependent parameters, and transmission channel characteristics, for a given network infrastructure. Even if in general, optimal path selection and rate allocation is an NP complete problem, an in-depth analysis of the media distortion evolution allows to define a low complexity algorithm for an optimal streaming strategy. In particular, we show that a greedy allocation of rate along paths with increasing error probability leads to an optimal solution. We argue that a network path shall not be chosen for transmission, unless all other available paths with lower error probability have been chosen. Moreover, the chosen paths should be used at their maximum available end-to-end bandwidth. Simulation results show that the optimal rate allocation carefully trades off total encoding/transmission rate, with the end-to-end transmission error probability and the number of chosen paths. In many cases, the optimal rate allocation provides more than 20% improvement in received video quality, compared to heuristic-based algorithms. This motivates its use in multipath networks, where it optimizes media specific quality of service, and simultaneously saves network resources, with very low computational complexity.

2005

Media-specific rate allocation in heterogeneous wireless networks

Pascal Frossard, Dan Jurca

We address the problem of joint path selection and rate allocation in multipath wireless streaming, in order to optimize a media specific quality of service. We leverage on the existence of multiple parallel wireless services, in order to enhance the received video quality at a wireless client. An optimization problem is proposed, aimed at minimizing a video distortion metric based on sequence-dependent parameters, and transmission channel characteristics, for a given wireless network infrastructure. Even if joint optimal path selection and rate allocation is in general an NP complete problem, an in-depth analysis of the media distortion evolution allows defining a low complexity optimal streaming strategy, under reasonable network assumptions. In particular, we show that a greedy allocation of rates along paths with increasing error probability leads to an optimal solution. We argue that a network path should not be chosen for transmission, unless all other available paths with lower error probability have been chosen. Moreover, the chosen paths should be used at their maximum end-to-end bandwidth. These results are demonstrated for both independent network paths, and non-disjoint channel segments, in generic network topologies. Simulation results showed that the optimal rate allocation carefully trades off total encoding/transmission rate, with the end-to-end transmission error probability and the number of chosen paths. In many cases, the optimal rate allocation provides more than 20% improvement in received video quality, compared to heuristic-based algorithms.

2006

Packet Selection and Scheduling for Multipath Video Streaming

Pascal Frossard, Dan Jurca

This paper addresses the problem of choosing the best streaming policy for distortion optimal multipath video delivery, under delay constraints. The streaming policy consists in a joint selection of the video packets to be transmitted, as well as their sending time, and the transmission path. A simple streaming model is introduced, which takes into account the video packet importance, and the dependencies among packets, and allows to compute the quality perceived by the receiver, as a function of the streaming policy. We derive an optimization problem based on the video abstraction model, under the assumption that the server knows, or can predict the state of the network. A detailed analysis of the timing constraints in multipath video streaming provides helpful insights that lead to an efficient algorithm to solve the NP-hard streaming policy optimization problem. We eventually propose a fast heuristic-based algorithm, that still provides close to optimal performance. Thanks to its limited complexity, this novel algorithm is finally demonstrated in live streaming scenarios, where it only induces a negligible distortion penalty compared to an optimal strategy. Simulation results finally show that the proposed scheduling solutions perform better than common scheduling algorithms, and represent very efficient multipath streaming strategies for both stored and live video services.

2004