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BitTorrent is nowadays the most common protocol to distribute contents through peer-to-peer networks. Because of its relevance, it is important to study and understand its behaviour and impact from several points of view, including those related to communication efficiency and security risks. In this paper, we analyse BitTorrent network focusing on the behaviour of shared resources. For that, we develop a monitoring methodology that allows to extract the time evolution of a sample of 1/256 of all the resources shared in the network. As a main difference with previous approaches, our methodology allows to monitor distributed hash table-based BitTorrent networks, that is, without considering trackers. We discuss the data obtained from a monitoring process carried out during 3 months, and as a result, we analyse the information of more than 70000 resources. This analysis is based on four features: geographic dispersion, popularity, sharing duration and availability. Finally, we show the potential of our methodology by outlining an example application that consists of a detection system intended to identify anomalous behaviours in the sharing of BitTorrent resources. Copyright © 2014 John Wiley & Sons, Ltd.

The polemic circumscribing the rise and regulation of new independent Indian cinema is a compelling example of vicissitudes in India's public sphere. This article locates a growing access to new independent Indian films through pirate spheres, reflected in the burgeoning popularity of BitTorrent websites, particularly among young, urban Indians, disenchanted by inaccessibility due to regulations and multiplex cinemas' expensive ticket-pricing system. It precipitates deeper discourses of ‘migrating’ cinema audiences, an ambivalent state of film and internet regulation, and civil resistance, exemplified in the recent Madras High Court volte face, unblocking banned BitTorrent websites. This article invokes interviews with independent filmmakers also utilising the paradigm of independent Bengali film Gandu (2010) – purportedly denied a release for its graphic sexual content, and yet widely accessed via BitTorrent and YouTube. Ultimately, this study examines the discursive ramifications of new independent Indian cinema in a metamorphosing Indian cinema sphere.

With only access billing no longer ensuring profits, an ISP's growth now relies on rolling out new and differentiated services. However, ISPs currently do not have a well-defined architecture for rapid, cost-effective, and scalable dissemination of new services. We present iSDF, a new SDN-enabled framework that can meet an ISP's service delivery constraints concerning cost, scalability, deployment flexibility, and operational ease. We show that meeting these constraints necessitates an SDN philosophy for a centralized management plane, a decoupled (from data) control plane, and a programmable data plane at customer premises. We present an ISP service delivery framework (iSDF) that provides ISPs a domain-specific API for network function virtualization by leveraging a programmable middlebox built from commodity home-routers. It also includes an application server to disseminate, configure, and update ISP services. We develop and report results for three diverse ISP applications that demonstrate the practicality and flexibility of iSDF, namely distributed VPN (control plane decisions), pay-per-site (rapid deployment), and BitTorrent blocking (data plane processing).

Cloud content providers must deliver vast amounts of data to an ever-growing number of users while maintaining responsive performance, thus increasing bandwidth-provisioning expenditures. To mitigate this problem, the authors transparently integrate BitTorrent into the cloud provider infrastructure and leverage users' upstream capacity to reduce bandwidth costs. They also allocate seeder bandwidth optimally among swarms to maximize throughput. Their system delivers higher performance when dealing with large volumes of data compared to the traditional client-server paradigm. The authors' solution has been integrated with OpenStack, a widely used open source platform for cloud services, to provide a personal cloud storage system.

BitTorrent is an issue for copyright protection and infringements should be punished based on evidence of invasion of the rights of others. In the BitTorrent system, seeders possess the complete content and leechers have partial content, and the content is shared among peers. Copyrighted content is easily distinguished with complete content but it might not be obvious with partial content. Thus, we propose an original content recovery technology based on Pulse Code Modulation pieces obtained from the CD ripping of music held by leechers. The proposed technique uses a correlation-based method that exploits the similarity of music. We verified that the proposed algorithm could recover pieces of files by comparing the output value of a correlator with that of the input piece, using a number of wave file channels and 8/16 bits.

With the many changes in mobile phone use, it is now common for users to connect to the Internet and share social and multimedia data, and peer-to-peer technology remains one of the most efficient solutions to content sharing. We analysed the lifecycle of content shared using the BitTorrent network, focusing on torrents retrieved by mobile phone clients using our MobTorrent application. MobTorrent, a complete Bit-Torrent client for feature phones, enables anonymous usage statistics to be collected. Based on statistics collected over the last three years, we analyze how mobile BitTorrent clients are being used. We discuss the success of individual sessions by additionally measuring peer connection download and success ratio statistics. This research can be considered as a pioneer work in the field of mobile content sharing solutions.

We propose a deterministic fluid model to understand the trade-offs in the design of peer-assisted video-on-demand (VoD) services. There are three entities in this model: peers (or end users), seeders (altruistic users that own one or several complete video items), and cache servers that store and forward videos with a limited capacity. Peers join the network, download one or multiple concurrent video streams (possibly different video items), and abort the system when they wish. Peers are assumed to cooperate in a BitTorrent-based fashion, governed by tit-for-tat and fair availability. The issue is to minimize the expected downloading times, choosing the set of video items that should be stored in each cache server. We first prove that the deterministic model is globally stable, and find closed expressions for the expected waiting times. Then, we introduce a combinatorial optimization problem (COP), whose nature is similar to the multiknapsack problem (where the items are videos, and knapsacks are related with the storage of cache servers). The problem turns out to be NP-complete. Therefore, we heuristically address the problem following a GRASP (greedy randomized adaptive search procedure) methodology. Finally, we simulate the new caching methodology with real-life traces taken from YouTube logs. The results suggest that the peer-to-peer philosophy is both stable and cost-effective for on-demand streaming purposes.

