Real P2P Systems Research Articles

Collaborative SVM classification in scale-free peer-to-peer networks

Distributed classification in large-scale P2P networks has gained relevance in recent years and support applications like distributed intrusion detection in P2P monitoring environments, online match-making, personalized information retrieval, distributed document classification in a P2P media repository and P2P recommender systems to mention a few. However, classification in a P2P network is a challenging task due to the constraints such as centralization of data is not feasible, scarce communication bandwidth, scalability, synchronization and peer dynamism. Moreover, without considering data distributions and topological scenarios of real world P2P systems, most of the existing distributed classification approaches lack in their predictive and network-cost performance. In this paper, we investigate a collaborative classification method (TRedSVM) based on Support Vector Machines (SVM) in Scale-free P2P networks. In particular, we demonstrate how to construct SVM classifier in real world P2P networks which exhibit inherently skewed distribution of node links and eventually data. The proposed method propagates the most influential instances of SVM models to the vast majority of scarcely connected peers in a controlled way that improves their local classification accuracy and, at the same time, keeps the communication cost low throughout the network. Besides using benchmark Machine Learning data sets for extensive experimental evaluations, we have evaluated the proposed method particularly for music genre classification to exhibit its performance in a real application scenario. Additionally, performance analysis is carried out with respect to centralized approaches, data replication in P2P networks and cost accuracy trade-off. TRedSVM outperforms baseline approaches of model propagation by improving the overall classification performance substantially at the cost of a tolerable increase in communication.

CDNPatch: a cost‐effective failover mechanism for hybrid CDN‐P2P live streaming systems

SummaryAmong the most well‐established live media distribution technologies is content delivery network (CDN), which improves user‐perceived quality of service by delivering content from proxy servers deployed at the Internet's edge. In recent years, CDN providers started to tap into their subscribers' peer‐to‐peer (P2P) capacity to alleviate their server costs. Under the inherent peer dynamics, a major challenge of these hybrid CDN‐P2P systems is to provide efficient failure recovery with good quality of service guarantees at a reduced server cost. In this work we propose a cost‐effective failover solution named CDNPatch to address the aforementioned problem. CDNPatch enables peers to periodically precompute a few backup content suppliers by efficient information exchange and maintenance algorithms, and leverages auxiliary CDN servers and an economic server provisioning algorithm to reduce the chance of playback interruption occurring to peers. Our simulation results show that CDNPatch can mask the impact of peer dynamics of 3 real P2P systems, namely, SOPCast, PPStream, and PPTV, with 100 % failure recovery success rate and a failure recovery time less than 1 second at a cost of small P2P communication overhead of less than 1 kilobits per second, while using only 10%, 21%, and 51%, respectively, of the pure CDN scheme's server consumption.

Understanding the effects of P2P dynamics on trust bootstrapping

Reputation and trust systems rely on historical information to account for uncertainty about the intention of users to cooperate. In open, dynamic systems like peer-to-peer (P2P) networks, however, forming trust relationships is often a lengthy and time consuming effort due to the anonymous and discontinuous participation of users. For example, the flow of transactions may be interrupted by unexpected user departures, precluding trustors from gaining the necessary experience to make an accurate trust evaluation. The problem is further complicated in the case that no previous direct and reputational evidence is available. This happens, for instance, when a new user joins the system for the first time or users form short-term, ad hoc groups around a shared goal, which is very common in P2P networks. In these cases, the problem is how to minimize the time to bootstrap trust between volatile users who are unknown to one another.To shed light on this question, this paper presents an accurate model for capturing the influence of churn – the continuous process of node arrival and departure – on trust bootstrapping. Using our analytical model, we show that churn can be very problematic in real P2P systems and develop equations that allow system architects to compute the minimal transaction rate that achieves quick bootstrapping of trust. Also, we present an example of how our analytical framework can be used to design a viable solution for the trust bootstrapping problem in dynamic settings. The core idea is that users ask their social links to transact with strangers and together generate trust evaluations in a short time scale. Finally, we verify our theoretical results by simulation and confirm how a simple application of our framework can reduce bootstrapping times by 50% in environments with high churn rates.

