Fabio Victora Hecht

LiveShift: Peer-to-Peer Live Streaming with Distributed Time-Shifting

The increasing assortment of devices with IP connectivity contributes to the high popularity of video sharing over the Internet. High traffic generated by such applications at the source can be better distributed using a peer-to-peer overlay, since every user forwards information to other users. Current implementations target either live or on demand video streaming. LiveShift is an application that combines both approaches. While video is transmitted through the peer-to-peer network in a live fashion, all peers participate in a distributed storage. This adds ability to replay time-shifted streams from other peers in a distributed and scalable manner. For the demonstration, a decentralized network is used, with peers running on EMANICSLab nodes and notebook computers.

CompactPSH: An efficient transitive TFT incentive scheme for Peer-to-Peer Networks

Incentive schemes in Peer-to-Peer (P2P) networks are necessary to discourage free-riding. One example is the Tit-for-Tat (TFT) incentive scheme, a variant of which is used in BitTorrent to encourage peers to upload. TFT uses data from local observations making it suitable for systems with direct reciprocity. This paper presents CompactPSH, an incentive scheme that works with direct and indirect reciprocity. CompactPSH allows peers to establish indirect reciprocity by finding intermediate peers, thus enabling trade with more peers and capitalizing on more resources. CompactPSH finds transitive paths while keeping the overhead of additional messages low. In a P2P file-sharing scenario based on input data from a large BitTorrent tracker, CompactPSH was found to exploit more reciprocity than TFT which enabled more chunks to be downloaded. As a consequence, peers are allowed to be stricter to fight white-washing without compromising performance.

LiveShift: Mesh-pull live and time-shifted P2P video streaming

The popularity of video sharing over the Internet has increased significantly. High traffic generated by such applications at the source can be better distributed using a peer-to-peer (P2P) overlay. Unlike most P2P systems, LiveShift combines both live and on-demand video streaming — while video is transmitted through the peer-to-peer network in a live fashion, all peers participate in distributed storage. This adds the ability to replay time-shifted streams from other peers in a distributed and scalable manner. This paper describes an adaptive fully-distributed mesh-pull protocol that supports the envisioned use case and a set of policies that enable efficient usage of resources, discussing interesting trade-offs encountered. User-focused evaluation results, including both channel switching and time shifting behavior, show that the proposed system provides good quality of experience for most users, in terms of infrequent stalling, low playback lag, and a small proportion of skipped blocks in all the scenarios studied, even in presence of churn.

B-Tracker: Improving load balancing and efficiency in distributed P2P trackers

Trackers are used in peer-to-peer (P2P) networks for provider discovery, that is, mapping resources to potential providers. Centralized trackers, e.g., as in the original BitTorrent protocol, do not benefit from P2P properties, such as no single point of failure, scalability, and load balancing. Decentralized mechanisms have thus been proposed, based on distributed hash tables (DHTs) and gossiping, such as BitTorrents Peer Exchange (PEX). While DHT-based trackers suffer from load balancing problems, gossip-based ones cannot deliver new mappings quickly. This paper presents B-Tracker, a fully-distributed, pull-based tracker. B-Tracker extends DHT functionality by distributing the tracker load among all providers in a swarm. Bloom filters are used to avoid redundant mappings to be transmitted. This results in the important properties of load balancing and scalability, while adding the ability for peers to fetch new mappings instantly. B-Tracker shows, through simulations, improved load balancing and better efficiency when compared to pure DHTs and PEX.

The Design and Evaluation of a Distributed Reliable File System

Peer-to-peer (P2P) systems are, in contrast to clientserver (C/S) systems, fault-tolerant, robust, and scalable. While C/S distributed file systems, such as NFS (Network File System) or SMB (Server Message Block), do not scale with respect to the number of clients and exhibit a single point of failure, P2P file systems have the potential to cope with an increasing number of participants. Thus, this paper presents DRFS (Distributed Reliable File System), a P2P file system for cooperative environments. DRFS uses random, content-independent identifiers for data storage, while maintaining high performance and low overhead with many concurrent reads and writes. A dynamic replication mechanism ensures data availability, even under high churn. The application scenario considers an office environment, where DRFS is installed on employees’ machines, who store and request files. DRFS has been implemented using the Filesystem in Userspace (FUSE) interface, in order to provide users with transparent read and write operations. Experiments show the benefits of such a peer-to-peer architecture, when a small number of peers reads or writes in parallel: DRFS performs better than NFS, as soon as 6 peers read or write in parallel a 32 MB file. For unpopular files, it is also more reliable than IgorFS.