According to statistics, most P2P applications use Gnutella or BitTorrent protocols to combat free riders. However, BitTorrent restrains free riders using the choking algorithm that chokes free riders only. Whereas, Gnutella identifies and prevents malicious nodes using the EigenTrust algorithm that has been proven to be imperfect. Therefore, both of these schemes are inefficient. According to a research conducted in 2005, 85% of Gnutella network users are free riders and only 1% of the users share new files and resources voluntarily. In this paper, by considering users' bandwidth, computing power and energy, our proposed system architecture gives users corresponding counters, which are stored and managed by the server. Moreover, the file-sharing model of our system can be divided into real-time streaming media sharing and file sharing. As for real-time streaming media sharing, users can use their counters to participate in the auction and bid on the admission of high-quality real-time streaming. As for file sharing, users have to pay a certain number of counters for every unit of download bandwidth. That is to say that all system users must use the counters to bid on or purchase services, which further enables users' spontaneous resource sharing.

BitTorrent (BT) plays an important role in Internet content distribution. Because public BTs suffer from the free-rider problem, Darknets are becoming increasingly popular, which use Sharing Ratio Enforcement to increase their efficiency. We crawled and traced 17 Darknets from September 2009 to February 2011, and obtained datasets about over 5 million torrents. We conducted a broad range of measurements, including traffic, sites, torrents, and users activities. We found that some of the features of Darknets are noticeably different from public BTs. The results of our study reflect both macroscopic and microscopic aspects of the overall ecosystem of BitTorrent Darknets.

BitTorrent, the immensely successful file swarming system, supports content bundling: a common strategy by which publishers package multiple related files and disseminate them via a single larger swarm. It has been reported that bundling in BitTorrent is wide-spread, currently being done in a subjective and manual manner by individual publishers. This paper is motivated by the following questions: What if bundling is automatically supported by the BitTorrent swarming system (e.g., at a tracker)? By what criteria and how can files be automatically bundled, for better performance of the swarming system? How much performance improvement could be obtained with such an automatic bundling system? To answer the questions, we first suggest nine bundling strategies based on (i) the attributes of the torrents such as title or tags and (ii) time-varying swarm dynamics such as torrent popularity or availability. We then propose and develop a tracker-based bundling system, where all the proposed bundling strategies are implemented and evaluated with a set of real BitTorrent traces. We show that all the proposed bundling strategies outperform no-bundling case in terms of the availability and file download time. The bundling strategy that bundles more popular/available torrents with less popular/available ones outperforms others in most cases. We find that title- and tag-similarity based bundling strategies also provide performance improvement comparable to those of the popularity/availability based bundling strategies.

A substantial amount of work has recently gone into localizing BitTorrent traffic within an ISP in order to avoid excessive and often times unnecessary transit costs. Several architectures and systems have been proposed and the initial results from specific ISPs and a few torrents have been encouraging. In this work we attempt to deepen and scale our understanding of locality and its potential. Looking at specific ISPs, we consider tens of thousands of concurrent torrents, and thus capture ISP-wide implications that cannot be appreciated by looking at only a handful of torrents. Second, we go beyond individual case studies and present results for few thousands ISPs represented in our data set of up to 40K torrents involving more than 3.9M concurrent peers and more than 20M in the course of a day spread in 11K ASes. Finally, we develop scalable methodologies that allow us to process this huge data set and derive accurate traffic matrices of torrents. Using the previous methods we obtain the following main findings: i) Although there are a large number of very small ISPs without enough resources for localizing traffic, by analyzing the 100 largest ISPs we show that Locality policies are expected to significantly reduce the transit traffic with respect to the default random overlay construction method in these ISPs; ii) contrary to the popular belief, increasing the access speed of the clients of an ISP does not necessarily help to localize more traffic; iii) by studying several real ISPs, we have shown that soft speed-aware locality policies guarantee win-win situations for ISPs and end users. Furthermore, the maximum transit traffic savings that an ISP can achieve without limiting the number of inter-ISP overlay links is bounded by “unlocalizable” torrents with few local clients. The application of restrictions in the number of inter-ISP links leads to a higher transit traffic reduction but the QoS of clients downloading “unlocalizable” torrents would be severely harmed. The research leading to these results has been partially funded by the European Union's FP7 Program under the projects eCOUSIN (318398) and TREND (257740), the Spanish Ministry of Economy and Competitiveness under the eeCONTENT project (TEC2011-29688-C02-02), and the Regional Government of Madrid under the MEDIANET Project (S2009/TIC-1468). Publicado

In recent years, a novel BitTorrent (BT) technology, Private Tracker (PT), has received extensive attention from both academia and industry. Due to its huge amount of traffic volumes and users, it is essential to understand PT’s characteristics regarding system management. In this paper, by studying the data crawled from a number of well-known PT sites, we performed an in-depth measurement and analysis of the PT system, in terms of resources and users’ behavior characteristics. The analysis of the activity and age distributions of torrents indicates that the sequence of torrent activities followed a power-law distribution while the sequence of torrent’s age followed a linear distribution. It was also found that the resources redundancy between any two PTs was larger than 60 %, which led to a substantial waste of storage space and power energy due to the lack of sharing mechanism among PT sites. Measurements on the users’ behavior show that every PT site had a number of users with stable levels who contributed to the survivability and popularity of the site. Finally, based on the results, several drawbacks of PT system were identified, which are crucial for efficacious system management.

