Zhengye Liu
New York University
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Publication
Featured researches published by Zhengye Liu.
IEEE Transactions on Multimedia | 2009
Zhengye Liu; Yanming Shen; Keith W. Ross; Shivendra S. Panwar; Yao Wang
Although there are several successful commercial deployments of live P2P streaming systems, the current designs; lack incentives for users to contribute bandwidth resources; lack adaptation to aggregate bandwidth availability; and exhibit poor video quality when bandwidth availability falls below bandwidth supply. In this paper, we propose, prototype, deploy, and validate LayerP2P, a P2P live streaming system that addresses all three of these problems. LayerP2P combines layered video, mesh P2P distribution, and a tit-for-tat-like algorithm, in a manner such that a peer contributing more upload bandwidth receives more layers and consequently better video quality. We implement LayerP2P (including seeds, clients, trackers, and layered codecs), deploy the prototype in PlanetLab, and perform extensive experiments. We also examine a wide range of scenarios using trace-driven simulations. The results show that LayerP2P has high efficiency, provides differentiated service, adapts to bandwidth deficient scenarios, and provides protection against free-riders.
Proceedings of the 2007 workshop on Peer-to-peer streaming and IP-TV | 2007
Zhengye Liu; Yanming Shen; Shivendra S. Panwar; Keith W. Ross; Yao Wang
In this paper, we design a distributed incentive mechanism for mesh-pull P2P live streaming networks. In our system, a video is encoded into layers with lower layers having more importance. The system is heterogeneous with peers having different uplink bandwidths. We design a distributed protocol in which a peer contributing more uplink bandwidth receives more layers and consequently better video quality. Previous approaches consider single-layer video, where each peer receives the same video quality no matter how much bandwidth it contributes to the system. The simulation results show that our approach can provide differentiated video quality commensurate with a peers contribution to other peers, and can also discourage free-riders. Furthermore, we also compare our layered approach with a multiple description coding (MDC) approach, and conclude that the layered approach is more promising, primarily due to its higher coding efficiency.
international conference on network protocols | 2008
Zhengye Liu; Yanming Shen; Keith W. Ross; Shivendra S. Panwar; Yao Wang
We consider the design of an open P2P live-video streaming system. When designing a live video system that is both open and P2P, the system must include mechanisms that incentivize peers to contribute upload capacity. We advocate an incentive principle for live P2P streaming: a peerpsilas video quality is commensurate with its upload rate. We propose substream trading, a new P2P streaming design which not only enables differentiated video quality commensurate with a peerpsilas upload contribution but can also accommodate different video coding schemes, including single-layer coding, layered coding, and multiple description coding. Extensive trace-driven simulations show that substream trading has high efficiency, provides differentiated service, low start-up latency, synergies among peers with different Internet access rates, and protection against free-riders.
internet measurement conference | 2011
Yuan Ding; Yuan Du; Yingkai Hu; Zhengye Liu; Luqin Wang; Keith W. Ross; Anindya Ghose
YouTube uploaders are the central agents in the YouTube phenomenon. We conduct extensive measurement and analysis of YouTube uploaders. We estimate YouTube scale and examine the uploading behavior of YouTube users. We demonstrate the positive reinforcement between on-line social behavior and uploading behavior. Furthermore, we examine whether YouTube users are truly broadcasting themselves, via characterizing and classifying videos as either user generated or user copied.
international conference on multimedia and expo | 2007
Zhengye Liu; Yanming Shen; Shivendra S. Panwar; Keith W. Ross; Yao Wang
In this paper, we consider applying multiple description coding in mesh-pull P2P live streaming networks to provide incentives for redistribution. In our system, a video is encoded into multiple descriptions with each description having equal importance. We consider a heterogeneous system with peers having different uplink bandwidths. We design a distributed protocol in which a peer contributing more uplink bandwidth receives more descriptions and consequently better video quality. Previous approaches consider single-layer video, where each peer receives the same video quality no matter how much bandwidth it contributes to the system. The simulation results show that our approach can provide differentiated video quality commensurate with a peers contribution to other peers.
