DOCSLIB.ORG

CS 417 29 October 2018 Paul Krzyzanowski 1

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
CS 417 29 October 2018 Paul Krzyzanowski 1 CS 417 29 October 2018 Distributed Lookup • Look up (key, value) • Cooperating set of nodes Distributed Systems • Ideally: – No central coordinator 16. Distributed Lookup – Some nodes can be down Paul Krzyzanowski Rutgers University Fall 2018 October 29, 2018 © 2014-2018 Paul Krzyzanowski 1 October 29, 2018 © 2014-2018 Paul Krzyzanowski 2 Approaches 1. Central Coordinator 1. Central coordinator • Example: Napster – Napster – Central directory – Identifies content (names) and the servers that host it 2. Flooding – lookup(name) → {list of servers} – Download from any of available servers – Gnutella • Pick the best one by pinging and comparing response times 3. Distributed hash tables • Another example: GFS – CAN, Chord, Amazon Dynamo, Tapestry, … – Controlled environment compared to Napster – Content for a given key is broken into chunks – Master handles all queries … but not the data October 29, 2018 © 2014-2018 Paul Krzyzanowski 3 October 29, 2018 © 2014-2018 Paul Krzyzanowski 4 1. Central Coordinator - Napster 2. Query Flooding • Pros • Example: Gnutella distributed file sharing – Super simple – Search is handled by a single server (master) – The directory server is a single point of control • Well-known nodes act as anchors • Provides definitive answers to a query – Nodes with files inform an anchor about their existence – Nodes select other nodes as peers • Cons – Master has to maintain state of all peers – Server gets all the queries – The directory server is a single point of control • No directory, no service! October 29, 2018 © 2014-2018 Paul Krzyzanowski 5 October 29, 2018 © 2014-2018 Paul Krzyzanowski 6 Paul Krzyzanowski 1 CS 417 29 October 2018 2. Query Flooding Overlay network • Send a query to peers if a file is not present locally An overlay network is a virtual network formed by peer connections – Each request contains: – Any node might know about a small set of machines – “Neighbors” may not be physically close to you • Query key • Unique request ID • Time to Live (TTL, maximum hop count) • Peer either responds or routes the query to its neighbors – Repeat until TTL = 0 or if the request ID has been processed – If found, send response (node address) to the requestor – Back propagation: response hops back to reach originator Underlying IP Network October 29, 2018 © 2014-2018 Paul Krzyzanowski 7 October 29, 2018 © 2014-2018 Paul Krzyzanowski 8 Overlay network Flooding Example: Overlay Network An overlay network is a virtual network formed by peer connections – Any node might know about a small set of machines – “Neighbors” may not be physically close to you Overlay Network October 29, 2018 © 2014-2018 Paul Krzyzanowski 9 October 29, 2018 © 2014-2018 Paul Krzyzanowski 10 Flooding Example: Query Flood Flooding Example: Query response Query TTL=0 TTL=1 TTL=0 TTL=2 TTL=1 Result TTL=2 TTL=0 TTL=1 Result TTL=2 Result TTL=0 TTL=1 Found! Found! TTL=1 TTL=0 TTL=0 TTL=1 Back propagation TTL=0 TTL = Time to Live (hop count) October 29, 2018 © 2014-2018 Paul Krzyzanowski 11 October 29, 2018 © 2014-2018 Paul Krzyzanowski 12 Paul Krzyzanowski 2 CS 417 29 October 2018 Flooding Example: Download What’s wrong with flooding? • Some nodes are not always up and some are slower than others – Gnutella & Kazaa dealt with this by classifying some nodes as special (“ultrapeers” in Gnutella, “supernodes” in Kazaa,) Request download • Poor use of network resources • Potentially high latency – Requests get forwarded from one machine to another – Back propagation (e.g., in Gnutella’s design), where the replies go through the same chain of machines