Peer-To-Peer Storage
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JULIAN ASSANGE: When Google Met Wikileaks
JULIAN ASSANGE JULIAN +OR Books Email Images Behind Google’s image as the over-friendly giant of global tech when.google.met.wikileaks.org Nobody wants to acknowledge that Google has grown big and bad. But it has. Schmidt’s tenure as CEO saw Google integrate with the shadiest of US power structures as it expanded into a geographically invasive megacorporation... Google is watching you when.google.met.wikileaks.org As Google enlarges its industrial surveillance cone to cover the majority of the world’s / WikiLeaks population... Google was accepting NSA money to the tune of... WHEN GOOGLE MET WIKILEAKS GOOGLE WHEN When Google Met WikiLeaks Google spends more on Washington lobbying than leading military contractors when.google.met.wikileaks.org WikiLeaks Search I’m Feeling Evil Google entered the lobbying rankings above military aerospace giant Lockheed Martin, with a total of $18.2 million spent in 2012. Boeing and Northrop Grumman also came below the tech… Transcript of secret meeting between Julian Assange and Google’s Eric Schmidt... wikileaks.org/Transcript-Meeting-Assange-Schmidt.html Assange: We wouldn’t mind a leak from Google, which would be, I think, probably all the Patriot Act requests... Schmidt: Which would be [whispers] illegal... Assange: Tell your general counsel to argue... Eric Schmidt and the State Department-Google nexus when.google.met.wikileaks.org It was at this point that I realized that Eric Schmidt might not have been an emissary of Google alone... the delegation was one part Google, three parts US foreign-policy establishment... We called the State Department front desk and told them that Julian Assange wanted to have a conversation with Hillary Clinton... -
Replication Strategies for Streaming Media
“replication-strategies” — 2007/4/24 — 10:56 — page 1 — #1 Research Report No. 2007:03 Replication Strategies for Streaming Media David Erman Department of Telecommunication Systems, School of Engineering, Blekinge Institute of Technology, S–371 79 Karlskrona, Sweden “replication-strategies” — 2007/4/24 — 10:56 — page 2 — #2 °c 2007 by David Erman. All rights reserved. Blekinge Institute of Technology Research Report No. 2007:03 ISSN 1103-1581 Published 2007. Printed by Kaserntryckeriet AB. Karlskrona 2007, Sweden. This publication was typeset using LATEX. “replication-strategies” — 2007/4/24 — 10:56 — page i — #3 Abstract Large-scale, real-time multimedia distribution over the Internet has been the subject of research for a substantial amount of time. A large number of mechanisms, policies, methods and schemes have been proposed for media coding, scheduling and distribution. Internet Protocol (IP) multicast was expected to be the primary transport mechanism for this, though it was never deployed to the expected extent. Recent developments in overlay networks has reactualized the research on multicast, with the consequence that many of the previous mechanisms and schemes are being re-evaluated. This report provides a brief overview of several important techniques for media broad- casting and stream merging, as well as a discussion of traditional IP multicast and overlay multicast. Additionally, we present a proposal for a new distribution system, based on the broadcast and stream merging algorithms in the BitTorrent distribution and repli- cation system. “replication-strategies” — 2007/4/24 — 10:56 — page ii — #4 ii “replication-strategies” — 2007/4/24 — 10:56 — page iii — #5 CONTENTS Contents 1 Introduction 1 1.1 Motivation . -
Bittorrent Files Hace Stopped Downloading
bittorrent files hace stopped downloading Why Some Torrents Don’t Download? A torrent that doesn’t start downloading or one that suddenly stops can be very frustrating. You check your Internet connection, the cables, and everything looks good. So what can be the reasons for those torrents that don’t seem to work? Some Torrents Don’t Download. The main reason behind a torrent file that doesn’t even start downloading is the lack of seeders and peers. In other words, there is no one seeding that file, meaning there’s no place where you can download it from. That’s why it’s very important that you have a look at the number of seeders and peers every time you start a new download. Seeders are the users who already finished downloading and are only sharing. The peers are the ones like you, the ones who are downloading and uploading at the same time. Some Files Suddenly Stop Downloading. This is another common scenario. We’ve all been there when a torrent stops at some moment, such as 99%. That usually happens when there are only peers, but no seeders . If you think about it, it makes total sense. The peers have many parts of the torrent in common, and they will share those between them. But because there are zero seeders, no one has the entire file , and everyone will share the same parts and stop in the same percentage point. A Dead Torrent. Both of the situations we just saw are what users in the community call a “dead torrent”. -
Improving Fairness in Peer-To-Peer Networks by Separating the Role of Seeders in Network Infrastructures
