PlanetLab Experiments Research Articles

Capability-Based Security Enforcement in Named Data Networking

Named data networking (NDN) enhances traditional IP networking by supporting in-network content caching for better bandwidth usage and location-independent data accesses for multi-path forwarding. However, NDN also brings new security challenges. For example, an adversary can arbitrarily inject packets to NDN to poison content cache, or access content packets without any restrictions. We propose capability-based security enforcement architecture (CSEA), a capability-based security enforcement architecture that enables data authenticity in NDN in a distributed manner. CSEA leverages capabilities to specify the access rights of forwarded packets. It allows NDN routers to verify the authenticity of forwarded packets, and throttles flooding-based DoS attacks from unsolicited packets. We further develop a lightweight one-time signature scheme for CSEA to ensure the timeliness of packets and support efficient verification. We prototype CSEA on the open-source CCNx platform, and evaluate CSEA via testbed and Planetlab experiments. Our experimental results show that CSEA only incurs around 4% of additional delays in retrieving data packets.

MCR: Structure-Aware Overlay-Based Latency-Optimal Greedy Relay Search

Geo-distributed network applications typically use relays to process and forward timely messages among clients. The state-of-the-art approaches greedily locate a relay that is closer to clients based on an overlay that favors neighbors in the immediate vicinity of the current node. Unfortunately, as clients are unknown a priori , the optimal relay is generally outside of the immediate vicinity of the current node. Consequently, the search process often terminates at a poor local minimum. In this paper, we address these challenges by designing and implementing a distributed relay-search system called MCR. In order to accurately locate a relay closer to clients, by observing that the latency space exhibits a proximity clustering phenomenon where nodes in the same cluster are typically within close proximity, we propose an overlay called MCRing that is aware of global proximity clusters. In order to scale well under dynamic relays, we maintain the proximity clusters via a gossiping-based clustering process. Furthermore, we propose a series of algorithms to accurately locate a relay that is closer to clients and satisfies the load constraints. We prove that the relay-search process achieves close to optimal results based on a doubling dimension-based analysis in an inframetric model. Finally, extensive evaluation via simulation and PlanetLab experiments shows that MCRing is able to locate near-optimal relays.

Privacy-preserving distributed collaborative filtering

We propose a new mechanism to preserve privacy while leveraging user profiles in distributed recommender systems. Our mechanism relies on two contributions: (i) an original obfuscation scheme, and (ii) a randomized dissemination protocol. We show that our obfuscation scheme hides the exact profiles of users without significantly decreasing their utility for recommendation. In addition, we precisely characterize the conditions that make our randomized dissemination protocol differentially private. We compare our mechanism with a non-private as well as with a fully private alternative. We consider a real dataset from a user survey and report on simulations as well as planetlab experiments. We dissect our results in terms of accuracy and privacy trade-offs, bandwidth consumption, as well as resilience to a censorship attack. In short, our extensive evaluation shows that our twofold mechanism provides a good trade-off between privacy and accuracy, with little overhead and high resilience.

Embedding Method for Packet Loss Self-Measurement of Video Streaming

PDF HTML阅读 XML下载 导出引用 引用提醒 一种嵌入视频流的丢包自测量方法 DOI: 10.3724/SP.J.1001.2013.04338 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(61073154) Embedding Method for Packet Loss Self-Measurement of Video Streaming Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:现有的丢包主动测量方法是通过探测流的丢包信息去推测网络的丢包特性,进而推测特定应用流的丢包,测量结果不能准确获知某一给定应用流的丢包情况.由于丢包通常属于短时间、小概率事件,要更加准确地测量丢包就意味着需延长测量时间,或者提高探测流的发送速率以及时发现丢包,这将不可避免地增加网络的额外负载.分析了不同类型帧损伤的影响,并以MPEG-4,H264 视频为研究对象,通过对其码流结构特点及RTP 封装策略的分析,提出一种将测量信息嵌入到视频用户数据域(User_Data)的丢包测量方法PLBU(packet loss measurement based on User_Data).该方法利用视频码流信息完成对丢包的探测,不影响视频的正常播放,不需要注入新的探测流,极大地降低了因测量而引入的额外负载.NIST Net 及Planetlab 等实验结果表明,该算法不仅丢包测量准确性高,且可提供丢包所属视频帧类型等信息,如视频中I,P,B 帧的数据包丢失的情况.借助该测量方法,服务提供商可评测网络视频流丢包,并分析视频体验质量(QoE)变化情况,且不受视频流在网络传输中的优先级影响. Abstract:The accurate packet loss measurement of application traffic has been challenging, since the frequently-used active monitoring approaches that use probe packets cannot capture the packet loss experienced by the traffic of individual user applications. Moreover, measurement and estimation of packet loss characteristics are challenging due to the relatively rare occurrence and typically short duration of packet loss episodes. Because it is often impossible to measure the entire data passing across a network, the most widely used method of measurement works by injecting probe packets. In order to overcome these shortcomings, this paper based on the analysis of MPEG4 video structural features and RTP encapsulation strategy, a novel packet loss probing technique, packet loss measurement based on User_Data (PLBU), is proposed. The PLBU complete packets loss measurement by using User_Data field of MPEG-4 video. This does not affect the normal video playback and dose not need to inject new probing stream, which makes it, less intrusive. NIST Net and Planetlab experiments verify the effectiveness of this method, and show that PLBU estimates packet loss more accurately, and with less measurement overhead than other existing technique such as BADABING. 参考文献 相似文献 引证文献

