Yongqiang Xiong

Stable Peers: Existence, Importance, and Application in Peer-to-Peer Live Video Streaming

This paper presents a systematic in-depth study on the existence, importance, and application of stable nodes in peer- to-peer live video streaming. Using traces from a real large-scale system as well as analytical models, we show that, while the number of stable nodes is small throughout a whole session, their longer lifespans make them constitute a significant portion in a per-snapshot view of a peer-to-peer overlay. As a result, they have substantially affected the performance of the overall system. Inspired by this, we propose a tiered overlay design, with stable nodes being organized into a tier-1 backbone for serving tier-2 nodes. It offers a highly cost-effective and deployable alternative to proxy-assisted designs. We develop a comprehensive set of algorithms for stable node identification and organization. Specifically, we present a novel structure, Labeled Tree, for the tier-1 overlay, which, leveraging stable peers, simultaneously achieves low overhead and high transmission reliability. Our tiered framework flexibly accommodates diverse existing overlay structures in the second tier. Our extensive simulation results demonstrated that the customized optimization using selected stable nodes boosts the streaming quality and also effectively reduces the control overhead. This is further validated through prototype experiments over the PlanetLab network.

mTreebone: A Collaborative Tree-Mesh Overlay Network for Multicast Video Streaming

Recently, application-layer overlay networks have been suggested as a promising solution for live video streaming over the Internet. To organize a multicast overlay, a natural structure is a tree, which, however, is known vulnerable to end-hosts dynamics. Data-driven approaches address this problem by employing a mesh structure, which enables data exchanges among multiple neighbors, and thus, greatly improves the overlay resilience. It unfortunately suffers from an efficiency-delay trade-off, because data have to be pulled from mesh neighbors by using extra notifications periodically. In this paper, we closely examine the contributions of overlay nodes, and argue that performance of a mesh overlay closely depends on a small set of stable backbone nodes. This is validated through a real trace study on PPLive, the largest commercial application-layer live streaming system to date. Motivated by this observation, we then suggest a novel collaborative tree-mesh design that leverages both mesh and tree structures. The key idea is to identify a set of stable nodes to construct a tree-based backbone, called treebone, with most of the data being pushed over this backbone. These stable nodes, together with others, are further organized through an auxiliary mesh overlay, which facilitates the treebone to accommodate node dynamics and fully exploit the available bandwidth between overlay nodes. This hybrid design, referred to as mTreebone, brings a series of unique and critical design challenges. In particular, the identification of stable nodes and seamless data delivery using both push and pull methods. In this paper, we present optimized solutions to these problems, which reconcile the two overlays under a coherent framework with controlled overhead. We evaluate mTreebone through both simulations and PlanetLab experiments. The results demonstrate the superior efficiency and robustness of this hybrid solution in both static and dynamic scenarios.

Optimizing the Throughput of Data-Driven Peer-to-Peer Streaming

During recent years, the Internet has witnessed a rapid growth in deployment of data-driven (or swarming based) peer-to-peer (P2P) media streaming. In these applications, each node independently selects some other nodes as its neighbors (i.e. gossip-style overlay construction), and exchanges streaming data with the neighbors (i.e. data scheduling). To improve the performance of such protocol, many existing works focus on the gossip-style overlay construction issue. However, few of them concentrate on optimizing the streaming data scheduling to maximize the throughput of a constructed overlay. In this paper, we analytically study the scheduling problem in data-driven streaming system and model it as a classical min-cost network flow problem. We then propose both the global optimal scheduling scheme and distributed heuristic algorithm to optimize the system throughput. Furthermore, we introduce layered video coding into data-driven protocol and extend our algorithm to deal with the end-host heterogeneity. The results of simulation with the real world traces indicate that our distributed algorithm significantly outperforms conventional ad hoc scheduling strategies especially in stringent buffer and bandwidth constraints.

MMC03-4: On the Optimal Scheduling for Media Streaming in Data-driven Overlay Networks

The Internet has witnessed a rapid growth in deployment of data-driven overlay network (DON) based streaming applications during recent years. In these applications, each node independently selects some other nodes as its neighbors (i.e. overlay construction), and exchanges streaming data with these neighbors (i.e. data scheduling). This scheme improves the robustness of the system. However, most of the work in the literature focused on the construction problem, and very few addressed its scheduling problem which is also very important for the overall performance. In this paper, we analytically study the scheduling problem in DON and model it as a classical min-cost network flow problem. We then propose both the global optimal scheduling scheme and distributed heuristic algorithm to maximize the system throughput. Experimental results indicate that our algorithms outperform other schemes and the throughput gain is up to 80%.