In recent years, the demand for live video streaming has steadily increased. Unfortunately, current video streaming architectures embody a number of drawbacks, which impact the quality of live video streaming and place a heavy demand on the video streaming server. Client-server architectures engender issues of network congestion, server bottlenecks and load-balancing, often leading to poor quality video playback at the client and thus making them inappropriate for live video streaming. Moreover, most live video streaming systems offer only a single, fixed bit rate video stream, which is typically not appropriate for all clients. If this bit rate is too high, then some clients may not possess sufficient bandwidth to view the video stream. Conversely, if it is set too low, then all clients will receive a low quality video stream, even those whose bandwidth can support a higher standard. The aforementioned issues can be addressed using multiple bit rate video streaming, thereby allowing clients to download content at a rate appropriate for their bandwidth. This paper focuses on the utilization of a BitTorrent-based, Peer-to-Peer (P2P) architecture, which mitigates the load on the video streaming server whilst supporting multiple bit rate live video streaming. Using this architecture, each client is able to share the responsibility of the streaming server by providing part of the steamed video content to other clients. Simulations conducted indicate that the proposed architecture offers better performance than both: the client-server approach and current P2P-based live video streaming systems.

BitTorrent (BT) is one of the most common Peer-to-Peer (P2P) file sharing protocols. Rather than downloading a file from a single source, the protocol allows users to join a swarm of peers to download and upload from each other simultaneously. Worms exploiting information from BT servers or trackers can cause serious damage to participating peers, which unfortunately has been neglected previously. In this article, we first present a new worm, called Adaptive BitTorrent worm (A-BT worm), which finds new victims and propagates sending forged requests to trackers. To reduce its abnormal behavior, the worm estimates the ratio of infected peers and adaptively adjusts its propagation speed. We then build a hybrid model to precisely characterize the propagation behavior of the worm. We also propose a statistical method to automatically detect the worm from the tracker by estimating the variance of the time intervals of requests. To slow down the worm propagation, we design a safe strategy in which the tracker returns secured peers when receives a request. Finally, we evaluate the accuracy of the hybrid model, and the effectiveness of our detection method and containment strategy through simulations.

There is no doubt that BitTorrent nowadays is one of the most popular peer-to-peer (P2P) applications on the Internet. On the other hand, Network Address Translation (NAT) has become pervasive in almost all networking scenarios. Despite the effort of NAT traversal, it is still very likely that applications, especially P2P ones, cannot receive incoming connection requests properly if they are behind NAT. In this paper, we build analytical models to characterize BitTorrent-like P2P systems with the presence of homogeneous and heterogeneous NAT peers, from which we observe and mathematically reason the poor download performance of NAT peers. Motivated by this observation, we further investigate the fairness metrics of the system, which reveal the fundamental problem of the BitTorrent unchoke mechanism: it is unaware of, and unfair to NAT peers. We thus propose a tunable optimistic unchoke strategy, in order to improve the overall system performance and fairness metrics considerably. The simulation results have validated our analytical models, and also the efficacy of our tunable optimistic unchoke strategy.

The adaptation of the BitTorrent protocol to multimedia on-demand streaming systems essentially lies on the modification of its two core algorithms, namely the piece and the peer selection policies, respectively. Much more attention has though been given to the piece selection policy. Within this context, this article proposes three novel peer selection policies for the design of BitTorrent-like protocols targeted at that type of systems: Select Balanced Neighbour Policy (SBNP), Select Regular Neighbour Policy (SRNP), and Select Optimistic Neighbour Policy (SONP). These proposals are validated through a competitive analysis based on simulations which encompass a variety of multimedia scenarios, defined in function of important characterization parameters such as content type, content size, and client interactivity profile. Service time, number of clients served and efficiency retrieving coefficient are the performance metrics assessed in the analysis. The final results mainly show that the novel proposals constitute scalable solutions that may be considered for real project designs. Lastly, future work is included in the conclusion of this paper., 19 PAGES

With the advent of BitTorrent protocol, internet users can easily share their movie and music files. Although the BitTorrent provides a highly efficient mechanism, the illegal use of BitTorrent on unauthorized distributing of copyright- protected digital content is increasing rapidly. To prevent illegal distribution of copyrighted files from spreading over the internet, the file pieces split by torrent file must be detected as soon as possible. In this paper, we propose a method of audio recognition on a few pieces of audio files downloaded by BitTorrent client program. The audio identification algorithm is made up of beat tracking and chroma features. To identify audio in the piece, the beat-by-chroma representations obtained from the piece and original audio are cross-correlated and look for sharp peaks. The experimental results show probabilities of successfully identifying the pieces with different piece sizes and different number of pieces.