FreeRec: an anonymous and distributed personalization architecture

We present and evaluate FreeRec, an anonymous decentralized peer-to-peer architecture, designed to bring personalization while protecting the privacy of its users. FreeRec's decentralized approach makes it independent of any entity wishing to collect personal data about users. At the same time, its onion-routing-like gossip-based overlay protocols effectively hide the association between users and their interest profiles without affecting the quality of personalization. The core of FreeRec consists of three layers of overlay protocols: the bottom layer, rps, consists of a standard random peer sampling protocol ensuring connectivity; the middle layer, PRPS, introduces anonymity by hiding users behind anonymous proxy chains, providing mutual anonymity; finally, the top clustering layer identifies for each anonymous user, a set of anonymous nearest neighbors. We demonstrate the effectiveness of FreeRec by building a decentralized and anonymous content dissemination system. Our evaluation by simulation, our PlanetLab experiments, and our probabilistic analysis show that FreeRec effectively decouples users from their profiles without hampering the quality of personalized content delivery.

Push or pull? Toward optimal content delivery using cloud storage

Cloud computing and ‘Storage As A Service’ (SaaS) are experiencing a momentous popularity increase due to its flexible, and scalable access to resources. Especially, cloud storage is becoming an economical alternative to traditional content delivery networks (CDNs) such as Akamai and Limelight Networks for moderate-size content providers. Previous research on content distribution mainly focuses on reducing latency experienced by content customers. A few recent studies address the issue of bandwidth usage in CDNs, as the bandwidth consumption is an important issue due to its relevance to the cost of content providers. However, few researches consider both bandwidth consumption and delay performance for the content providers that use cloud storages with limited budgets, which is the focus of this paper. We develop an efficient light-weight approximation algorithm toward the joint optimization problem of content placement. We also conduct the analysis of its theoretical complexities. The performance bound of the proposed approximation algorithm exhibits a much better worst case than those in previous studies. We further extend the approximate algorithm into a distributed version that allows it to promptly react to dynamic changes in users’ interests. The extensive results from both simulations and Planetlab experiments exhibit that the performance is near optimal for most of the practical conditions.

Accelerating Peer-to-Peer File Sharing with Social Relations

Peer-to-peer file sharing systems, most notably BitTorrent (BT), have achieved tremendous success among Internet users. Recent studies suggest that long-term relationships among BT peers could be explored for peer cooperation, so as to achieve better sharing efficiency. However, whether such long-term relationships exist remain unknown. From an 80-day trace of 100,000 real world swarms, we find that less than 5% peers can meet each other again throughout the whole period, which largely invalidates the fundamental assumption of these peer cooperation protocols. Yet the recent emergence of online social network applications sheds new light on this problem. In particular, a number of BT swarms are now triggered by Twitter, reflecting a new trend for initializing sharing among communities. In this paper, we for the first time examine the challenges and potentials of accelerating peer-to-peer file sharing with Twitter social networks. We show that the peers in such swarms have stronger temporal locality, thus offering great opportunity for improving their degree of sharing. Based on the Hadamard Transform of peers' online behaviors, we develop a social index to quickly locate peers of common patterns. We further demonstrate a practical cooperation protocol that identifies and utilizes the social relations with the index. Our PlanetLab experiments indicate that the incorporation of social relations remarkably accelerates the downloading time. The improvement remains noticeable even in a hybrid system with a small set of socially active peers only.