Turkish Journal of Electrical Engineering & Computer Sciences Turk J Elec Eng & Comp Sci (2016) 24: 2255 { 2266 http://journals.tubitak.gov.tr/elektrik/ ⃝c TUB¨ ITAK_ Research Article doi:10.3906/elk-1402-304 Improving fairness in peer-to-peer networks by separating the role of seeders in network infrastructures Alireza NAGHIZADEH∗, Reza EBRAHIMI ATANI Department of Computer Engineering, Faculty of Engineering, University of Guilan, Rasht, Iran Received: 27.02.2014 • Accepted/Published Online: 08.07.2014 • Final Version: 15.04.2016 Abstract:Fairness is one of the most important challenges that should be considered as a priority when designing a P2P file-sharing network. An unfair P2P network may attract free-riders, frustrate the majority of users, and consequently shorten the longevity of files. When BitTorrent protocol was first introduced, by suggesting new algorithms like tit-for- tat or rarest-first and combining them with methods like choking and unchoking, it pushed fairness one step forward. However, BitTorrent did not bring a plenary solution and has its own shortcomings. For instance, neither this protocol nor other P2P protocols that we are aware of precisely indicate how seeders should be treated in their networks. Most of the time they dictate that seeders upload as much as possible. With this approach, seeders can easily be abused by free-riders. It gets even worse when we realize that for lack of a good infrastructure a lawful user may become a free-rider unknowingly. The purpose of this paper is to address this problem by suggesting a novel and universal method that can be implemented in current P2P networks. -
P2P File Sharing P2P File Sharing
P2P File Sharing P2P file sharing Alice chooses one of the peers, Bob. File is copied from Bob’s PC to Example Alice’s notebook: HTTP Alice runs P2P client While Alice downloads, other application on her notebook users uploading from Alice. computer Alice’s peer is both a Web client Intermittently connects to and a transient Web server. Internet; gets new IP address All peers are servers = highly for each connection scalable! Asks for “Hey Jude” Application displays other peers that have copy of Hey Jude. P2P: centralized directory (Napster’s Approach) Bob centralized directory server original “Napster” design 1 1) when peer connects, it peers 1 informs central server: IP address 1 3 content 2 1 2) Alice queries for “Hey Jude” 3) Alice requests file from Alice Bob P2P: problems with centralized directory file transfer is Single point of failure decentralized, but locating content is Performance highly decentralized bottleneck Copyright infringement Query flooding: Gnutella overlay network: graph edge between peer X fully distributed and Y if there’s a TCP no central server connection public domain all active peers and protocol edges is overlay net many Gnutella clients Edge is not a physical implementing protocol link Given peer will typically be connected with < 10 overlay neighbors Gnutella: protocol Ì File transfer: Query message HTTP sent over existing TCP connections Query Ì peers forward QueryHit Query message Ì QueryHit sent over reverse Query path QueryHit Scalability: limited scope flooding Gnutella: Peer joining 1. Joining peer X must find some other peer in Gnutella network: use list of candidate peers 2. -
Compsci 514: Computer Networks Lecture 21-2: from Bittorrent to Bittyrant Problem Statement
CompSci 514: Computer Networks Lecture 21-2: From BitTorrent to BitTyrant Problem Statement ... Server • One-to-many content distribution – Millions of clients downloading from the same server Evolving Solutions • Observation: duplicate copies of data are sent • Solutions – IP multicast – End system multicast – Content distribution networks e.g. Akamai – P2P cooperative content distribution • Bittorrent etc. IP multicast • End systems join a multicast group • Routers set up a multicast tree • Packets are duplicated and forwarded to multiple next hops at routers • Multicast pros and cons End system multicast • End systems rather than routers organize into a tree, forward and duplicate packets • Pros and cons Content distribution networks • Akamai – Works well but expensive, requires infrastructure support Peer-to-Peer Cooperative Content Distribution u Use the client’s uplink bandwidth u New problem: incentives for cooperation or how to motivate clients to upload The Gnutella approach u All nodes are true peers u A peer is the publisher, the uploader and the downloader. u No single point of failure. u Efficiency and scalability issue: u File searches span across a large number of nodes generating lots of traffic. u Integrity, i.e.content pollution issue: u Anyone can claim that he publishes valid content u No guarantee of quality of objects u Incentive issue: u No incentives for cooperation (free-riding in Gnutella) Outline u Problem of Content Distribution u The BitTorrent approach u BitTyrant BitTorrent overview Tracker 1 2 3 Leecher A Seeder Leecher C Leecher B u File is divided into chunks (e.g. 256KB) uShA1 hashes of all the pieces are included in the .torrent file for integrity check uA chunk is divided into sub-pieces to improve efficiency u Seeders have all chunks of the file u Leechers have some or no chunks of the file BitTorrent overview Tracker 1 2 3 Leecher A Seeder Leecher C Leecher B u File is divided into chunks (e.g. -
Exploiting Bittorrent for Fun (But Not Profit)
