Danjue Li

BASS: BitTorrent Assisted Streaming System for Video-on-Demand

This paper introduces a hybrid server/P2P streaming system called bittorrent-assisted streaming system (BASS) for large-scale video-on-demand (VoD) services. By distributing the load among P2P connections as well as maintaining active server connections, BASS can increase the system scalability while decreasing media playout wait times. To analyze the benefits of BASS, we examine torrent trace data collected in the first week of distribution for Fedora Core 3 and develop an empirical model of bittorrent client performance. Based on this, we run trace-based simulations to evaluate BASS and show that it is more scalable than current unicast solutions and can greatly decrease the average waiting time before playback

Cooperative Peer-to-Peer Repair for Wireless Multimedia Broadcast

This paper explores how to leverage IEEE802.11-based cooperative peer-to-peer repair (CPR) to enhance the reliability of wireless multimedia broadcasting. We first formulate the CPR problem and present an algorithm that assumes global state information to optimally schedule CPR transmissions. Based on insights gained from the optimal algorithm, we propose a fully distributed CPR (DCPR) protocol. Simulation results demonstrate that the DCPR protocol can effectively enhance the reliability of wireless broadcast services with a repair latency comparable to that of optimal scheduling.

Multi-source multi-path video streaming over wireless mesh networks

This paper proposes to leverage multi-source multi-path diversity to design a video streaming system for supporting concurrent video-on-demand (VoD) services over wireless mesh networks (WMNs). By integrating a wireless interference model into consideration, we have a more realistic network model to capture the characteristics of wireless networks. Based on that, we mathematically formulate the route selection problem for the proposed streaming system using rate/interference-distortion optimization framework, and rely on a genetic algorithm to solve it heuristically. Simulation results show that the proposed system has better performance than systems using single-source, single-path and systems that do not consider interference

MUVIS: Multi-source video streaming service over WLANs

Video streaming over wireless networks is challenging due to node mobility and high channel error rate. In this paper, we propose a multi-source video streaming (MUVIS) system to support high quality video streaming service over IEEE 802.11-based wireless networks. We begin by collocating a streaming proxy with the wireless access point to help leverage both the media server and peers in the WLAN. By tracking the peer mobility patterns and performing content discovery among peers, we construct a multi-source sender group and stream video using a rate-distortion optimized scheme. We formulate such a multi-source streaming scenario as a combinatorial packet scheduling problem and introduce the concept of asynchronous clocks to decouple the problem into three steps. First, we decide the membership of the multi-source sender group based on the mobility pattern tracking, available video content in each peer and the bandwidth each peer allocates to the multi-source streaming service. Then, we select one sender from the sender group in each optimization instance using asynchronous clocks. Finally, we apply the point-to-point rate-distortion optimization framework between the selected sender-receiver pair. In addition, we implement two different caching strategies, simple caching simple fetching (SCSF) and distortion minimized smart caching (DMSC), in the proxy to investigate the effect of caching on the streaming performance. To design more realistic simulation models, we use the empirical results from corporate wireless networks to generate node mobility. Simulation results show that our proposed multi-source streaming scheme has better performance than the traditional server-only streaming scheme and that proxy-based caching can potentially improve video streaming performance.

On the complexity of cooperative peer-to-peer repair for wireless broadcasting

The well-known NAK implosion problem for wireless broadcast can be addressed by leveraging cooperative peer-to-peer connectivity to repair corrupted data. This paper studies the cooperative peer-to-peer repair (CPR) framework for multimedia broadcast. We show that CPR can be formulated as an optimization problem that minimizes the number of iterations it takes to wirelessly disseminate a desired message from peers with the content to peers without it. Complicating the problem are transmission conflicts, where pre-specified sets of links cannot simultaneously transmit due to interference. In this paper, we formalize the CPR minimum delay problem and prove that it is NP-hard

Joint server/peer receiver-driven rate-distortion optimized video streaming using asynchronous clocks

This paper proposes a joint server/peer video streaming architecture for wireless networks, where a receiver can access a video server via an access point using the infrastructure mode and at the same lime communicate with its peers using the ad hoc mode of its IEEE 802.11 interface card. We introduce a joint infrastructure/peer-to-peer, receiver-driven streaming scheme, and formulate it as a combinatorial optimization problem. We decouple the problem into two steps: first selecting the sender (server or peer) by introducing asynchronous clocks, and then applying point-to-point rate-distortion optimization algorithm between a specific sender-receiver pair. Simulation results show that our joint approach has better performance than those systems with single server or with round-robin selection scheme.

Optimizing video streaming against transient failures and routing instability

In addition to network congestion, a link/node failure is another major cause of performance degradation for video streaming over the Internet. Such failures may be followed by a long routing instability period, during which packets can be black-holed due to invalid paths or caught in routing loops. This paper proposes a routing proxy approach to improve media streaming adaptation against both link/node failures and network congestion. In particular, we first argue that it is important to distinguish between network performance degradation due to network congestion versus link/node failures, and then model link/node failures using empirical models derived from measurements. We then show how by means of proper congestion control, such timely notifications from the network layer can be exploited at the streaming server to improve the performance of a rate-adaptive automatic retransmission request (ARQ) video streaming scheme. Simulation results show that a rate-adaptive streaming scheme using feedbacks from our proposed proxy can recover much faster from link/node failures than a scheme without such feedbacks.

Energy-Aware Multi-Source Video Streaming

In a multi-source video streaming system, premature draining of low-power nodes can cause sudden failures of peer connections and degrade streaming performance. To solve this problem, we propose an energy-aware scheduling (EAS) scheme to better distribute the streaming load among different peers by jointly considering network conditions and node energy levels. We model the proposed scheme using a rate/energy-distortion optimization framework and heuristically solve it using the concept of asynchronous clocks. Simulation studies show that the proposed EAS scheme can achieve comparable streaming quality while consuming less energy