Torrents on Twitter: Explore Long-Term Social Relationships in Peer-to-Peer Systems

Peer-to-peer file sharing systems, most notably BitTorrent (BT), have achieved tremendous success among Internet users. Recent studies suggest that the long-term relationships among BT peers can be explored to enhance the downloading performance; for example, for re-sharing previously downloaded contents or for effectively collaborating among the peers. However, whether such relationships do exist in real world remains unclear. In this paper, we take a first step towards the real-world applicability of peers' long-term relationship through a measurement based study. We find that 95% peers cannot even meet each other again in the BT networks; therefore, most peers can hardly be organized for further cooperation. This result contradicts to the conventional understanding based on the observed daily arrival pattern in peer-to-peer networks. To better understand this, we revisit the arrival of BT peers as well as their long-range dependence. We find that the peers' arrival patterns are highly diverse; only a limited number of stable peers have clear self-similar and periodic daily arrivals patterns. The arrivals of most peers are, however, quite random with little evidence of long-range dependence. To better utilize these stable peers, we start to explore peers' long-term relationships in specific swarms instead of conventional BT networks. Fortunately, we find that the peers in Twitter-initialized torrents have stronger temporal locality, thus offering great opportunity for improving their degree of sharing. Our PlanetLab experiments further indicate that the incorporation of social relations remarkably accelerates the download completion time. The improvement remains noticeable even in a hybrid system with a small set of social friends only.

Peer-Assisted Social Media Streaming with Social Reciprocity

Online video sharing and social networking are cross-pollinating rapidly in today's Internet: Online social network users are sharing more and more media contents among each other, while online video sharing sites are leveraging social connections among users to promote their videos. An intriguing development as it is, the operational challenge in previous video sharing systems persists, em i.e., the large server cost demanded for scaling of the systems. Peer-to-peer video sharing could be a rescue, only if the video viewers' mutual resource contribution has been fully incentivized and efficiently scheduled. Exploring the unique advantages of a social network based video sharing system, we advocate to utilize social reciprocities among peers with social relationships for efficient contribution incentivization and scheduling, so as to enable high-quality video streaming with low server cost. We exploit social reciprocity with two give-and-take ratios at each peer: (1) peer contribution ratio (em PCR), which evaluates the reciprocity level between a pair of social friends, and (2) system contribution ratio (em SCR), which records the give-and-take level of the user to and from the entire system. We design efficient peer-to-peer mechanisms for video streaming using the two ratios, where each user optimally decides which other users to seek relay help from and help in relaying video streams, respectively, based on combined evaluations of their social relationship and historical reciprocity levels. Our design achieves effective incentives for resource contribution, load balancing among relay peers, as well as efficient social-aware resource scheduling. We also discuss practical implementation and implement our design in a prototype social media sharing system. Our extensive evaluations based on PlanetLab experiments verify that high-quality large-scale social media sharing can be achieved with conservative server costs.

SLDRT: A measurement technique for available bandwidth on multi-hop path with bursty cross traffic

End-to-end available bandwidth is of great importance as a metric that characterizes the network’s dynamic transmitting capability. Most estimation methodologies infer available bandwidth from the relationship between the input inter-packet gaps and those of the output. This paper analyzes the challenges brought by extending the measurement environment to the multi-hop path with bursty cross-traffic. Based on the analysis, a novel probing technique, self-loading decreasing rate train (SLDRT), is proposed. SLDRT measures the available bandwidth by using a single decreasing rate packet train. The special train can efficiently avoid bias caused by multiple sampling. Performance analysis via NS-2 simulations and PlanetLab experiments verify the effectiveness of our method under multi-hop path with the bursty cross traffic environment, and also show that SLDRT estimates available bandwidth more quickly, accurately, and with less measurement overhead than other existing techniques such as pathload and pathChirp.

M3FEC: Joint Multiple Description Coding and Forward Error Correction for Interactive Multimedia in Multiple Path Transmission

The best-effort internet has inherent limitations on the end-to-end performance for interactive multimedia communications. This paper presents a multiple description coding (MDC) and forward error correction (FEC) based multiple path transmission schemes for interactive multimedia (M3FEC), which improves the end users' experience by maximizing a rate-distortion (R-D) based optimization problem. The proposed model considers both the network diversity and the application's stringent requirements, and combines the individual merits of the three promising technologies of multiple path overlay routing, MDC and FEC. Extensive numerical analysis and PlanetLab experiments demonstrate that M3FEC successfully combats packet losses, error propagation, and unpredictable network dynamics. This method also significantly increases distortion for interactive multimedia by over 10 dB than traditional IP-layer single path transmission in poor network environments, and outperforms the performance achieved by using MDC or FEC alone.

