Existing studies on BitTorrent systems are single-torrent based, while more than 85 % of all peers participate in multiple torrents according to our trace analysis. In addition, these studies are not sufficiently insightful and accurate even for single-torrent models, due to some unrealistic assumptions. Our analysis of representative Bit-Torrent traffic provides several new findings regarding the limitations of BitTorrent systems: (1) Due to the exponentially decreasing peer arrival rate in reality, service availability in such systems becomes poor quickly, after which it is difficult for the file to be located and downloaded. (2) Client performance in the BitTorrentlike systems is unstable, and fluctuates widely with the peer population. (3) Existing systems could provide unfair services to peers, where peers with high downloading speed tend to download more and upload less. In this paper, we study these limitations on torrent evolution in realistic environments. Motivated by the analysis and modeling results, we further build a graph based multi-torrent model to study inter-torrent collaboration. Our model quantitatively provides strong motivation for inter-torrent collaboration instead of directly stimulating seeds to stay longer. We also discuss a system design to show the feasibility of multi-torrent collaboration. 1

Abstract — Data-centric applications are still a challenging issue for large scale distributed computing systems. The emergence of new protocols and software for collaborative content distribution over Internet offers a new opportunity for efficient and fast delivery of high volume of data. In a previous paper, we have investigated BitTorrent as a protocol for data diffusion in the context of Computational Desktop Grid. We showed that BitTorrent is efficient for large file transfers, scalable when the number of nodes increases but suffers from a high overhead when transmitting small files. This paper investigates two approach to overcome these limitations. First, we propose a performance model to select the best of FTP and BitTorrent protocols according to the size of the file to distribute and the number of receiver nodes. Next we propose enhancement of the BitTorrent protocol which provides more predictable communication patterns. We design a model for communication performance and evaluate BitTorrent-aware versions BT-MinMin, BT-MaxMin and BT-Sufferage scheduling heuristics against a synthetic parametersweep application. I.

The commonly agreed Zipf-like access pattern of Web workloads is mainly based on Internet measurements when textbased content dominated the Web traffic. However, with dramatic increase of media traffic on the Internet, the inconsistency between the access patterns of media objects and the Zipf model has been observed in a number of studies. An insightful understanding of media access patterns is essential to guide Internet system design and management, including resource provisioning and performance optimizations. In this paper, we have studied a large variety of media workloads collected from both client and server sides in different media systems with different delivery methods. Through extensive analysis and modeling, we find: (1) the object reference ranks of all these workloads follow the stretched exponential

Abstract — In this paper, we present the mathematical analysis of two important performance measures for a BitTorrent (BT) like P2P file sharing system, namely, average file downloading time and file availability. For the file downloading time, we develop a model using the “stochastic differential equation ” approach, which can capture the system more accurately than some previous approach [17] and can capture various network settings and peers behavior. We study the steady-state behavior and obtain the closed-form solutions for performance measures which allow us to carry sensitivity analysis on various performance measures for various system parameters. We then extend this model to consider multiclass peers wherein some peers are behind firewalls which may impede the uploading service. We also present the mathematical model to study the file availability of a BT-like system. The model helps us gain the understanding of why the “rarest-first ” chunk selection policy is used in today’s BT protocol. We propose a novel chunk selection algorithm to enhance the overall system file availability. Extensive simulations are carried to validate our analysis. I.

Abstract — In this paper, we propose to model the dynamics of BitTorrent (BT) P2P file sharing systems using the stochastic differential equation method. Unlike previous approach, our method can capture more realistic network environment and peers behavior. Closed-form solutions of various performance measures such as the average number of downloaders, seeders, the system throughput and file downloading time are derived. We also validate our mathematical results via simulation and show that not only our mathematical model can closely track the dynamics of BT-like systems, but the model has a much higher accuracy than previous proposed methods. Also, many important properties can be derived from the close-form solution such as performance scalability, sensitivity of the measurements to various system parameters. We believe the proposed method can provide better understanding in the design and analysis of BT-like P2P systems. I.