Robust mobile video streaming in a peer-to-peer system

In a peer-to-peer (P2P) video streaming system, peers not only consume video, but also route it to other peers in the system, where ordinary peers are assumed to have sufficient downlink speed and media capability. This assumption often fails when the P2P system consists of peers that are heterogeneous in their computing power, hardware, and media capability.In this paper, we address a problem of streaming video to mobile devices, which are less capable than ordinary peers. In order to stream video to mobile devices, transcoding is often required to render video suitable for their small display, limited downlink speed, and limited video decoding capability. However, performing transcoding at a single peer is vulnerable to peer churn, which leads to video disruption. We propose interleaved distributed transcoding (IDT), a robust video encoding scheme that allows peers more capable than mobile devices to perform transcoding in a collaborative fashion. IDT is designed in such a way that transcoded substreams are assembled into a single video stream, which can be decoded by any H.264/AVC baseline profile compliant decoder. Extensive simulations and its implementation in a real P2P system demonstrate that the proposed scheme not only reduces computational load at a peer, but also achieves robust streaming in the case of peer failure or packet loss due to adverse wireless channel conditions. We confirm this finding by analyzing the effect of distributed transcoding under peer failure.

Simulation-based development of Peer-to-Peer systems with the RealPeer methodology and framework

In the process of developing Peer-to-Peer (P2P) systems, simulation has proved to be an essential tool for the evaluation of existing and conceived P2P systems. So far, in practice, there has been a clear separation between a simulation model of a P2P system and a real P2P system that operates on a real physical network. This separation hinders the transition of models to real systems and the evaluation of already deployed systems by means of simulation. To bridge this gap, we put forward the idea of simulation-based development of P2P systems. In this approach, an initial simulation model of a P2P system is iteratively transformed into the intended real P2P system. As a concretion of this approach, we propose a methodology and a framework for the simulation-based development of P2P systems. The presented framework effectively supports a developer in modelling, simulating and ultimately developing P2P systems. We demonstrate the validity of our approach and the framework by constructing an example P2P application. This application is simulated in a series of experiments as well as deployed in a large-scale internet-based P2P system.

Distance browsing in distributed multimedia databases

The state of the art of searching for non-text data (e.g., images) is to use extracted metadata annotations or text, which might be available as a related information. However, supporting real content-based audiovisual search, based on similarity search on features, is significantly more expensive than searching for text. Moreover, such search exhibits linear scalability with respect to the dataset size, so parallel query execution is needed. In this paper, we present a Distributed Incremental Nearest Neighbor algorithm ( DINN) for finding closest objects in an incremental fashion over data distributed among computer nodes, each able to perform its local Incremental Nearest Neighbor ( local-INN) algorithm. We prove that our algorithm is optimum with respect to both the number of involved nodes and the number of local-INN invocations. An implementation of our DINN algorithm, on a real P2P system called MCAN, was used for conducting an extensive experimental evaluation on a real-life dataset. The proposed algorithm is being used in two running projects: SAPIR and NeP4B.

Balancing Trust and Incentive in Peer-to-Peer Collaborative System

In order to maximize resource utilization as well as providing trust management in P2P computing environments, we propose a novel framework - Trust-Incentive Service Management (TIM). Having child model, club model, bid model and trust model, TIM is constructed based on role based price strategy. In this mechanism, providers set the price according to demand and supply, and consumers maximize the surplus upon budget and deadline. A weighted voting scheme is also proposed to secure the P2P system by declining the join request from malicious peers. TIM is scalable and efficient in that: (1) it is completely distributed without a central server; (2) it dynamically manages the price and service by integrating valuables of pricing, trust, and incentive. A TIM prototype has been successfully implemented in a real P2P system, CROWN. We evaluate the proposed approach through comprehensive experiments and achieve improved results in service allocation efficiency, system completion time, and aggregated resource utilization.

A Measurement Study of the Structured Overlay Network in P2P File-Sharing Systems

The architecture of P2P file-sharing applications has been developing to meet the needs of large scale demands. The structured overlay network, also known as DHT, has been used in these applications to improve the scalability, and robustness of the system, and to make it free from single-point failure. We believe that the measurement study of the overlay network used in the real file-sharing P2P systems can provide guidance for the designing of such systems, and improve the performance of the system. In this paper, we perform the measurement in two different aspects. First, a modified client is designed to provide view to the overlay network from a single-user vision. Second, the instances of crawler programs deployed in many nodes managed to crawl the user information of the overlay network as much as possible. We also find a vulnerability in the overlay network, combined with the character of the DNS service, a more serious DDoS attack can be launched.