Exploiting BitTorrent For Fun (But Not Profit) Nikitas Liogkas, Robert Nelson, Eddie Kohler, and Lixia Zhang University of California, Los Angeles fnikitas, rlnelson, kohler, [email protected] ABSTRACT the file can be downloaded from different peers. A meta- This paper assesses BitTorrent’s robustness against selfish peers, data file is associated with every download. This file con- who try to download more than their fair share by abusing existing tains information necessary for the download process, in- protocol mechanisms. We design and implement three selfish-peer cluding the number of pieces and hashes for all the pieces; exploits and evaluate their effectiveness on public and private tor- the hashes are used by peers to verify that a piece has been rents. In practice, BitTorrent appears quite robust against this kind received correctly. This metadata file is typically created by of exploit: selfish peers can sometimes obtain more bandwidth, and the content provider, who must also launch at least one client honest peers’ download rates suffer slightly in consequence, but we offering the entire file for download. In order to join the observe no considerable degradation of the system’s quality of ser- download process, a client retrieves the metadata file out of vice. We identify private-torrent scenarios in which a selfish peer band, usually either from a well-known website or by email. could benefit more significantly at the expense of honest peers, and It then contacts the tracker, a centralized component that discuss the BitTorrent protocol mechanisms that lead to robustness by rendering these scenarios infeasible. keeps track of all the peers participating in the download. -
Peer-To-Peer Networking
Peer-to-Peer Networking Case Study: BitTorrent Lecture Content BitTorrent (protocol version 1.0) File transfer protocol Novel techniques for distributing content P2P system studied further The original design Later enchantments are not discussed here BitTorrent (BT) BT is a file transfer protocol for content distribution Protocol specifications v1.0 studied here A centralised P2P system (compare to Napster) A tracker server managing users© downloads BitTorrent concentrates on efficient file transfer Searching content is not provided by the protocol specification, but out-of-band methods Addresses the free riding problem in P2P file sharing BT Terminology (1/3) Torrent Set of peers cooperating to download the same content using BT protocol Tracker Centralised server keeping track of current participants. Does not involve to data transfers, but collect statistics Pieces and blocks File is cut into fixed size pieces (typically 256 KB) and pieces are further cut into blocks (transfer unit, 16 KB) BT Terminology (2/3) Metainfo file, or .torrent file Contains information about the file, its length, name and the address and port of the tracker Hashes for pieces of files for verification Interested and Choked A is marked as interested in peer B when B has pieces that A wants, and vice versa. Also, A is choked, when B decides not to upload data when A is interested. When B is willing to upload again, A is unchoked. BT Terminology (3/3) Peer set or a swarm The group of machines that are collectively connected for a particular file, i.e. a list of open TCP connections Leecher and seed Leecher is a peer that is still downloading the pieces. -
Online Music Communities: Challenging Sexism, Capitalism, and Authority in Popular Music
ONLINE MUSIC COMMUNITIES ONLINE MUSIC COMMUNITIES: CHALLENGING SEXISM, CAPITALISM, AND AUTHORITY IN POPULAR MUSIC By PAUL ALEXANDER AITKEN, B.FA. A Thesis Submitted to the School of Graduate Studies in Partial Requirements for the Degree Master of Arts McMaster University © Copyright by Paul Alexander Aitken, September 2007 MASTER OF ARTS (2007) McMaster University (Music Criticism) Hamilton, Ontario TITLE: Online Music Communities: Challenging Sexism, Capitalism, and Authority in Popular Music AUTHOR: Paul Alexander Aitken, B.FA. (York University) SUPERVISOR: Dr. Christina Baade NUMBER OF PAGES: vii, 167 ii ABSTRACT With its almost exclusive focus on the economics of the music industry, the early-21 st century debate over digital music piracy has obscured other vital areas of study in the relationship between popular music and the Intemet. This thesis addresses some of these neglected areas, specifically issues of agency, representation, discipline, and authority; it examines each of these in relationship to the formation and maintenance different online music communities. I argue that contemporary online trends related to music promotion, consumption, and criticism are, in fact, part of a much larger socio-cultural re-envisioning of the relationships between artists and audiences, artists and the music industry, and among audience members themselves. The relationship between music and the Intemet is not only subversive on the level of economics. I examine these issues in three key areas. Independent women's music cOlmnunities challenge patriarchal authority in the music industry as they use online discussion forums and web sites to advance their own careers. The tension that exists between the traditional for-profit music industry and the developing ethic of sharing in the filesharing community creates the conditions whereby we can imagine aItemative ways that music can circulate in culture. -
Peer-To-Peer Networks – Protocols, Cooperation and Competition
