The performance and locality tradeoff in BitTorrent-like P2P file-sharing systems

The recent surge of large-scale peer-to-peer (P2P) applications has brought huge amounts of P2P traffic, which significantly changes the Internet traffic pattern and increases the traffic-relay cost at the Internet Service Providers (ISPs). To alleviate the stress on networks, localized peer selection has been proposed that advocates neighbor selection within the same network (AS or ISP) to reduce the cross-ISP traffic. Nevertheless, localized peer selection may potentially lead to the downgrade of downloading speed at the peers, rendering a non-negligible tradeoff between the downloading performance and traffic localization in the P2P system. Aiming at effective peer selection strategies that achieve any desired Pareto optimum in face of the tradeoff, in this paper, we characterize the performance and locality tradeoff as a multi-objective b-matching optimization problem. In particular, we first present a generic maximum weight b-matching model that characterizes the tit-for-tat in BitTorrent-like peer selection. We then introduce multiple optimization objectives into the model, which effectively characterize the performance and locality tradeoff using simultaneous objectives to optimize. We also design fully distributed peer selection algorithms that can effectively achieve any desired Pareto optimum of the global multi-objective optimization, that represents a desired tradeoff point between performance and locality in the entire system. Our models and algorithms are supported by rigorous analysis and extensive simulations. ©2010 IEEE.published_or_final_versionThe IEEE International Conference on Communications (ICC 2010), Cape Town, South Africa, 23-27 May 2010. In Proceedings of the IEEE International Conference on Communications, 2010, p. 1-

CLOSER: A Collaborative Locality-aware Overlay SERvice

Current Peer-to-Peer (P2P) file sharing systems make use of a considerable percentage of Internet Service Providers (ISPs) bandwidth. This paper presents the Collaborative Locality-aware Overlay SERvice (CLOSER), an architecture that aims at lessening the usage of expensive international links by exploiting traffic locality (i.e., a resource is downloaded from the inside of the ISP whenever possible). The paper proves the effectiveness of CLOSER by analysis and simulation, also comparing this architecture with existing solutions for traffic locality in P2P systems. While savings on international links can be attractive for ISPs, it is necessary to offer some features that can be of interest for users to favor a wide adoption of the application. For this reason, CLOSER also introduces a privacy module that may arouse the users' interest and encourage them to switch to the new architectur

Cloud-based Content Distribution on a Budget

To leverage the elastic nature of cloud computing, a solution provider must be able to accurately gauge demand for its offering. For applications that involve swarm-to-cloud interactions, gauging such demand is not straightforward. In this paper, we propose a general framework, analyze a mathematical model, and present a prototype implementation of a canonical swarm-to-cloud application, namely peer-assisted content delivery. Our system – called Cyclops – dynamically adjusts the off-cloud bandwidth consumed by content servers (which represents the bulk of the provider's cost) to feed a set of swarming clients, based on a feedback signal that gauges the real-time health of the swarm. Our extensive evaluation of Cyclops in a variety of settings – including controlled PlanetLab and live Internet experiments involving thousands of users – show significant reduction in content distribution costs (by as much as two orders of magnitude) when compared to non-feedback-based swarming solutions, with minor impact on content delivery times

ISP-friendly Peer-assisted On-demand Streaming of Long Duration Content in BBC iPlayer

In search of scalable solutions, CDNs are exploring P2P support. However, the benefits of peer assistance can be limited by various obstacle factors such as ISP friendliness - requiring peers to be within the same ISP, bitrate stratification - the need to match peers with others needing similar bitrate, and partial participation - some peers choosing not to redistribute content. This work relates potential gains from peer assistance to the average number of users in a swarm, its capacity, and empirically studies the effects of these obstacle factors at scale, using a month-long trace of over 2 million users in London accessing BBC shows online. Results indicate that even when P2P swarms are localised within ISPs, up to 88% of traffic can be saved. Surprisingly, bitrate stratification results in 2 large sub-swarms and does not significantly affect savings. However, partial participation, and the need for a minimum swarm size do affect gains. We investigate improvements to gain from increasing content availability through two well-studied techniques: content bundling - combining multiple items to increase availability, and historical caching of previously watched items. Bundling proves ineffective as increased server traffic from larger bundles outweighs benefits of availability, but simple caching can considerably boost traffic gains from peer assistance.Comment: In Proceedings of IEEE INFOCOM 201

Understanding the Properties of the BitTorrent Overlay

In this paper, we conduct extensive simulations to understand the properties of the overlay generated by BitTorrent. We start by analyzing how the overlay properties impact the efficiency of BitTorrent. We focus on the average peer set size (i.e., average number of neighbors), the time for a peer to reach its maximum peer set size, and the diameter of the overlay. In particular, we show that the later a peer arrives in a torrent, the longer it takes to reach its maximum peer set size. Then, we evaluate the impact of the maximum peer set size, the maximum number of outgoing connections per peer, and the number of NATed peers on the overlay properties. We show that BitTorrent generates a robust overlay, but that this overlay is not a random graph. In particular, the connectivity of a peer to its neighbors depends on its arriving order in the torrent. We also show that a large number of NATed peers significantly compromise the robustness of the overlay to attacks. Finally, we evaluate the impact of peer exchange on the overlay properties, and we show that it generates a chain-like overlay with a large diameter, which will adversely impact the efficiency of large torrents