In this paper, we propose a modification to the BitTorrent protocol related to its peer unchoking policy . In particular, we apply a novel optimistic unchoking approach that improves the quality of inter-connections amongst peers, i.e., increases the number of directly-connected and interested-in-cooperation peers without penalizing underutilized and/or idle peers. Our optimistic unchoking policy takes into consideration the number of clients currently interested in downloading from a peer that is to be unchoked. Our conjecture is that peers having few clients interested in downloading data from them, should be favored with optimistic unchoke intervals. This enables the peers in question to receive data since they become unchoked faster and in turn, they will trigger the interest of additional clients. In contrast, peers with plenty of “interested” clients should enjoy a lower priority to be selected as planned optimistic unchoked , since these peers likely have enough data to forward; nevertheless, they receive enough data due to tit-for-tat peer reciprocation and are not in need of optimistic unchoking slots. Armed with this realization, we establish an analytical model and prove a significant performance improvement under our modified BitTorrent protocol. Experimental results, also, indicate that our approach significantly outperforms the existing optimistic unchoking policy in three important aspects: first, there is a higher number of interested-in-cooperation and directly-connected peers. Second, since leechers now act as data intermediaries, the load on seeders eases up considerably. Last, a shorter bootstrapping period for fresh peers is achieved. Hence, we claim that our approach helps implement an enhanced BitTorrent protocol and we name it “ EnhancedBit ”.

Peer to Peer communication has become very popular these days .This popularity and increase in P2P traffic has given birth to many internet traffic management problems for service providers. One of these problems is high download traffic of P2P file sharing application for long network distances ,as current applications do not pay attention to network topology while selecting peers for sharing data .To reduce this trans network traffic various solutions have been suggested but all of them lead to compromises for upload rate, or file availability ,or external infrastructure on the internet to support the solution. This papers suggest a modified version of Adaptive search radius algorithm for BitTorrent to solve the problem , at minimum compromise to efficiency of file sharing applications .This papers shows how BitTorrent protocol react to modified adaptive search radius , as it is the most favored application for peer to peer file sharing .

Peer-to-peer systems are a popular means of transferring files over the Internet, accounting for a third of the upload bandwidth of end users as of 2013. However, recent studies have highlighted that peer-to-peer systems are affected by a lack of balance between the supply and demand of bandwidth. This imbalance stems from the skewed popularity distribution of the files transfered in the system; newly released files may exhibit an undersupply of bandwidth while older ones may exhibit oversupply. In this work, we introduce a bandwidth marketplace for peers, with the aim of aligning supply and demand without the need for human intervention. Peers constantly monitor their performance and gossip with each other about undersupplied files. Peers with idle upload bandwidth that learn about an undersupplied file can autonomously start a special help mode download, with the goal of supplying as much upload bandwidth as possible to the other peers. We present an analytical model of help mode downloading and derive from it bounds for the performance of helper peers. Furthermore, we evaluate a recent existing implementation of help mode in Libtorrent, a popular BitTorrent library. Our tests show that Libtorrent help mode is effective at alleviating undersupply, although its performance relative to our model can be improved.

In this paper, we propose a method of recovering the music piece of FLAC file downloaded by BitTorrent. It was decoded the split FLAC file via getting the complete frames from piece of FLAC file and adding the temporary header to decode. The percentage of successfully decoding is all above 90%. From the partial audio signal we extract the musical feature and calculate the cross-correlation with the features in database. The feature in database is extract from the complete music file. The Musical feature is detected by chromagram to get the key strength. The percentage of audio identification is growing tendency with the increase of piece size. It experiment shows probability of identify audio with getting the part of FLAC file distributed by BitTorrent.

Mestrado em Engenharia de Computadores e Telemática Desde a criação da Internet que existem inumeras formas de partilhar ficheiros, mas até ao dia de hoje é discutível se alguma possa ser considerada a melhor. A apetência do público em geral para conteúdo multimedia levou ao aparecimento de novas plataformas de distribuição de conteúdo como o Google Play, Netflix, Apple Store, entre outros. Estes conteúdos são distribuídos de forma centralizada e levam a grandes custos de infra-estrutura para essas entidades. Por outro lado, as redes P2P permitem a distribuição de conteúdos de forma descentralizada e com baixos custos, estes contudo, exigem aplicações específicas e conhecimentos técnicos, o que se torna uma barreira entre o consumidor e os conteúdos que estão disponíveis nestas plataformas. Nesta tese é desenvolvido um protótipo de uma nova solução, usando novos standards HTML5 como WebSockets e WebRTC para introduzir uma nova perspectiva de como os utilizadores podem partilhar e consumir conteúdo. Em termos simples, a abordagem desta tese procura trazer a rede BitTorrent para os Browsers usando apenas javascript, tirando partido da sua facilidade de utilização por não exigir qualquer tipo de instalação necessária. Usando WebRTC esta tese foca-se em como fazer crescer a rede dos Browsers de forma descentralizada, incentivando o consumo de conteúdo em comunidades de utilizadores num esforço para aumentar a privacidade e resistência à censura, assim como mitigar limitações de escala da solução. Os resultados deste trabalho demonstram que alguns conceitos utilizados nesta tese têm vantagens únicas que são relevantes para o público em geral, no entanto, estas vêm com o custo de algumas limitações que são inerentes e devem ser mitigadas. Since the inception of the Internet there are a lot of ways to share files, but still to this day it is arguable if there’s a best one. The palatability of the general public for multimedia content created the need for new platforms of content distribution like Google Play, Netflix, Apple Store and some others. Contents that are distributed in a centralized way and that lead to great infrastructure costs to these entities. On the other hand, P2P networks allow the distribution of content in a decentralized way with low costs, these however require specific applications and technical knowledge, which is a barrier between the consumer and the contents that are available in these platforms. In this thesis a prototype of a new solution is developed, using upcoming HTML5 standards like WebSockets and WebRTC to introduce a new perspective to how users can share and consume content. In simple terms, the approach of this thesis is to bring the BitTorrent network into the browsers using only javascript, taking advantage of its ease of use by not requiring any kind installation. Using WebRTC this thesis focused in how to grow the browser’s network while being decentralized, encouraging content consumption in communities of users in an effort to increase privacy and resilience to censorship as well as mitigate scaling limitations of the solution. Results of this research demonstrate that some concepts used in this thesis have unique advantages that are relevant to the general public, however they come at the cost of some inherent limitations that should be mitigated.

