103 research outputs found
LiveShift: mesh-pull P2P live and time-shifted 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 overlay. 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 technical report describes an architecture, a mesh-pull protocol, and a set of policies that support the envisioned use case enable. User-focused evaluation results show its effectiveness and limits in terms of quality of experience
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
Search for Neutral Supersymmetric Higgs Bosons in Collisions at TeV
We present the results of a search for neutral Higgs bosons produced in
association with quarks in
final states with pb of collisions at
TeV recorded by the Collider Detector at Fermilab. We find no
evidence of such a signal and the data is interpreted in the context of the
neutral Higgs sector of the Minimal Supersymmetric extension of the Standard
Model. With basic parameter choices for the supersymmetric scale and the stop
quark mixing, we derive 95% C.L. lower mass limits for neutral Higgs bosons for
\tb values in excess of 35.Comment: 2 tex files 3 figure
Preparing construction supply chains for blockchain technology:An investigation of its potential and future directions
Blockchain, a peer-to-peer, controlled, distributed database structure, has the potential to profoundly affect current business transactions in the construction industry through smart contracts, cryptocurrencies, and reliable asset tracking. The construction industry is often criticized for being slow in embracing emerging technologies and not effectively diffusing them through its supply chains. Often, the extensive fragmentation, traditional procurement structures, destructive competition, lack of collaboration and transparency, low-profit margins, and human resources are shown as the main culprits for this. As blockchain technology makes its presence felt strongly in many other industries like finance and banking, this study investigates the preparation of construction supply chains for blockchain technology through an explorative analysis. Empirical data for the study were collected through semistructured interviews with 17 subject experts. Alongside presenting a strengths, weaknesses, opportunities, and threats analysis (SWOT), the study exhibits the requirements for and steps toward a construction supply structure facilitated by blockchain technology
Game theoretical analysis of incentives for large-scale, fully decentralized collaboration networks
One of the key challenges in peer-to-peer networks is the design of incentives to encourage peers to share their resources. Incentives are necessary in order to exploit the full potential of these systems. The tit-for-tat incentive scheme, as used in BitTorrent for example, has proven to be a successful approach in P2P file sharing systems, where peers have direct relations and share the same kind of resources. However, in P2P systems where different kind of resources are shared between peers with non-direct relations, the design of incentives remains a challenge. In this paper, a large-scale, fully decentralized P2P collaboration network is shown, where peers share not only bandwidth and storage space, but also contribute by editing articles and voting for or against changes. A new incentive scheme is proposed which supports non-direct relations and provides incentives for sharing different kind of resources. The incentive scheme is based on a reputation system that assigns a reputation value to every peer reflecting its previous behavior in the network. Based on this value, the service level is differentiated, i.e. the higher a peer's reputation the better the quality of service it can get from the network. The service differentiation has been analyzed and simulated with rational, irrational and altruistic peers based on game theory concepts
PeerCollaboration
Increasing traffic due to increased bandwidth or the number of users calls for scalable systems, which can be built with peer-to-peer (P2P) mechanisms. Scalability is a key issue for systems that rely on many participants, such as large-scale collaboration system. This paper introduces PeerCollaboration, a fully decentralized P2P collaboration system for documents, which is robust against malicious behavior, provides an efficient content search, and offer mechanisms for distributed control. Typical tasks in PeerCollaboration are searching, retrieving, creating, changing, and maintaining documents in a collaborative manner. Three problem areas are investigated within this system. The first problem focuses on similarity search on top of existing P2P networks and highlights a novel algorithm, which outperforms compared approaches. The second problem deals with incentive schemes, which work with indirect reciprocity. Thus, the novel and robust incentive scheme finds more reciprocities than with compared approaches. The third problem focuses on user-based voting mechanisms
Abstract
Fast similarity search is important for time-sensitive applications. Those include both enterprise and web scenarios, where typos, misspellings, and noise need to be removed in an efficient way, in order to improve data quality, or to find all information of interest to the user. This paper presents a new algorithm called Fast Similarity Search (FastSS) that performs an exhaustive similarity search in a dictionary, based on the edit distance model of string similarity. The algorithm uses deletions to model the edit distance. For a dictionary containing n words of average length m, and given a maximum number of spelling errors k, FastSS uses a deletion dictionary of size O(nm k). At search time each query is mutated to generate a deletion neighborhood of size O(m k), which is compared to the indexed deletion dictionary. As a deletion neighborhood is smaller than a neighborhood using deletions, insertions and replacements, this contributes to a faster search. FastSS looks up misspellings in a time which is independent of n fo
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
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