international conference on multimedia and expo | 2005
Yanming Shen; Zhengye Liu; Shivendra S. Panwar; Keith W. Ross; Yao Wang
Peer-to-peer video streaming has emerged as an important means to transport stored video. The peers are less costly and more scalable than an infrastructure-based video streaming network which deploys a dedicated set of servers to store and distribute videos to clients. In this paper, we investigate streaming layered encoded video using peers. Each video is encoded into hierarchical layers which are stored on different peers. The system serves a client request by streaming multiple layers of the requested video from separate peers. The system provides unequal error protection for different layers by varying the number of copies stored for each layer according to its importance. We evaluate the performance of our proposed system with different copy number allocation schemes through extensive simulations. Finally, we compare the performance of layered coding with multiple description coding.
international conference on distributed computing systems | 2010
Zhengye Liu; Prithula Dhungel; Di Wu; Chao Zhang; Keith W. Ross
Incentive mechanisms play a critical role in P2P systems. Private BitTorrent sites use a novel incentive paradigm, where the sites record upload and download amounts of users and require each user to maintain its upload-to-download ratio above a specified threshold. This paper explores in-depth incentives in private P2P file-sharing systems. Our contributions are threefold. We first conduct a measurement study on a representative private BitTorrent site, examining how incentives influence user behavior. Our measurement study shows that, as compared with public torrents, a private BitTorrent site provides more incentive for users to contribute and seed. Second, we develop a game theoretic model and analytically show that the ratio mechanism indeed provides effective incentives. But existing ratio incentives in private BitTorrent sites are vulnerable to collusions. Third, to prevent collusion, we propose an upload entropy scheme, and show through analysis and experiment that the entropy scheme successfully limits colluding, while rarely affecting normal users who do not collude.
international conference on multimedia and expo | 2006
Yanming Shen; Zhengye Liu; Shivendra S. Panwar; Keith W. Ross; Yao Wang
In this paper, we examine the prefetching strategies in a peer-driven video on-demand system. In our design, each video is encoded into multiple low bit-rate substreams and copies of the substreams are distributed to the participating peers. When a peer streams in a substream of rate r, it instead streams at rate rcirc, where r>rcirc. In this manner, if one of the peers suppliers disconnects, the client peer can tap the reservoir of prefetched bits while searching for a replacement server, thereby avoiding any glitches or reduced visual quality. We examine how to assign prefetching rates to each of substreams as a function of their importance. Our studies show that appropriate prefetching strategies can bring significant performance improvements for both multiple description and layered videos
Packet Video 2007 | 2007
Zhengye Liu; Yanming Shen; Shivendra S. Panwar; Keith W. Ross; Yao Wang
In a P2P VoD system, the rate at which peers receive video fluctuates due to peer churn. Although scalable video coding has the potential to adapt to long-term rate variations, existing scalable video schemes have not been tailored for P2P systems for which substreams emanate from churning peers. In this paper we propose a new multi-stream coding and transmission scheme, Redundancy-Free Multiple Description (RFMD) Coding and Transmission, that has been designed for P2P VoD systems. Unlike layered video, with RFMD all substreams have equal importance. Thus, video quality gracefully degrades as substreams are lost, independently of which particular substreams are lost. Furthermore, only the source bits are collectively transmitted by the supplying peers. Thus, all transmitted bits contribute to improve video quality. Finally, RFMD can be used to create any number of descriptions. We conduct an extensive simulation study, comparing single layer coding with highrate erasure codes, layered coding, multiple description coding (MD-FEC) and RFMD. The simulations show that RFMD performs best in a variety of representative scenarios.
international conference on peer-to-peer computing | 2012
Zhengye Liu; Yuan Ding; Yong Liu; Keith W. Ross
User Generated Content (UGC) video applications, such as YouTube, are enormously popular. UGC systems can potentially reduce their distribution costs by allowing peers to store and redistribute the videos that they have seen in the past. We study peer-assisted UGC from three perspectives. First, we undertake a measurement study of the peer-assisted distribution system of Tudou (a popular UGC network in China), revealing several fundamental characteristics that models need to take into account. Second, we develop analytical models for peer-assisted distribution of UGC. Our models capture essential aspects of peer-assisted UGC systems, including system size, peer bandwidth heterogeneity, limited peer storage, and video characteristics. We apply these models to numerically study YouTube-like UGC services. And third, we develop analytical models to understand the rate at which users would install P2P client applications to make peer-assisted UGC a success. Our results provide a comprehensive study of peer-assisted UGC distribution, exposing its fundamental characteristics and limitations.