Large datacenter operators often run a large number of datacenters over the globe, and it is of their great interest to improve the bandwidth utilization of inter-datacenter networks. One general approach is to schedule delay tolerant background traffic over the residual bandwidth. However, the difficulty is that the residual bandwidth is time and spatial varying, and the traditional bandwidth forecast technique is not precise enough. We propose a back- pressure based joint flow scheduling and bandwidth allocation algorithm which does not require the prior- knowledge of residual bandwidth. The algorithm allows the data packets to be temporarily stored at intermediate datacenters and forwarded to the destination when there are available spare residual bandwidth. The main idea is to balance the buffers of two adjacent datacenter nodes as much as possible by pushing data across the link between the two nodes using the residual bandwidth, where the buffer size is regard as the pressure of the buffer. The novelty of our approach is that it allows random bandwidth, where in the original algorithm, the link bandwidth is fixed and static. In order to cope with the randomness of residual bandwidth, we redesign the buffer reallocation scheme and apply the Lyapunov drift technique with a completely new Lyapunov function to prove the stability of the algorithm. Our experiments show that the algorithm makes the buffers stable when the data arrival rates are inside the residual capacity region and achieves good throughput compared with the simple store-and-forward strategy and the BitTorrent technique.

Bit Torrent protocol is widely used for file sharing in peer-to-peer systems. Also, many cloud environments utilizethis protocol. Despite many advantages, among which are goodscalability and performance, BitTorrent has also limitations. Toamend them, this paper proposes TManTorrent protocol — adistributed BitTorrent protocol, which replaces a tracker serverwith a gossiping mechanism, and promotes most appropriatenodes to cooperate with, during exchange of a required content. The paper includes results of simulation experiments, which confirm the efficiency of the proposed TManTorrent protocol.

As citizens debate the morality of using global surveillance to enforce cyber security, software technologies that can proliferate illegal distribution of copyright material are evolving rapidly. One such technology is Peer-to-Peer networking which, through well-known implementations such as Napster, Bittorrent and eMule, has enabled users to share files at optimal speeds and at near infinite scale. This technology is contentious in that it can distribute highly desired files globally in minutes if not seconds and determining illegal vs legal applications is a challenge. Recently, a new player Xunlei has arrived on the Peer-to-Peer scene with an impressive network and unprecedented global reach. Xunlei, a proprietary Peer-to-Peer network, is unique in that it aggregates multiple file sources together seamlessly enabling content to be consumed via a single client. The aggregated approach raises some ethical dilemmas. Is it a good thing that centralised management of Peer-to-Peer networks exists? Is it a form of populous control? Where will it lead as Peer-to-Peer usage becomes more mainstream? Finally, does it threaten an individual's privacy? This paper investigates the Xunlei network as it stands today and takes valuable steps towards addressing these questions, and to defining future fields of research.

In this paper we introduce IoTPatchPool — a novel scheme that enables an incentivized distributed delivery network of IoT software updates. We use a decentralized storage network for reducing the load on the vendor when distributing patches toward IoT devices, and eliminating central points of failure. Unlike existing peer-to-peer file sharing networks which have a fundamental availability problem for unpopular files, our protocol utilizes blockchain-based smart contracts to incentivize independent peers, termed distributors, by means of cryptocurrency payments. A vendor of IoT devices deploys a smart contract with a deposit, which acts as a publicly verifiable binding bid for delivery of patches to a specific set of IoT endpoints. Distributors will compete for delivering the updates to the desired IoT devices and present proofs-of-distribution in exchange for cryptocurrency payments. We address the fair exchange problem between distributors and the consuming IoT devices by utilizing a variation of the Zero-Knowledge Contingent Payments (ZKCP) protocol, ensuring that the process is trustless. This can encourage the participation of a large number of distributors, and thus facilitate a rapid scale-out of the system. Finally, we present and evaluate a prototype implementation combining the BitTorrent network with the cryptocurrency Ethereum.

This paper focuses on the sampling-based Deep Packet Inspection for the traffic of P2P file sharing systems, especially for BitTorrent, and proposes a logarithmic-based Adaptive Trust Sampling (ATS) strategy for P2P traffic identification. In the whole process of sampling identification for P2P traffic, the sampling ratio of the current node in a P2P network can automatically adjust and dynamically vary according to the estimator of P2P traffic ratio of historical cycles. The experimental results show that the Adaptive Trust Sampling strategy can adapt to the dynamic change of sample size, effectively reduce the total sample size, mitigate the consumptions of system resources to some extent, and achieve the purpose of P2P traffic sampling.