Pushing BitTorrent Locality to the Limit

Peer-to-peer (P2P) locality has recently raised a lot of interest in the community. Indeed, whereas P2P content distribution enables financial savings for the content providers, it dramatically increases the traffic on inter-ISP links. To solve this issue, the idea to keep a fraction of the P2P traffic local to each ISP was introduced a few years ago. Since then, P2P solutions exploiting locality have been introduced. However, several fundamental issues on locality still need to be explored. In particular, how far can we push locality, and what is, at the scale of the Internet, the reduction of traffic that can be achieved with locality? In this paper, we perform extensive experiments on a controlled environment with up to 10 000 BitTorrent clients to evaluate the impact of high locality on inter-ISP links traffic and peers download completion time. We introduce two simple mechanisms that make high locality possible in challenging scenarios and we show that we save up to several orders of magnitude inter-ISP traffic compared to traditional locality without adversely impacting peers download completion time. In addition, we crawled 214 443 torrents representing 6 113 224 unique peers spread among 9 605 ASes. We show that whereas the torrents we crawled generated 11.6 petabytes of inter-ISP traffic, our locality policy implemented for all torrents would have reduced the global inter-ISP traffic by 40%

Understanding collaboration in volunteer computing systems

Volunteer computing is a paradigm in which devices participating in a distributed environment share part of their resources to help others perform their activities. The effectiveness of this computing paradigm depends on the collaboration attitude adopted by the participating devices. Unfortunately for software designers it is not clear how to contribute with local resources to the shared environment without compromising resources that could then be required by the contributors. Therefore, many designers adopt a conservative position when defining the collaboration strategy to be embedded in volunteer computing applications. This position produces an underutilization of the devices’ local resources and reduces the effectiveness of these solutions. This article presents a study that helps designers understand the impact of adopting a particular collaboration attitude to contribute with local resources to the distributed shared environment. The study considers five collaboration strategies, which are analyzed in computing environments with both, abundance and scarcity of resources. The obtained results indicate that collaboration strategies based on effort-based incentives work better than those using contribution-based incentives. These results also show that the use of effort-based incentives does not jeopardize the availability of local resources for the local needs.Peer ReviewedPostprint (published version

An Efficient Holistic Data Distribution and Storage Solution for Online Social Networks