PeerVote: A Decentralized Voting Mechanism for P2P Collaboration Systems

Peer-to-peer (P2P) systems achieve scalability, fault tolerance, and load balancing with a low-cost infrastructure, characteristics from which collaboration systems, such as Wikipedia, can benefit. A major challenge in P2P collaboration systems is to maintain article quality after each modification in the presence of malicious peers. A way of achieving this goal is to allow modifications to take effect only if a majority of previous editors approve the changes through voting. The absence of a central authority makes voting a challenge in P2P systems. This paper proposes the fully decentralized voting mechanism PeerVote, which enables users to vote on modifications in articles in a P2P collaboration system. Simulations and experiments show the scalability and robustness of PeerVote, even in the presence of malicious peers.

PSH: A Private and Shared History-Based Incentive Mechanism

Fully decentralized peer-to-peer (P2P) systems do not have a central control mechanism. Thus, different forms of control mechanisms are required to deal with selfish peers. One type of selfish behavior is the consumption of resources without providing sufficient resources. Therefore, incentive schemes encourage peers to share resources while punishing selfish peers. A well-known example of an incentive scheme is Tit-for-Tat (TFT), as used in BitTorrent. With this scheme, a peer can only consume as much resources as it provides. TFT is resilient to collusion due to relying on private histories only. However, TFT can only be applied to peers with direct reciprocity. This paper presents a private and shared history (PSH) based incentive mechanism, which supports transitive relations (indirect reciprocity). Furthermore, it is resilient to collusion and it combines private and shared histories in an efficient manner. The PSH approach uses a shared history for identifying transitive relations. Those relations are verified using private histories. Simulations show that the PSH mechanism has a higher transaction success ratio than TFT.

Radiommender: P2P on-line radio with a distributed recommender system

Radiommender is a fully-distributed, peer-to-peer on-line radio. Users can share their music collection and explore music collections of other users. The difference to current file sharing systems is that songs do not need to be searched individually - a distributed recommender system is used to estimate user preference. Recommendation is done with a combination of an implicit voting system that assigns songs to search terms and an affinity network that correlates user interest. The demonstration shows the software functionality and includes the visualization of affinity graphs built by the recommender system.

Value analysis of centralized and distributed communications and video streaming

Purpose – When comparing novel centralized and distributed communications and video streaming services, the authors identified a need for a theoretic framework to position a multitude of ICT services and technologies according to their value proposition. Literature does not integrate existing value analysis concepts into a holistic theoretical framework. This paper aims to address this shortcoming by proposing a value analysis framework for ICT services capable of describing the value exchanges between different actors and their role constellations based on technological componentizations.Design/methodology/approach – The paper evaluates a representative selection of communications and video streaming services and an extensive literature study on existing value analysis research was conducted to develop the framework and to verify it.Findings – The paper demonstrates the applicability of the value analysis framework in communications and video streaming case studies, which are technically very different f...

Playback policies for live and on-demand p2p video streaming

Peer-to-peer (P2P) has become a popular mechanism for video distribution over the Internet, by allowing users to collaborate on locating and exchanging video blocks. The approach LiveShift supports further collaboration by enabling storage and a later redistribution of received blocks, thus, enabling time shifting and video-on-demand in an integrated manner. Video blocks, however, are not always downloaded quickly enough to be played back without interruptions. In such situations, the playback policy defines whether peers (a) stall the playback, waiting for blocks to be found and downloaded, or (b) skip them, losing information. Thus, for the fist time this paper investigates in a reproducible manner playback policies for P2P video streaming systems. A survey on currently-used playback policies shows that existing playback policies, required by any streaming system, have been defined almost arbitrarily, with a minimal scientific methodology applied. Based on this survey and on major characteristics of video streaming, a set of five distinct playback policies is formalized and implemented in LiveShift. Comparative evaluations outline the behavior of those policies under both under- and over-provisioned networks with respect to the playback lag experienced by users, the share of skipped blocks, and the share of sessions that fail. Finally, playback policies with most suitable characteristics for either live or on-demand scenarios are derived.