Enabling broadcast of user-generated live video without servers

We are witnessing the unprecedented popularity of User-Generated-Content (UGC) on the Internet. While YouTube hosts pre-recorded video clips, in near future, we expect to see the emergence of User-Generated Live Video, for which any user can create its own temporary live video channel from a webcam or a hand-held wireless device. Hosting a large number of UG live channels on commercial servers can be very expensive. Server-based solutions also involve various economic, copyright and content control issues between users and the companies hosting their content. In this paper, leveraging on the recent success of P2P video streaming, we study the strategies for end users to directly broadcast their own live channels to a large number of audiences without resorting to any server support. The key challenge is that end users are normally bandwidth constrained and can barely send out one complete video stream to the rest of the world. Existing P2P streaming solutions cannot maintain a high level of user Quality-of-Experience (QoE) with such a highly constrained video source. We propose a novel Layered P2P Streaming (LPS) architecture, to address this challenge. LPS introduces playback delay differentiation and constructs virtual servers out of peers to boost end users’ capability of driving large-scale video streaming. Through detailed packet-level simulations and PlanetLab experiments, we show that LPS enables a source with upload bandwidth slightly higher than the video streaming rate to stream video to tens of thousands of peers with premium quality of experience.

Minimising delay for video conference with network coding

Video conference is an attractive and promising application which allows immersive communication and discussion among people at different and distant places. However, its stringent delay and bandwidth requirements limit its scale and spread over current internet. This paper attempts to introduce the prosperous technology of network coding (NC) into video conference to minimise the maximal transmission delay between source and all the participants while retaining high bandwidth utilisation at the same time. Extensive numerical analysis and PlanetLab experiments demonstrate that the proposed innovative NC scheme can significantly improve the delay performance for video conference like multi-party interactive multimedia applications than conventional application level multicast.

Fuzzynet: Ringless routing in a ring-like structured overlay

Many structured overlay networks rely on a ring invariant as a core network connectivity element. The responsibility ranges of the participating peers and navigability principles (greedy routing) heavily depend on the ring structure. For correctness guarantees, each node needs to eagerly maintain its immediate neighboring links - the ring invariant. However, the ring maintenance is an expensive task and it may not even be possible to maintain the ring invariant continuously under high churn, particularly as the network size grows. Furthermore, routing anomalies in the network, peers behind firewalls and Network Address Translators (NATs) create non-transitivity effects, which inevitably lead to the violation of the ring invariant. We argue that reliance on the ring structure is a serious impediment for real life deployment and scalability of structured overlays. In this paper we propose an overlay called Fuzzynet, which does not rely on the ring invariant, yet has all the functionalities of structured overlays. Fuzzynet takes the idea of lazy overlay maintenance further by dropping any explicit connectivity and data maintenance requirement, relying merely on the actions performed when new Fuzzynet peers join the network. We show that with sufficient amount of neighbors (O(log N), comparable to traditional structured over-lays), even under high churn, data can be retrieved in Fuzzynet w.h.p. We validate our novel design principles by simulations as well as PlanetLab experiments and compare them with ring based overlays.

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.

Fast-Mesh: A Low-Delay High-Bandwidth Mesh for Peer-to-Peer Live Streaming

Peer-to-peer (P2P) technology has emerged as a promising scalable solution for live streaming to a large group. In this paper, we address the design of an overlay mesh which achieves low source-to-peer delay, accommodates asymmetric and diverse uplink bandwidth, and continuously improves delay based on an existing pool of peers. By considering a streaming mesh as an aggregation of data flows along multiple spanning trees, the peer delay in the mesh is then its longest delay (including both propagation and scheduling delay) among all the trees. Clearly, such delay can be very high if the mesh is not designed well. In this paper, we propose and study a mesh protocol called Fast-Mesh, which optimizes such delay while meeting a certain streaming bandwidth requirement. Fast-Mesh is particularly suitable for a mildly dynamic network consisting of proxies, supernodes, or content distribution servers. We first formulate the minimum delay multiple trees (MDMT) problem and show that it is NP-hard. Then we propose a centralized heuristic based on complete knowledge, which may be used when the network is small or managed, and serves as an optimal benchmark for all the other schemes under comparison. We then propose a simple distributed algorithm, Fast-Mesh, where peers select their parents based on the concept of power in networks given by the ratio of throughput and delay. By maximizing the network power, our algorithm achieves low delay. The algorithm makes continuous improvement on delay until some minimum delay is reached. Simulation and PlanetLab experiments show that our distributed algorithm performs very well in terms of delay and source workload, and substantially outperforms traditional and state-of-the-art approaches.