Piece-related algorithms, including piece revelation, selection, and queuing, play a crucial role in the BitTorrent (BT) protocol, because the BT system can be viewed as a market where peers trade their pieces with one another. During the piece exchanging, a peer selects some pieces revealed by neighbors, and queues them up for downloading. In this paper, we provide a deep understanding of these algorithms, and also propose some improvements to them. Previous study has shown that the piece revelation strategy is vulnerable to under-reporting. We provide a game-theoretic analysis for this selfish gaming, and propose a distributed credit method to prevent it. Existing piece selection strategies, though long believed to be good enough, may fail to balance piece supply and demand. We propose a unified strategy to shorten the download time of peers by applying utility theory. The design of the piece queuing algorithm has a conflict with that of piece selection strategy, because it is not possible to assume that the queued requests for a selected piece can always be available on multiple neighbors. We give a possible fix to address the conflict by allowing peers to dynamically manage their unfulfilled requests. To evaluate the performance of the proposed algorithms, we run several experiments in a live swarm. Our primary results show that they can achieve fast individual and system-wide download time.

Reliable Group Data Delivery (RGDD) is a pervasive traffic pattern in data centers. In an RGDD group, a sender needs to reliably deliver a copy of data to all the receivers. Existing solutions either do not scale due to the large number of RGDD groups (e.g., IP multicast) or cannot efficiently use network bandwidth (e.g., end-host overlays). Motivated by recent advances on data center network topology designs (multiple edge-disjoint Steiner trees for RGDD) and innovations on network devices (practical in-network packet caching), we propose Datacast for RGDD. Datacast explores two design spaces: 1) Datacast uses multiple edge-disjoint Steiner trees for data delivery acceleration. 2) Datacast leverages in-network packet caching and introduces a simple soft-state based congestion control algorithm to address the scalability and efficiency issues of RGDD. Our analysis reveals that Datacast congestion control works well with small cache sizes (e.g., 125KB) and causes few duplicate data transmissions (e.g., 1.19%). Both simulations and experiments confirm our theoretical analysis. We also use experiments to compare the performance of Datacast and BitTorrent. In a BCube(4, 1) with 1Gbps links, we use both Datacast and BitTorrent to transmit 4GB data. The link stress of Datacast is 1.01, while it is 1.39 for BitTorrent. By using two Steiner trees, Datacast finishes the transmission in 16.9s, while BitTorrent uses 52s.

In this paper, we investigated the problem of copyright infringement in the peer-to-peer (P2P) environment, and proposed a system for piracy tracking. Even though the BitTorrent P2P software is a very efficient way to transfer files, it has become the main tool used to pirate copyrighted materials. Thus, we studied the bit torrent packet itself in order to detect the destination and source of the piracy. The torrent meta-file which has hash values of the pieces of the shared content is also analyzed to identify copyrighted material. As a result, we proposed a tracking system for copyright protection against BitTorrent piracy. Our system consists of hash database, feature database, protocol analyzer, torrent meta-file crawler, and copyright identifier. In this tracking system, the content is identified by three ways. The first way is to use the info hash in the hash DB. The second way is to use the piece hash value in the hash DB. Last way is to use the feature of the content that is able to identify if the content is slightly changed from original. If the proposed system is installed on the ISP network, it is able to protect the content from BitTorrent distribution.

Peer-to-Peer (P2P) streaming technology based on various service requirements often remains on the elusive benefits of user-friendly video streaming in cloud computing environments. Cloud-assisted P2P media streaming gives an opportunity to enhance on-demand, dynamic and easily accessible videos. This paper outlines the fundamental video block device (VBD) method for user-friendly viewing patterns that inherits from user access patterns and provides efficient delivery using an enhanced BitTorrent protocol.

BitTorrent is the most popular peer-to-peer (P2P) content delivery application where individual users share various types of content with tens of thousands of other users. The growing popularity of BitTorrent is primarily due to the availability of valuable content without any cost for the consumers. However, apart from the required resources, publishing valuable (and often copyrighted) content has serious legal implications for the users who publish the material. This raises the question that whether (at least major) content publishers behave in an altruistic fashion or have other motives such as financial incentives. In this paper, we identify the content publishers of more than 55 K torrents in two major BitTorrent portals and examine their characteristics. We discover that around 100 publishers are responsible for publishing 67% of the content, which corresponds to 75% of the downloads. Our investigation reveals several key insights about major publishers. First, antipiracy agencies and malicious users publish “fake” files to protect copyrighted content and spread malware, respectively. Second, excluding the fake publishers, ontent publishing in major BitTorrent portals appears to be largely driven by companies that try to attract consumers to their own Web sites for financial gain. Finally, we demonstrate that profit-driven publishers attract more loyal consumers than altruistic top publishers, whereas the latter have a larger fraction of loyal consumers with a higher degree of loyalty than the former. TRUE pub

There are substantial differences in chunk dissemination manner between P2P live streaming and BitTorrent, and inappropriate algorithms will result in inefficiency of live streaming systems. In this paper, we study the chunk dissemination of P2P live streaming, and introduce a discrete and slotted mathematical model to analyze chunk selection algorithms, including rarest first algorithm and greedy algorithm. Moreover, we present a performance metric to evaluate chunk selection algorithms, as well as the optimization function for the exploration of chunk dissemination strategies. We point out the causes of poor performance of these algorithms, and propose a service request randomization mechanism to promote the use of peer resources, which can prevent chunk requests from rendezvous on a few of peers. Simultaneously, we employ weight assignment strategies to avoid excessive requests for rare chunks. Besides, we present an enhanced model, which adds node degree constraint, to improve our model. We revisit the chunk selection algorithms based on the enhanced model. The results of simulation experiments validate our theoretical analysis and indicate that the weighted randomization mechanism is resilient to flash crowd and peer churn, and can improve the performance of P2P live streaming.