Peer-to-Peer Networks – Protocols, Cooperation and Competition Hyunggon Park Signal Processing Laboratory (LTS4), Institute of Electrical Engineering, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland Rafit Izhak Ratzin Computer Science Department, University of California, Los Angeles (UCLA), Los Angeles, USA Mihaela van der Schaar Multimedia Communications and Systems Laboratory, Electrical Engineering Department, University of California, Los Angeles (UCLA), Los Angeles, USA 1. INTRODUCTION Peer-to-peer (P2P) networks connect many end-hosts (also referred to as peers) in an ad-hoc manner. P2P networks have been typically used for file sharing applications, which enable peers to share digitized content such as general documents, audio, video, electronic books, etc. Recently, more advanced applications such as real-time conferences, online gaming, and media streaming have also been deployed over such networks. Unlike traditional client-server networks, where servers only provide content, and clients only consume content, in P2P networks, each peer is both a client and a server. It has been observed that P2P file sharing applications dominate Internet traffic usage. In fact, a wide range of measurements, which were performed in 8 different geographic regions during the years of 2008-2009, show that P2P networks generated most of the traffic in all monitored regions, ranging from 43% in Northern Africa to 70% in Eastern Europe (http://www.ipoque.com/). The same study also identified that BitTorrent (Cohen, 2003) is the most popular protocol on the Internet, generating most of the traffic in 7 out of 8 regions ranging from 32% in South Africa to 57% in Eastern Europe. The details of the BitTorrent protocol will be discussed in Section 3. -
Libswift P2p Protocol: an Analysis and Extension
Master Thesis - TRITA-ICT-EX-2012-262 LIBSWIFT P2P PROTOCOL: AN ANALYSIS AND EXTENSION Fu Tang Design and Implementation of ICT products and systems Royal Institute of Technology (KTH) [email protected] October 30th, 2012 Supervisor: Flutra Osmani Examiner: Bj¨ornKnutsson Department: ICT School, NSLab Royal Institute of Technology (KTH) 1 Abstract More and more end-users are using P2P protocols for content sharing, on-demand and live streaming, contributing considerably to overall Internet traffic. A novel P2P streaming protocol named libswift was developed to enable people experience a better service by consuming less resources and transferring less unnecessary functions and metadata. This master thesis studies the inner functioning of libswift and analyzes some of the vulnerabilities that directly impact performance of the protocol, namely download speed and response delay. By investigating the behavior of libswift in scenarios with multiple peers, we found that the lack of a peer selection mechanism inside the protocol affects download efficiency and response time. We also discovered that libswift's internal piece picking algorithm raises competition among peers, thus not fully utilizing connected peers. In addition, we found that current libswift implementation does not follow the specification for PEX peer discovery, thus we modified PEX algorithm to support another message that is used to proactively request new peers from the currently connected. Having made these observations, we designed and implemented a peer selection extension interface that allows for third-party peer selection mechanisms to be used with libswift protocol. Apropos, we tested the interface (or adapter) with an example peer selection mechanism that groups peers according to properties such as latency and locality. -
Thèse De Doctorat De
Thèse de doctorat de L’UNIVERSITÉ DE RENNES 1 Comue Université Bretagne Loire École Doctorale N° 601 Mathématiques et Sciences et Technologies de l’Information et de la Communication Spécialité : Informatique Par Adrien LUXEY Les e-squads : Un nouveau paradigme pour la conception d’applications ubiquitaires respectant le droit à la vie privée Thèse présentée et soutenue à Rennes (France), le 29 Novembre 2019 Unité de recherche : Irisa (UMR 6074) Rapporteurs avant soutenance : Romain ROUVOY Professeur des Universités Université de Lille Vivien QUÉMA Professeur des Universités Grenoble INP Composition du Jury : Présidente : Anne-Marie KERMARREC Directrice de recherche Univ Rennes, CNRS, Inria, IRISA Rapporteurs : Romain ROUVOY Professeur des Universités Université de Lille Vivien QUÉMA Professeur des Universités Grenoble INP Examinatrice : Sonia BEN MOKHTAR Directrice de recherche CNRS Lyon Dir. de thèse : Yérom-David BROMBERG Professeur des Universités Univ Rennes, CNRS, Inria, IRISA Notre héritage n’est précédé d’aucun testament. René Char Technology is neither good nor bad; nor is it neutral. Melvin Kranzberg A tenured scientist Table of Contents 1 Introduction7 2 State of the Art 11 2.1 ‘Privacy is dead’ ... in the cloud........................ 12 2.2 Today’s alternatives............................... 13 2.2.1 The edge cloud: a poor diversion................... 13 2.2.2 Decentralised networks......................... 13 2.3 The multi-device paradigm........................... 17 2.4 The path toward e-squads........................... 18 3 Fluid user interactions inside the e-squad 21 3.1 Introducing Sprinkler ............................ 21 3.2 Our approach.................................. 23 3.2.1 Solution outline............................. 23 3.2.2 Decentralized knowledge aggregation................. 26 3.2.3 The Session Handoff algorithm...................