In the past few years, Online Social Networks (OSNs) have dramatically spread over the world. Facebook [4], one of the largest worldwide OSNs, has 1.35 billion users, 82.2% of whom are outside the US [36]. The browsing and posting interactions (text content) between OSN users lead to user data reads (visits) and writes (updates) in OSN datacenters, and Facebook now serves a billion reads and tens of millions of writes per second [37]. Besides that, Facebook has become one of the top Internet traffic sources [36] by sharing tremendous number of large multimedia files including photos and videos. The servers in datacenters have limited resources (e.g. bandwidth) to supply latency efficient service for multimedia file sharing among the rapid growing users worldwide. Most online applications operate under soft real-time constraints (e.g., ≤ 300 ms latency) for good user experience, and its service latency is negatively proportional to its income. Thus, the service latency is a very important requirement for Quality of Service (QoS) to the OSN as a web service, since it is relevant to the OSN’s revenue and user experience. Also, to increase OSN revenue, OSN service providers need to constrain capital investment, operation costs, and the resource (bandwidth) usage costs. Therefore, it is critical for the OSN to supply a guaranteed QoS for both text and multimedia contents to users while minimizing its costs. To achieve this goal, in this dissertation, we address three problems. i) Data distribution among datacenters: how to allocate data (text contents) among data servers with low service latency and minimized inter-datacenter network load; ii) Efficient multimedia file sharing: how to facilitate the servers in datacenters to efficiently share multimedia files among users; iii) Cost minimized data allocation among cloud storages: how to save the infrastructure (datacenters) capital investment and operation costs by leveraging commercial cloud storage services. Data distribution among datacenters. To serve the text content, the new OSN model, which deploys datacenters globally, helps reduce service latency to worldwide distributed users and release the load of the existing datacenters. However, it causes higher inter-datacenter communica-tion load. In the OSN, each datacenter has a full copy of all data, and the master datacenter updates all other datacenters, generating tremendous load in this new model. The distributed data storage, which only stores a user’s data to his/her geographically closest datacenters, simply mitigates the problem. However, frequent interactions between distant users lead to frequent inter-datacenter com-munication and hence long service latencies. Therefore, the OSNs need a data allocation algorithm among datacenters with minimized network load and low service latency. Efficient multimedia file sharing. To serve multimedia file sharing with rapid growing user population, the file distribution method should be scalable and cost efficient, e.g. minimiza-tion of bandwidth usage of the centralized servers. The P2P networks have been widely used for file sharing among a large amount of users [58, 131], and meet both scalable and cost efficient re-quirements. However, without fully utilizing the altruism and trust among friends in the OSNs, current P2P assisted file sharing systems depend on strangers or anonymous users to distribute files that degrades their performance due to user selfish and malicious behaviors. Therefore, the OSNs need a cost efficient and trustworthy P2P-assisted file sharing system to serve multimedia content distribution. Cost minimized data allocation among cloud storages. The new trend of OSNs needs to build worldwide datacenters, which introduce a large amount of capital investment and maintenance costs. In order to save the capital expenditures to build and maintain the hardware infrastructures, the OSNs can leverage the storage services from multiple Cloud Service Providers (CSPs) with existing worldwide distributed datacenters [30, 125, 126]. These datacenters provide different Get/Put latencies and unit prices for resource utilization and reservation. Thus, when se-lecting different CSPs’ datacenters, an OSN as a cloud customer of a globally distributed application faces two challenges: i) how to allocate data to worldwide datacenters to satisfy application SLA (service level agreement) requirements including both data retrieval latency and availability, and ii) how to allocate data and reserve resources in datacenters belonging to different CSPs to minimize the payment cost. Therefore, the OSNs need a data allocation system distributing data among CSPs’ datacenters with cost minimization and SLA guarantee. In all, the OSN needs an efficient holistic data distribution and storage solution to minimize its network load and cost to supply a guaranteed QoS for both text and multimedia contents. In this dissertation, we propose methods to solve each of the aforementioned challenges in OSNs. Firstly, we verify the benefits of the new trend of OSNs and present OSN typical properties that lay the basis of our design. We then propose Selective Data replication mechanism in Distributed Datacenters (SD3) to allocate user data among geographical distributed datacenters. In SD3,a datacenter jointly considers update rate and visit rate to select user data for replication, and further atomizes a user’s different types of data (e.g., status update, friend post) for replication, making sure that a replica always reduces inter-datacenter communication. Secondly, we analyze a BitTorrent file sharing trace, which proves the necessity of proximity-and interest-aware clustering. Based on the trace study and OSN properties, to address the second problem, we propose a SoCial Network integrated P2P file sharing system for enhanced Efficiency and Trustworthiness (SOCNET) to fully and cooperatively leverage the common-interest, geographically-close and trust properties of OSN friends. SOCNET uses a hierarchical distributed hash table (DHT) to cluster common-interest nodes, and then further clusters geographically close nodes into a subcluster, and connects the nodes in a subcluster with social links. Thus, when queries travel along trustable social links, they also gain higher probability of being successfully resolved by proximity-close nodes, simultaneously enhancing efficiency and trustworthiness. Thirdly, to handle the third problem, we model the cost minimization problem under the SLA constraints using integer programming. According to the system model, we propose an Eco-nomical and SLA-guaranteed cloud Storage Service (ES3), which finds a data allocation and resource reservation schedule with cost minimization and SLA guarantee. ES3 incorporates (1) a data al-location and reservation algorithm, which allocates each data item to a datacenter and determines the reservation amount on datacenters by leveraging all the pricing policies; (2) a genetic algorithm based data allocation adjustment approach, which makes data Get/Put rates stable in each data-center to maximize the reservation benefit; and (3) a dynamic request redirection algorithm, which dynamically redirects a data request from an over-utilized datacenter to an under-utilized datacenter with sufficient reserved resource when the request rate varies greatly to further reduce the payment. Finally, we conducted trace driven experiments on a distributed testbed, PlanetLab, and real commercial cloud storage (Amazon S3, Windows Azure Storage and Google Cloud Storage) to demonstrate the efficiency and effectiveness of our proposed systems in comparison with other systems. The results show that our systems outperform others in the network savings and data distribution efficiency

Impact of traffic mix on caching performance in a content-centric network

For a realistic traffic mix, we evaluate the hit rates attained in a two-layer cache hierarchy designed to reduce Internet bandwidth requirements. The model identifies four main types of content, web, file sharing, user generated content and video on demand, distinguished in terms of their traffic shares, their population and object sizes and their popularity distributions. Results demonstrate that caching VoD in access routers offers a highly favorable bandwidth memory tradeoff but that the other types of content would likely be more efficiently handled in very large capacity storage devices in the core. Evaluations are based on a simple approximation for LRU cache performance that proves highly accurate in relevant configurations

Localising Peers in P2P Live Streaming Systems Within Resource-Constrained Networks

The use of locality within peer-to-peer (P2P) networks is showing promise, ensuring the construction of overlay networks that are both economically viable for network operators and scalable, ensuring the successful delivery of content. However, the underlying protocols on which P2P overlays are based were originally designed as a best-effort, non-real time transfer medium which is now rapidly having to evolve in order to better support more time sensitive, real-time video delivery systems. This shift places greater demand on locality mechanisms to ensure the correct balance between bandwidth savings and successful timely playback. In this paper, we continue our work to resolve the strong trade-off resulted from the limited network condition in order to support efficient P2P live streaming services. Based on our findings we propose an OPLoc framework for supporting locality and harmonised play points in a live streaming P2P system. We present our results and analysis of its operation through a series of simulations which measure bandwidth consumption at network egress points, failure rates and each peers’ play point relative to the live stream