used in the query, increases latency even more October 29, 2018 © 2014-2018 Paul Krzyzanowski 13 October 29, 2018 © 2014-2018 Paul Krzyzanowski 14 Hash tables • Remember hash functions & hash tables? – Linear search: O(N) – Tree: O(logN) 3. Distributed Hash Tables – Hash table: O(1) October 29, 2018 © 2014-2018 Paul Krzyzanowski 15 October 29, 2018 © 2014-2018 Paul Krzyzanowski 17 What’s a hash function? (refresher) Considerations with hash tables (refresher) • Hash function • Picking a good hash function – A function that takes a variable length input (e.g., a string) – We want uniform distribution of all values of key over the space 0 … N-1 and generates a (usually smaller) fixed length result (e.g., an integer) – Example: hash strings to a range 0-7: • Collisions • hash(“Newark”) → 1 • hash(“Jersey City”) → 6 – Multiple keys may hash to the same value • hash(“Paterson”) → 2 • hash(“Paterson”) → 2 • hash(“Edison”) → 2 • Hash table – table[i] is a bucket (slot) for all such (key, value) sets – Table of (key, value) tuples – Within table[i], use a linked list or another layer of hashing – Look up a key: • Hash function maps keys to a range 0 … N-1 table of N elements • Think about a hash table that grows or shrinks i = hash(key) – If we add or remove buckets → need to rehash keys and move items table[i] contains the item – No need to search through the table! October 29, 2018 © 2014-2018 Paul Krzyzanowski 18 October 29, 2018 © 2014-2018 Paul Krzyzanowski 19 Paul Krzyzanowski 3 CS 417 29 October 2018 Distributed Hash Tables (DHT) Consistent hashing Create a peer-to-peer version of a (key, value) data store • Conventional hashing – Practically all keys have to be remapped if the table size changes How we want it to work • Consistent hashing 1. A peer (A) queries the data store with a key – Most keys will hash to the same value as before 2. The data store finds the peer (B) that has the value – On average, K/n keys will need to be remapped 3. That peer (B) returns the (key, value) pair to the querying peer (A) K = # keys, n = # of buckets Make it efficient! Example: splitting a bucket Only the keys in slot c get remapped – A query should not generate a flood! query(key) B C slot a slot b slot c slot d slot e A value D E slot a slot b slot c1 slot c2 slot d slot e October 29, 2018 © 2014-2018 Paul Krzyzanowski 20 October 29, 2018 © 2014-2018 Paul Krzyzanowski 21 3. Distributed hashing • Spread the hash table across multiple nodes • Each node stores a portion of the key space lookup(key) → node ID that holds (key, value) Distributed Hashing lookup(node_ID, key) → value Case Study Questions CAN: Content Addressable Network How do we partition the data & do the lookup? & keep the system decentralized? & make the system scalable (lots of nodes with dynamic changes)? & fault tolerant (replicated data)? October 29, 2018 © 2014-2018 Paul Krzyzanowski 22 October 29, 2018 © 2014-2018 Paul Krzyzanowski 23 CAN design CAN key→node mapping: 2 nodes • Create a logical grid y=ymax x = hashx(key) – x-y in 2-D (but not limited to two dimensions) y = hashy(key) • Separate hash function per dimension if x < (xmax/2) n1 has (key, value) – hx(key), hy(key) n1 n2 if x ≥ (xmax/2) n2 has (key, value) • A node – Is responsible for a range of values in each dimension n2 is responsible for a zone – Knows its neighboring nodes x=(xmax/2 .. xmax), y=(0 .. ymax) y=0 x=0 xmax/2 x=xmax October 29, 2018 © 2014-2018 Paul Krzyzanowski 24 25 Paul Krzyzanowski 4 CS 417 29 October 2018 CAN partitioning CAN key→node mapping y=ymax y=ymax Any node can be split in x = hashx(key) two – either horizontally or vertically y = hashy(key) n1 n1 if x < (xmax/2) { if y < (ymax/2) n0 has (key, value) n2 n2 ymax/2 ymax/2 else n1 has (key, value) } n0 n0 if x ≥ (xmax/2) n2 has (key, value) y=0 y=0 x=0 xmax/2 x=xmax x=0 xmax/2 x=xmax October 29, 2018 © 2014-2018 Paul KrzyzanowsKi 26 October 29, 2018 © 2014-2018 Paul Krzyzanowski 27 CAN partitioning CAN neighbors y=ymax y=ymax Any node can be split in Neighbors refer to n1 n1 two – either horizontally nodes that share or vertically adjacent zones in the n0 n11 n0 n11 overlay network n2 n2 Associated data has to be moved to the new n4 only needs to keep n3 n3 node based on track of n5, n7, or n8 as ymax/2 hash(key) ymax/2 its right neighbor. n5 n6 n5 n6 n9 Neighbors need to be n9 n7 made aware of the new n7 n4 node n4 n8 n10 A node knows only of its n8 n10 neighbors y=0 y=0 x=0 xmax/2 x=xmax x=0 xmax/2 x=xmax October 29, 2018 © 2014-2018 Paul Krzyzanowski 28 October 29, 2018 © 2014-2018 Paul Krzyzanowski 29 CAN routing CAN y=ymax • Performance lookup(key) on a node n1 – For n nodes in d dimensions that does not own the value – # neighbors = 2d n0 n11 – Average route for 2 dimensions = O(√n) hops n2 Compute hashx(key), hashy(key) n3 and route request to a ymax/2 neighboring node • To handl e fai l ures n5 n6 n9 – Share knowledge of neighbor’s neighbors Ideally: route to n7 – One of the node’s neighbors takes over the failed zone minimize distance to n4 destination n8 n10 y=0 x=0 xmax/2 x=xmax October 29, 2018 © 2014-2018 Paul Krzyzanowski 30 October 29, 2018 © 2014-2018 Paul Krzyzanowski 31 Paul Krzyzanowski 5 CS 417 29 October 2018 Chord & consistent hashing • A key is hashed to an m-bit value: 0 … (2m-1) • A logical ring is constructed for the values 0 ... (2m-1) Distributed Hashing • Nodes are placed on the ring at hash(IP address) Case Study 15 0 1 Node 14 2 hash(IP address) = 3 Chord 13 3 12 4 11 5 10 6 9 7 8 October 29, 2018 © 2014-2018 Paul Krzyzanowski 32 October 29, 2018 © 2014-2018 Paul Krzyzanowski 33 Key assignment Handling query requests • Example: n=16; system with 4 nodes (so far) • Any peer can get a request (insert or query).
Load more

Recommended publications
  • Uila Supported Apps
    Uila Supported Applications and Protocols updated Oct 2020 Application/Protocol Name Full Description 01net.com 01net website, a French high-tech news site. 050 plus is a Japanese embedded smartphone application dedicated to 050 plus audio-conferencing. 0zz0.com 0zz0 is an online solution to store, send and share files 10050.net China Railcom group web portal. This protocol plug-in classifies the http traffic to the host 10086.cn. It also 10086.cn classifies the ssl traffic to the Common Name 10086.cn. 104.com Web site dedicated to job research. 1111.com.tw Website dedicated to job research in Taiwan. 114la.com Chinese web portal operated by YLMF Computer Technology Co. Chinese cloud storing system of the 115 website. It is operated by YLMF 115.com Computer Technology Co. 118114.cn Chinese booking and reservation portal. 11st.co.kr Korean shopping website 11st. It is operated by SK Planet Co. 1337x.org Bittorrent tracker search engine 139mail 139mail is a chinese webmail powered by China Mobile. 15min.lt Lithuanian news portal Chinese web portal 163. It is operated by NetEase, a company which 163.com pioneered the development of Internet in China. 17173.com Website distributing Chinese games. 17u.com Chinese online travel booking website. 20 minutes is a free, daily newspaper available in France, Spain and 20minutes Switzerland. This plugin classifies websites. 24h.com.vn Vietnamese news portal 24ora.com Aruban news portal 24sata.hr Croatian news portal 24SevenOffice 24SevenOffice is a web-based Enterprise resource planning (ERP) systems. 24ur.com Slovenian news portal 2ch.net Japanese adult videos web site 2Shared 2shared is an online space for sharing and storage.