Distributed Hash Tables (DHTs) have been used in a variety of applications, but most DHTs so far have opted to solve lookups with multiple hops, which sacrifices performance in order to keep little routing information and minimize maintenance traffic. In this paper, we introduce D1HT, a novel single hop DHT that is able to maximize performance with reasonable maintenance traffic overhead even for huge and dynamic peer-to-peer (P2P) systems. We formally define the algorithm we propose to detect and notify any membership change in the system, prove its correctness and performance properties, and present a Quarantine-like mechanism to reduce the overhead caused by volatile peers. Our analyses show that D1HT has reasonable maintenance bandwidth requirements even for very large systems, while presenting at least twice less bandwidth overhead than previous single hop DHT.

In this paper we report on the results of a largescale measurement study of two popular peer-to-peer systems, namely BitTorrent and eMule, that use practical and lightweight incentive mechanisms to encourage cooperation between users. We focus on identifying the strategic behavior of users in response to those incentive mechanisms. Our results illustrate a gap between what system designers and researchers expect from users in reaction to an incentive mechanism, and how users react to those incentives. In particular, we observe that the majority of BitTorrent users appear to cooperate well despite the existence of known ways to tamper with the incentive mechanism; while users engaging in behavior that could be regarded as cheating comprised around 10 % of BitTorrent’s population. In the eMule system, we identify two distinct classes of users based on their behavior. The first class contains users who appear to perceive cooperation as a good strategy, and openly share all the files they obtained. The second class comprises users who engage in more subtle strategic choices, by actively optimizing the number and types of files they share in order to improve their standing in eMule’s waiting queues; they tend to remove files for which downloading is complete and keep a limited total volume of files shared.

Measurement studies have shown that real world BitTorrent (BT) systems exhibit high seed capacity. Thus, appropriate use of seed capacity can have a significant effect on BT performance. Moreover, seed capacity is also easily exploitable by free-riders, and such free-riding clients exist out in the wild today. In this paper, we propose a simple and scalable approach that makes more intelligent use of seed capacity by hurting free-riders, without their explicit identification, while improving the performance of contributing nodes. The effectiveness of our approach is studied via extensive simulations.

BitTorrent is a highly popular peer-to-peer filesharing protocol. Much BitTorrent activity takes place within private virtual communities called “Private Trackers ”-aserver that allows only community members to share files. Many private trackers implement “ratio enforcement ” where the tracker monitors the upload and download behaviour of peers. If a peer downloads substantially more than it uploads then service is terminated. Tracker policies related to credit effect the performance of the community as a whole. We identify the possibility of a “credit squeeze ” in which performance is reduced due to lack of credit for some peers. We consider statistics from a popular private tracker and results from a simple model (called “BitCrunch”).

Abstract—A private BitTorrent site (also known as a “Bit-Torrent darknet”) is a collection of torrents that can only be accessed by members of the darknet community. The private BitTorrent sites also have incentive policies which encourage users to continue to seed files after completing downloading. Although there are at least 800 independent BitTorrent darknets in the Internet, they have received little attention in the research community to date. We examine BitTorrent darknets from macroscopic, medium-scopic and microscopic perspectives. For the macroscopic analysis, we consider 800+ private sites to obtain a broad picture of the darknet landscape, and obtain a rough estimate of the total number of files, accounts, and simultaneous peers within the entire darknet landscape. Although the size of each private site is relatively small, we find the aggregate size of the darknet landscape to be surprisingly large. For the medium-scopic analysis, we investigate content overlap between four private sites and the public BitTorrent ecosystem. For the microscopic analysis, we explore in-depth one private site and examine its user behavior. We observe that the seed-to-leecher ratios and upload-to-download ratios are much higher than in the public ecosystem. The macroscopic, medium-scopic and microscopic analyses when combined provide a vivid picture of the darknet landscape, and provide insight into how the darknet landscape differs from the public BitTorrent ecosystem. I.