Recently, the Federal Communications Commission has mandated the use of a database to observe the spectral opportunity at a given place over time along with the use of spectrum sensing. It is arduous to obtain the database for spectral opportunity for all places, and since spectral opportunities rapidly vary with location, a new paradigm to obtain the spectral opportunity needs to be determined. We propose a method to obtain the spectral opportunity at a given location for specific channels, such as television (TV) and frequency-modulated (FM) bands, which follow deterministic time usage pattern. Since these channels have a periodic deterministic time usage pattern for every 24 h, learning the spectral opportunities and utilizing these for consequent time periods have better efficiency than other proposed schemes. Once the spectral opportunity is known and if we have multiple channels from which to select, then a decision on the selection of a channel is made. The spectrum decision is done to satisfy the constraints imposed by a user. Since, with our proposed method, the spectral opportunity is known ahead of time, better spectrum decisions can be made. To this end, we propose three different channel selection techniques with different constraints applied. The first channel selection technique provides the selection of channels with a minimum number of channel switching and, thus, reduces the jitters, switching delays, and packet losses. This channel selection technique is appurtenant to real-time applications such as voice over Internet Protocol. The second channel selection technique provides the selection of channels that maximizes the overall throughput of the system and is particularly useful for bandwidth-intensive applications such as BitTorrent. The third channel selection technique provides a compromised value between minimal channel switching and maximal throughput, thus providing a control over the bandwidth demand and real-time requirement. A comparison of these channel selection techniques is done with three other studies to demonstrate the competency in terms of a number of channel switching and throughput obtained in the system.

Power consumption is becoming more and more important with the increased popularity of smart-phones, tablets and laptops. The threat of reducing a customer's battery-life now hangs over the software developer, who now asks, "will this next change be the one that causes my software to drain a customer's battery?" One solution is to detect power consumption regressions by measuring the power usage of tests, but this is time-consuming and often noisy. An alternative is to rely on software metrics that allow us to estimate the impact that a change might have on power consumption thus relieving the developer from expensive testing. This paper presents a general methodology for investigating the impact of software change on power consumption, we relate power consumption to software changes, and then investigate the impact of OO software metrics and churn metrics on power consumption. We demonstrated that software change can effect power consumption using the Firefox web-browser and the Azureus/Vuze BitTorrent client. We found evidence of a potential relationship between some software metrics and power consumption. We also investigate the effect of library versioning on the power consumption of rTorrent. In conclusion, we investigate the effect of software change on power consumption on two projects; and we provide an initial investigation on the impact of software metrics on power consumption.

Motivated by the popularity of content distribution and file sharing applications that nowadays dominate Internet traffic, we focus on the incentive mechanism of a very popular, yet not very well studied, peer-to-peer application, eMule. In our work, we recognize that the incentive scheme of eMule is more sophisticated than current alternatives (e.g., BitTorrent) as it uses a general, priority-based, time-dependent queuing discipline to differentiate service among cooperative users and free-riders. In this paper, we describe a general model of such an incentive mechanism and analyze its properties in terms of application performance. We validate our model using both numerical simulations (when analytical techniques become prohibitive) and with a measurement campaign of the live eMule system. Our results, in addition to validating our model, indicate that the incentive scheme of eMule suffers from starvation. Therefore, we present an alternative scheme that mitigates this problem, and validate it through numerical simulations and a second measurement campaign.

Video on demand services have been increasingly proliferated in the Internet. One popular way to disseminate video files among numerous users is to leverage peer-to-peer (P2P) systems (e.g., BitTorrent). However, BitTorrent is not designed with video streaming requirements and hence suffers from long setup delay. In this paper, the drawbacks of existing P2P-based streaming solutions are analyzed in terms of sequential delivery. Then we propose Waterfall that splits the whole swarm into multiple swarms, which are then cascaded by the scene sequence. In this way, peers in a swarm download the chunks of the same video scene from the peers in the same swarm as well as the ones in the preceding swarm that already moved on to the next scene. The average setup delay and maximum playback rate of Waterfall are analyzed. Experiments from a wide area network testbed reveal that Waterfall achieves two to three times higher playback rate and significantly low setup delay than the prior BitTorrent-based streaming solutions.