On the Placement of Infrastructure Overlay Nodes

Overlay routing has emerged as a promising approach to improving performance and reliability of Internet paths. To fully realize the potential of overlay routing under the constraints of deployment costs in terms of hardware, network connectivity and human effort, it is critical to carefully place infrastructure overlay nodes to balance the tradeoff between performance and resource constraints. In this paper, we investigate approaches to perform intelligent placement of overlay nodes to facilitate (i) resilient routing and (ii) TCP performance improvement. We formulate objective functions to capture application behavior: reliability and TCP performance, and develop several placement algorithms, which offer a wide range of tradeoffs in complexity and required knowledge of the client-server location and traffic load. Using simulations on synthetic and real Internet topologies, and PlanetLab experiments, we demonstrate the effectiveness of the placement algorithms and objective functions developed, respectively. We conclude that a hybrid approach combining greedy and random approaches provides the best tradeoff between computational efficiency and accuracy. We also uncover the fundamental challenge in simultaneously optimizing for reliability and TCP performance, and propose a simple unified algorithm to achieve both.

M2FEC: An effective FEC based multi-path transmission scheme for interactive multimedia communication

The oncoming prosperity of interactive multimedia application triggers significant challenges to current best-effort Internet due to such application’s stringent delay, loss and bandwidth requirements, and Internet’s unpredictable dynamics. Multi-path transmission and error-resilient coding are two promising approaches to alleviate these problems. This paper attempts to introduce error-resilient coding into multi-path transmission to better trade off between multi-path bandwidth resource consumption and reliable media quality. We propose a model for multi-paths interactive multimedia transmission and develop M2FEC—a FEC based transmission scheme which maximizes the overall quality at the client under various constraints based on the proposed model. Numerical simulation and PlanetLab experiments demonstrate the effectiveness and practicability of M2FEC in theory and in empiricism, respectively.

Experiences on enhancing data collection in large networks

We improve and validate TICP [C. Barakat, M. Malli, N. Nonaka, TICP: Transport Information Collection Protocol, Annals of Telecommunications 61 (1-2) (2006) 167-192], our TCP-friendly reliable transport protocol to collect information from a large number of Internet entities. A collector machine sends probes to a set of information sources that reply by sending back their reports. TICP adapts the sending rate of probes in a way similar to TCP for the purpose of avoiding network congestion and keeps requesting reports until they are well received. In a first part of this work, we add to TICP a mechanism to cluster information sources in order to smooth the variation of network conditions during the collection session and to ensure an efficient handling of congestion at network bottlenecks. Simulations in ns-2 and PlanetLab experiments prove the outperformance of TICP over non-adaptive solutions and the interest of the clustering mechanism in shortening the duration of the collection session and in decreasing the ratio of lost packets. In a second part, we adapt TICP to collect several packets of information from each data source. By the means of simulations, we compare the performance obtained by TICP to that obtained when using parallel short-lived TCP connections. Our main observation is that TICP yields shorter collection sessions due to its inherent multiplexing capability and that it avoids parallel Slow Start phases. Finally, in a last part, we study the impact of delegating collection to some proxy collectors. We explain our method for delegation and we show by simulations that for a judicious choice of proxy collectors, one can decrease considerably the collection session duration.

Evaluation of a comprehensive P2P video-on-demand streaming system

Video-on-demand (VoD) streaming has recently become a popular service on the Internet, with several companies offering videos to a global audience. However, traditional client/server based VoD streaming systems can be very bandwidth intensive and expensive to maintain, especially for high quality video content. To improve the scalability these systems, the use of peer-to-peer (P2P) networking has been proposed, but despite the efficiency of applications such as BitTorrent for downloading of large files, it is not simple to use P2P techniques for streaming. Problems such as firewalls and freeloaders reduce the efficiency of both types of P2P systems, but for real-time services such as streaming, the result can be reduced playback quality. Other issues include the traffic load imposed on ISPs by P2P networks, which can motivate ISPs to interfere with the P2P traffic. Finally, protecting against malicious modification of content can increase overhead, response times, and startup delays. We consider these issues to be fundamental to the problem of P2P based VoD, but despite the large amount of research that has been done in this field, these issues have largely been ignored. To address this, we present an evaluation of the Streaming P2P Protocol (SPP) architecture. By studying the problem as a whole we have found a simple and comprehensive solution that addresses all the four issues listed above. To show that the system is not only scalable, but also that it can be implemented efficiently, we have used both simulations and experiments on PlanetLab for evaluation. The results show that the combination of cache nodes and use of end-user resources found in the SPP architecture can give a low load on servers and ISPs, even when firewalls are taken into consideration. Furthermore, we observed low startup delays and few playback errors during the PlanetLab experiments. The scalable and low-cost distribution of content possible with the SPP architecture should be suitable for both large-scale commercial distributors and users of community networks with limited resources.