Modeling and Evaluation of Multisource Streaming Strategies in P2P VoD Systems

In recent years, multimedia content distribution has largely been moved to the Internet, inducing broadcasters, operators and service providers to upgrade with large expenses their infrastructures. In this context, streaming solutions that rely on user devices such as set-top boxes (STBs) to offload dedicated streaming servers are particularly appropriate. In these systems, contents are usually replicated and scattered over the network established by STBs placed at users' home, and the video-on-demand (VoD) service is provisioned through streaming sessions established among neighboring STBs following a Peer-to-Peer fashion. Up to now the majority of research works have focused on the design and optimization of content replicas mechanisms to minimize server costs. The optimization of replicas mechanisms has been typically performed either considering very crude system performance indicators or analyzing asymptotic behavior. In this work, instead, we propose an analytical model that complements previous works providing fairly accurate predictions of system performance (i.e., blocking probability). Our model turns out to be a highly scalable, flexible, and extensible tool that may be helpful both for designers and developers to efficiently predict the effect of system design choices in large scale STB-VoD system

Relating Query Popularity and File Replication in the Gnutella Peer-to-Peer Network

In this paper, we characterize the user behavior in a peer-to-peer (P2P) file sharing network. Our characterization is based on the results of an extensive passive measurement study of the messages exchanged in the Gnutella P2P file sharing system. Using the data recorded during this measurement study, we analyze which queries a user issues and which files a user shares. The investigation of users queries leads to the characterization of query popularity. Furthermore, the analysis of the files shared by the users leads to a characterization of file replication. As major contribution, we relate query popularity and file replication by an analytical formula characterizing the matching of files to queries. The analytical formula defines a matching probability for each pair of query and file, which depends on the rank of the query with respect query popularity, but is independent of the rank of the file with respect to file replication. We validate this model by conducting a detailed simulation study of a Gnutella-style overlay network and comparing simulation results to the results obtained from the measurement

Predicting the Impact of Measures Against P2P Networks on the Transient Behaviors

The paper has two objectives. The first is to study rigorously the transient behavior of some P2P networks whenever information is replicated and disseminated according to epidemic-like dynamics. The second is to use the insight gained from the previous analysis in order to predict how efficient are measures taken against peer-to-peer (P2P) networks. We first introduce a stochastic model which extends a classical epidemic model and characterize the P2P swarm behavior in presence of free riding peers. We then study a second model in which a peer initiates a contact with another peer chosen randomly. In both cases the network is shown to exhibit a phase transition: a small change in the parameters causes a large change in the behavior of the network. We show, in particular, how the phase transition affects measures that content provider networks may take against P2P networks that distribute non-authorized music or books, and what is the efficiency of counter-measures.Comment: IEEE Infocom (2011

A HOLISTIC REDUNDANCY- AND INCENTIVE-BASED FRAMEWORK TO IMPROVE CONTENT AVAILABILITY IN PEER-TO-PEER NETWORKS

Peer-to-Peer (P2P) technology has emerged as an important alternative to the traditional client-server communication paradigm to build large-scale distributed systems. P2P enables the creation, dissemination and access to information at low cost and without the need of dedicated coordinating entities. However, existing P2P systems fail to provide high-levels of content availability, which limit their applicability and adoption. This dissertation takes a holistic approach to device mechanisms to improve content availability in large-scale P2P systems. Content availability in P2P can be impacted by hardware failures and churn. Hardware failures, in the form of disk or node failures, render information inaccessible. Churn, an inherent property of P2P, is the collective effect of the users’ uncoordinated behavior, which occurs when a large percentage of nodes join and leave frequently. Such a behavior reduces content availability significantly. Mitigating the combined effect of hardware failures and churn on content availability in P2P requires new and innovative solutions that go beyond those applied in existing distributed systems. To addresses this challenge, the thesis proposes two complementary, low cost mechanisms, whereby nodes self-organize to overcome failures and improve content availability. The first mechanism is a low complexity and highly flexible hybrid redundancy scheme, referred to as Proactive Repair (PR). The second mechanism is an incentive-based scheme that promotes cooperation and enforces fair exchange of resources among peers. These mechanisms provide the basis for the development of distributed self-organizing algorithms to automate PR and, through incentives, maximize their effectiveness in realistic P2P environments. Our proposed solution is evaluated using a combination of analytical and experimental methods. The analytical models are developed to determine the availability and repair cost properties of PR. The results indicate that PR’s repair cost outperforms other redundancy schemes. The experimental analysis was carried out using simulation and the development of a testbed. The simulation results confirm that PR improves content availability in P2P. The proposed mechanisms are implemented and tested using a DHT-based P2P application environment. The experimental results indicate that the incentive-based mechanism can promote fair exchange of resources and limits the impact of uncooperative behaviors such as “free-riding”

Toward Self-Organising Service Communities

This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.)

Characterizing the query behavior in peer-to-peer file sharing systems

This paper characterizes the query behavior of peers in a peer-to-peer (P2P) file sharing system. In contrast to previous work, which provides various aggregate workload statistics, we characterize peer behavior in a form that can be used for constructing representative synthetic workloads for evaluating new P2P system designs. In particular, the analysis exposes heterogeneous behavior that occurs on different days, in different geographical regions (i. e., Asia, Europe, and North America) or during different periods of the day. The workload measures include the fraction of connected sessions that are passive (i. e., issue no queries), the duration of such sessions, and for each active session, the number of queries issued, time until first query, query interarrival time, time after last query, and distribution of query popularity. Moreover, the key correlations in these workload measures are captured in the form of conditional distributions, such that the correlations can be accurately reproduced in a synthetic workload. The characterization is based on trace data gathered in the Gnutella P2P system over a period of 40 days. To characterize system-independent user behavior, we eliminate queries that are specific to the Gnutella system software, such as re-queries that are automatically issued by some client implementations to improve system responsiveness