BitTorrent (BT) is a widely-used peer-to-peer (P2P) application. Most of BT's characteristics (except the topology) have been studied extensively by measurement approaches. In this paper, we deploy a measurement system to examine some performance-related topology properties of BT. Our goal is to provide a measurement view of the real-world BT topologies and to verify the previous estimations via simulations and real-world experiments. We observe that at the steady stage, a BT topology has short distances and low clustering coefficients, and its degree-frequency exhibits a Gaussian-like distribution. These indicate that a BT network is very close to a random network rather than a scale-free network or a small world. The proportion of peers with large download percentages is very high at the steady stage, showing that the swarm is robust from the resource perspective. We also find out that most high-degree peers have a very fast download speed. However, the low Spearman's rank correlation coefficient indicates that there is no strong correlation between the peer connection degree and the download speed. Different from previous results, we find that the diameter of a BT network at the initial stage is small even when 95% of peers use the peer exchange extension. 1983-2012 IEEE. Scopus 2-s2.0-84930209164

Private BitTorrent (PT) is a new trend in Peer-to-Peer file sharing system, which provides high incentives for its users to seed after download by maintaining an upload-to-download ratio in the tracker for each registered community member. From the data we collected from six active PT sites, we discover that the population of both users and contents in any single PT site is much less than the public BitTorrent, and the intersection of content sets in different PTs is quite small. Based on this observation, we propose a content sharing/distribution framework among PTs (named CrossPT), as well as its sharing mechanism. In addition, we investigate the sharing strategy of the PT participants in CrossPT using game theory and the fetch strategy by modeling the scenario to a Neighbor Selection Problem (NSP). We prove NSP to be NP-complete and propose a heuristic algorithm to solve it. The evaluations with the input of crawled data from six PT sites demonstrate the efficiency of our mechanism. The content sizes of the six PT sites can be increased by 113.95%-438.46% with CrossPT. Also, the content distribution process can be done in less than one second, excluding the delivery time of the content itself.

Peer-to-Peer (P2P) networks have been widely used in various Internet applications. However, P2P networks also cause serious concerns of copyrighted contents piracy: P2P helps to pirate copyrighted contents, which impedes wide application of P2P networks. In this paper, we investigate several important issues on the ways to prevent pirated content propagation in P2P networks. We propose a system to stop pirated content propagation by utilizing several attacks to BitTorrent (BT). First, we design a system that can handle a large number of concurrent connections to reduce bandwidth consumption. Second, we build two mathematical models for BT attacks, including leechers behavior model and fake-block behavior model, and we analyze the performance of the system using these models. Third, we optimize BT clients by taking into account different implementations and counter-measure designs. We conducted several experiments in real networks, the results of which verified that our system is suitable for most current BT clients, and BT clients' download duration is extended at least three times longer, which is much better than the results reported in the literature.

Using new wireless capabilities in vehicles, various applications have appeared in Vehicular Ad Hoc Networks (VANETs). Multimedia data sharing is one of these applications, which has recently been given so much attention. Most of presented schemes in this field have focused on direct opportunistic meetings between vehicles or request/response broadcast in the whole network, which are inefficient and un-scalable due to VANET characteristics. In this paper, we propose an ID-based Scalable and EFficient distributed File sharing technique that increases efficiency and scalability via taking advantages of BitTorrent protocol and consistent hashing technique. The results of simulations show that our approach increases the received file ratio, reduces total download time of files and message overhead. Consequently, it can enhance efficiency and performance.

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.

Our understanding for the traffic behaviors on P2P networks is, unfortunately, still incomplete in the sense that the current studies on traffic measurement primarily focus on the traffic in large, and insufficient efforts have been devoted to the investigation of the inter-peer traffic. Toward resolving this issue, we in this paper propose and implement a method for measuring the traffic between any individual peers. Through deploying this measurement method on the PlanetLab platform, traffic data are collected and analyzed in the following aspects: data correctness, Poisson property, traffic self-similarity of individual peers, and traffic self-similarity of the BT system. Results of these analyses suggest that the proposed method is feasible, effective, and can be extended to larger networks.

Existing IP anonymity systems tend to sacrifice one of low latency, high bandwidth, or resistance to traffic-analysis. High-latency mix-nets like Mixminion batch messages to resist traffic-analysis at the expense of low latency. Onion routing schemes like Tor deliver low latency and high bandwidth, but are not designed to withstand traffic analysis. Designs based on DC-nets or broadcast channels resist traffic analysis and provide low latency, but are limited to low bandwidth communication. In this paper, we present the design, implementation, and evaluation of Aqua, a high-bandwidth anonymity system that resists traffic analysis. We focus on providing strong anonymity for BitTorrent, and evaluate the performance of Aqua using traces from hundreds of thousands of actual BitTorrent users. We show that Aqua achieves latency low enough for efficient bulk TCP flows, bandwidth sufficient to carry BitTorrent traffic with reasonable efficiency, and resistance to traffic analysis within anonymity sets of hundreds of clients. We conclude that Aqua represents an interesting new point in the space of anonymity network designs.

BitTorrent swarms rely on reciprocative chunk exchanges among autonomously participating peers. It has been shown that BitTorrent native tit-for-tat mechanism cannot effectively discourage the peer strategic misbehavior such as free-riding and fake chunk attack. This paper proposes a hierarchical chunk cipher scheme based only on bits circular shifting manipulation. As such, encrypted chunks preserve a fraction of information entropy of original chunks that can be observed by the receiving peers directly, which is used for assuring authenticity of the encrypted chunks. Our hierarchical bits shifting scheme allows more flexibility on the fraction of information entropy exposed directly by the encrypted chunks, when compared to the single layer bits shifting scheme. Further, exact mathematical results between the hierarchical scheme and the single layer scheme are derived and analyzed in detail.