    [Show full text]
  • Simulacijski Alati I Njihova Ograničenja Pri Analizi I Unapređenju Rada Mreža Istovrsnih Entiteta
    SVEUČILIŠTE U ZAGREBU FAKULTET ORGANIZACIJE I INFORMATIKE VARAŽDIN Tedo Vrbanec SIMULACIJSKI ALATI I NJIHOVA OGRANIČENJA PRI ANALIZI I UNAPREĐENJU RADA MREŽA ISTOVRSNIH ENTITETA MAGISTARSKI RAD Varaždin, 2010. PODACI O MAGISTARSKOM RADU I. AUTOR Ime i prezime Tedo Vrbanec Datum i mjesto rođenja 7. travanj 1969., Čakovec Naziv fakulteta i datum diplomiranja Fakultet organizacije i informatike, 10. listopad 2001. Sadašnje zaposlenje Učiteljski fakultet Zagreb – Odsjek u Čakovcu II. MAGISTARSKI RAD Simulacijski alati i njihova ograničenja pri analizi i Naslov unapređenju rada mreža istovrsnih entiteta Broj stranica, slika, tablica, priloga, XIV + 181 + XXXVIII stranica, 53 slike, 18 tablica, 3 bibliografskih podataka priloga, 288 bibliografskih podataka Znanstveno područje, smjer i disciplina iz koje Područje: Informacijske znanosti je postignut akademski stupanj Smjer: Informacijski sustavi Mentor Prof. dr. sc. Željko Hutinski Sumentor Prof. dr. sc. Vesna Dušak Fakultet na kojem je rad obranjen Fakultet organizacije i informatike Varaždin Oznaka i redni broj rada III. OCJENA I OBRANA Datum prihvaćanja teme od Znanstveno- 17. lipanj 2008. nastavnog vijeća Datum predaje rada 9. travanj 2010. Datum sjednice ZNV-a na kojoj je prihvaćena 18. svibanj 2010. pozitivna ocjena rada Prof. dr. sc. Neven Vrček, predsjednik Sastav Povjerenstva koje je rad ocijenilo Prof. dr. sc. Željko Hutinski, mentor Prof. dr. sc. Vesna Dušak, sumentor Datum obrane rada 1. lipanj 2010. Prof. dr. sc. Neven Vrček, predsjednik Sastav Povjerenstva pred kojim je rad obranjen Prof. dr. sc. Željko Hutinski, mentor Prof. dr. sc. Vesna Dušak, sumentor Datum promocije SVEUČILIŠTE U ZAGREBU FAKULTET ORGANIZACIJE I INFORMATIKE VARAŽDIN POSLIJEDIPLOMSKI ZNANSTVENI STUDIJ INFORMACIJSKIH ZNANOSTI SMJER STUDIJA: INFORMACIJSKI SUSTAVI Tedo Vrbanec Broj indeksa: P-802/2001 SIMULACIJSKI ALATI I NJIHOVA OGRANIČENJA PRI ANALIZI I UNAPREĐENJU RADA MREŽA ISTOVRSNIH ENTITETA MAGISTARSKI RAD Mentor: Prof.
    [Show full text]
  • Distributed Lookup: Part 1: Distributed Hash Tables
    CS 417 – DISTRIBUTED SYSTEMS Week 9: Distributed Lookup: Part 1: Distributed Hash Tables © 2021 Paul Krzyzanowski. No part of this content, may be reproduced or reposted in Paul Krzyzanowski whole or in part in any manner without the permission of the copyright owner. Distributed Lookup • Store (key, value) data Object Storage • Look up a key to get the value • Cooperating set of nodes store data • Ideally: – No central coordinator • Peer-to-peer system: all systems have the same capabilities – Some nodes can be down CS 417 © 2021 Paul Krzyzanowski 2 Approaches 1. Central coordinator – Napster 2. Flooding – Gnutella 3. Distributed hash tables – CAN, Chord, Amazon Dynamo, Tapestry, … CS 417 © 2021 Paul Krzyzanowski 3 1. Central Coordinator • Example: Napster – Central directory – Identifies content (names) and the servers that host it – lookup(name) → {list of servers} – Download from any of available servers • Pick the best one by pinging and comparing response times • Another example: GFS – Controlled environment compared to Napster – Content for a given key is broken into chunks – Master handles all queries … but not the data CS 417 © 2021 Paul Krzyzanowski 4 1. Central Coordinator - Napster • Pros – Super simple – Search is handled by a single server (master) – The directory server is a single point of control • Provides definitive answers to a query • Cons – Master has to maintain state of all peers – Server gets all the queries – The directory server is a single point of control • No directory, no service! CS 417 © 2021 Paul Krzyzanowski 5 2. Query Flooding • Example: Gnutella distributed file sharing • Each node joins a group – but only knows about some group members – Well-known nodes act as anchors – New nodes with files inform an anchor about their existence – Nodes use other nodes they know about as peers CS 417 © 2021 Paul Krzyzanowski 6 2.
    [Show full text]
  • Title: P2P Networks for Content Sharing
    Title: P2P Networks for Content Sharing Authors: Choon Hoong Ding, Sarana Nutanong, and Rajkumar Buyya Grid Computing and Distributed Systems Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Australia (chd, sarana, raj)@cs.mu.oz.au ABSTRACT Peer-to-peer (P2P) technologies have been widely used for content sharing, popularly called “file-swapping” networks. This chapter gives a broad overview of content sharing P2P technologies. It starts with the fundamental concept of P2P computing followed by the analysis of network topologies used in peer-to-peer systems. Next, three milestone peer-to-peer technologies: Napster, Gnutella, and Fasttrack are explored in details, and they are finally concluded with the comparison table in the last section. 1. INTRODUCTION Peer-to-peer (P2P) content sharing has been an astonishingly successful P2P application on the Internet. P2P has gained tremendous public attention from Napster, the system supporting music sharing on the Web. It is a new emerging, interesting research technology and a promising product base. Intel P2P working group gave the definition of P2P as "The sharing of computer resources and services by direct exchange between systems". This thus gives P2P systems two main key characteristics: • Scalability: there is no algorithmic, or technical limitation of the size of the system, e.g. the complexity of the system should be somewhat constant regardless of number of nodes in the system. • Reliability: The malfunction on any given node will not effect the whole system (or maybe even any other nodes). File sharing network like Gnutella is a good example of scalability and reliability.
