Congestion-Aware Scalable Video Streaming

Postprin

Q-AIMD: A Congestion Aware Video Quality Control Mechanism

Following the constant increase of the multimedia traffic, it seems necessary to allow transport protocols to be aware of the video quality of the transmitted flows rather than the throughput. This paper proposes a novel transport mechanism adapted to video flows. Our proposal, called Q-AIMD for video quality AIMD (Additive Increase Multiplicative Decrease), enables fairness in video quality while transmitting multiple video flows. Targeting video quality fairness allows improving the overall video quality for all transmitted flows, especially when the transmitted videos provide various types of content with different spatial resolutions. In addition, Q-AIMD mitigates the occurrence of network congestion events, and dissolves the congestion whenever it occurs by decreasing the video quality and hence the bitrate. Using different video quality metrics, Q-AIMD is evaluated with different video contents and spatial resolutions. Simulation results show that Q-AIMD allows an improved overall video quality among the multiple transmitted video flows compared to a throughput-based congestion control by decreasing significantly the quality discrepancy between them

Application-Level QoS: Improving video conferencing quality through sending the best packet next

In a traditional network stack, data from an application is transmitted in the order that it is received. An algorithm is proposed where information about the priority of packets and expiry times is used by the transport layer to reorder or discard packets at the time of transmission to optimise the use of available bandwidth. This can be used for video conferencing to prioritise important data. This scheme is implemented and compared to unmodified datagram congestion control protocol (DCCP). This algorithm is implemented as an interface to DCCP and tested using traffic modelled on video conferencing software. The results show improvement can be made to video conferencing during periods of congestion - substantially more audio packets arrive on time with the algorithm, which leads to higher quality video conferencing. In many cases video packet arrival rate also increases and adopting the algorithm gives improvements to video conferencing that are better than using unmodified queuing for DCCP. The algorithm proposed is implemented on the server only, so benefits can be obtained on the client without changes being required to the client

Adaptive Multicast of Multi-Layered Video: Rate-Based and Credit-Based Approaches

Network architectures that can efficiently transport high quality, multicast video are rapidly becoming a basic requirement of emerging multimedia applications. The main problem complicating multicast video transport is variation in network bandwidth constraints. An attractive solution to this problem is to use an adaptive, multi-layered video encoding mechanism. In this paper, we consider two such mechanisms for the support of video multicast; one is a rate-based mechanism that relies on explicit rate congestion feedback from the network, and the other is a credit-based mechanism that relies on hop-by-hop congestion feedback. The responsiveness, bandwidth utilization, scalability and fairness of the two mechanisms are evaluated through simulations. Results suggest that while the two mechanisms exhibit performance trade-offs, both are capable of providing a high quality video service in the presence of varying bandwidth constraints.Comment: 11 page

Effective video multicast over wireless internet

With the rapid growth of wireless networks and great success of Internet video, wireless video services are expected to be widely deployed in the near future. As different types of wireless networks are converging into all IP networks, i.e., the Internet, it is important to study video delivery over the wireless Internet. This paper proposes a novel end-system based adaptation protocol calledWireless Hybrid Adaptation Layered Multicast (WHALM) protocol for layered video multicast over wireless Internet. In WHALM the sender dynamically collects bandwidth distribution from the receivers and uses an optimal layer rate allocation mechanism to reduce the mismatches between the coarse-grained layer subscription levels and the heterogeneous and dynamic rate requirements from the receivers, thus maximizing the degree of satisfaction of all the receivers in a multicast session. Based on sampling theory and theory of probability, we reduce the required number of bandwidth feedbacks to a reasonable degree and use a scalable feedback mechanism to control the feedback process practically. WHALM is also tuned to perform well in wireless networks by integrating an end-to-end loss differentiation algorithm (LDA) to differentiate error losses from congestion losses at the receiver side. With a series of simulation experiments over NS platform, WHALM has been proved to be able to greatly improve the degree of satisfaction of all the receivers while avoiding congestion collapse on the wireless Internet

eCMT-SCTP: Improving Performance of Multipath SCTP with Erasure Coding Over Lossy Links

Performance of transport protocols on lossy links is a well-researched topic, however there are only a few proposals making use of the opportunities of erasure coding within the multipath transport protocol context. In this paper, we investigate performance improvements of multipath CMT-SCTP with the novel integration of the on-the-fly erasure code within congestion control and reliability mechanisms. Our contributions include: integration of transport protocol and erasure codes with regards to congestion control; proposal for a variable retransmission delay parameter (aRTX) adjustment; performance evaluation of CMT-SCTP with erasure coding with simulations. We have implemented the explicit congestion notification (ECN) and erasure coding schemes in NS-2, evaluated and demonstrated results of improvement both for application goodput and decline of spurious retransmission. Our results show that we can achieve from 10% to 80% improvements in goodput under lossy network conditions without a significant penalty and minimal overhead due to the encoding-decoding process