Per-packet load-balanced, low-latency routing for clos-based data center networks

Clos-based networks including Fat-tree and VL2 are being built in data centers, but existing per-flow based routing causes low network utilization and long latency tail. In this paper, by studying the structural properties of Fat-tree and VL2, we propose a per-packet round-robin based routing algorithm called Digit-Reversal Bouncing (DRB). DRB achieves perfect packet interleaving. Our analysis and simulations show that, compared with random-based load-balancing algorithms, DRB results in smaller and bounded queues even when traffic load approaches 100%, and it uses smaller re-sequencing buffer for absorbing out-of-order packet arrivals. Our implementation demonstrates that our design can be readily implemented with commodity switches. Experiments on our testbed, a Fat-tree with 54 servers, confirm our analysis and simulations, and further show that our design handles network failures in 1-2 seconds and has the desirable graceful performance degradation property.

Robust and efficient path diversity in application-layer multicast for video streaming

Application-layer multicast (ALM), as alternative to IP multicast, provides group communication without the need for network infrastructure support. To improve the reliability of ALM service, path diversity has been studied and two schemes to construct diverse paths for hosts are proposed. One is the random multicast forest (RMF) and the other is topology-aware hierarchical arrangement graph (THAG). RMF makes the paths from the media source to a participating host diverse by selecting parents for each host randomly, while THAG makes the paths node-disjoint by constructing multiple independent multicast trees, where any interior node in a multicast tree will be leaf node in all the other multicast trees. Topology-awareness is implemented in both schemes to make them efficient for media delivery. We compare the reliability and efficiency of THAG and RMF through extensive simulation. The results show that the reliability of THAG has been improved up to 20% compared with RMF. The efficiency metrics, such as relative delay penalty, link stress, and delay variation among different trees in THAG, are also smaller than or almost the same as that in RMF. The results indicate that THAG is a reliable and efficient ALM scheme for streaming media service.

Using CPU as a traffic co-processing unit in commodity switches

Commodity switches are becoming increasingly important as they are the basic building blocks for the enterprise and data center networks. With the availability of all-in-one switching ASICs, these switches almost universally adopt single switching ASIC design. However, such design also brings two major limitations, i.e, limited forwarding table for flow-based forwarding scheme such as Openflow and shallow buffer for bursty traffic pattern. In this paper, we propose to use CPU in the switches to handle not only control plane but also data plane traffic. We show that this design can provide large forwarding table for flow-based forwarding scheme and deep packet buffer for bursty traffic. We build such a prototype switch on ServerSwitch platform. In our evaluation, we show that our prototype can achieve over 90% traffic offloading ratio, absorb large traffic bursts without a single packet drop, and can be easily programmed to detect and defend low-rate burst attacks.

Tuning ECN for data center networks

There have been some serious concerns about the TCP performance in data center networks, including the long completion time of short TCP flows in competition with long TCP flows, and the congestion due to TCP incast. In this paper, we show that a properly tuned instant queue length based Explicit Congestion Notification (ECN) at the intermediate switches can alleviate both problems. Compared with previous work, our approach is appealing as it can be supported on current commodity switches with a simple parameter setting and it does not need any modification on ECN protocol at the end servers. Furthermore, we have observed a dilemma in which a higher ECN threshold leads to higher throughput for long flows whereas a lower threshold leads to more senders on incast under buffer pressure. We address this problem with a switch modification only scheme - dequeue marking, for further tuning the instant queue length based ECN to achieve optimal incast performance and long flow throughput with a single threshold value. Our experimental study demonstrates that dequeue marking is effective for increasing the maximum incast senders close to the performance limit of ECN, achieving a gain anywhere from 16% to 140%.

Pharos: accurate and decentralised network coordinate system

Network coordinates (NC) system is an efficient mechanism for Internet distance prediction with scalable measurements. The intrinsical cause for the unsatisfactory accuracy of the simulation-based NC algorithms has been identified. Then Pharos, a fully decentralised and hierarchical scheme, is proposed to solve this problem. Pharos leverages multiple coordinate sets at different distance scales, with the right scale being chosen for prediction each time. We evaluate the performance of Pharos system with the King data set and latency data from PlanetLab, and compare it with the representative NC system, Vivaldi. The experimental results show that Pharos greatly outperforms Vivaldi in Internet distance prediction without adding any significant overhead. Our extensive evaluation results also demonstrate that Pharos can significantly improve the performance in distributed Internet applications, such as overlay multicast and server selection.

Ripple-Stream: Safeguarding P2P Streaming Against Dos Attacks

Compared with file-sharing and distributed hash table (DHT) network, P2P video streaming is more vulnerable to denial of service (DoS) attacks because of its high bandwidth demand and stringent time requirement. This paper studies the design of DoS resilient streaming networks using credit systems. We propose a novel framework-ripple-stream-to improve DoS resilience of P2P streaming. Ripple-stream leverages existing credit systems to introduce credit constraints in overlay construction such that malicious nodes are pushed to the fringe of overlays. Combining credit constraints with overlay optimization techniques, ripple-stream can achieve both DoS resilience and overlay efficiency