    [Show full text]
  • Download Times, Bandwidth and Energy Consumption in the Network, Internet Bandwidth Cost, and Traffic Load Imbalance in the Network
    Content Sharing and Distribution in Wireless Community Networks by Amr Alasaad B.Sc., King Saud University, 2000 M.Sc., The University of Southern California, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Electrical and Computer Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2013 c Amr Alasaad 2013 Abstract We consider the problem of content sharing and distribution in a wireless mesh community network (WMCN). Due to the community oriented nature of such networks, and with the evolution of advanced mobile computing devices; it is projected that the demand for content sharing and distribution in wireless community networks will dramatically increase in the coming years. A popular scheme for content sharing and distribution is through the use of Peer-to-Peer (P2P) technology. This dissertation studies the technical challenges involved while deploying P2P applications over WMCNs. We advance the thesis that support from a number of infrastructure nodes in a wire- less community network to P2P applications running on top of the wireless community network such as P2P content sharing and P2P media streaming, results in significant performance enhancement. Such support from infrastructure nodes benefits from aware- ness of the underlying network topology (i.e., information available at relay nodes about the true physical connections between nodes in the network). Cross-layer information exchange between the P2P system and the WMCN opens the door to developing efficient algorithms and schemes for P2P communications that account for the specific features of WMCNs (e.g., contention for wireless medium between neighbouring nodes and traffic in- terference).
    [Show full text]
  • Gnutella Protocol
    A BRIEF INTRODUCTION AND ANALYSIS OF THE GNUTELLA PROTOCOL By Gayatri Tribhuvan University of Freiburg Masters in Applied Computer Science [email protected] ABSTRACT Peer to peer technology has certainly improved mechanisms of downloading files at a very high rate. Statistics and research show that as more number of peer to peer protocols developed, the number of nodes in the entire network increased. In this paper, we observe the structure and operation of Gnutella , a peer to peer protocol. The paper also focuses on some issues of this protocol and what improvements were further made to improve its scalability. We also have a look at some of the security issues of this protocol. Some statistics in the paper also reflect important changes that the protocol inflicted onto the entire network. PDF Created with deskPDF PDF Writer - Trial :: http://www.docudesk.com 1. INTRODUCTION Gnutella is a p2p protocol. This paper has tried to address some of the issues that have been faced by users of Gnutella, including that of scalability (increasing the scale of operation, i.e. the volume of operation with progressively larger number of users) and security. The Gnutella protocol is an open, decentralized group membership and search protocol, mainly used for file searching and sharing. Group membership is open and search protocol addresses searching and sharing of files. The term Gnutella represents the entire group of computers which have Gnutella speaking applications loaded in them forming a virtual network. Each node can function as both client as well as server. Thus they can issue queries to other nodes as well accept and respond to queries from other nodes, after matching the queries with the contents loaded in their own hard disks.
    [Show full text]
  • Index Images Download 2006 News Crack Serial Warez Full 12 Contact
    index images download 2006 news crack serial warez full 12 contact about search spacer privacy 11 logo blog new 10 cgi-bin faq rss home img default 2005 products sitemap archives 1 09 links 01 08 06 2 07 login articles support 05 keygen article 04 03 help events archive 02 register en forum software downloads 3 security 13 category 4 content 14 main 15 press media templates services icons resources info profile 16 2004 18 docs contactus files features html 20 21 5 22 page 6 misc 19 partners 24 terms 2007 23 17 i 27 top 26 9 legal 30 banners xml 29 28 7 tools projects 25 0 user feed themes linux forums jobs business 8 video email books banner reviews view graphics research feedback pdf print ads modules 2003 company blank pub games copyright common site comments people aboutus product sports logos buttons english story image uploads 31 subscribe blogs atom gallery newsletter stats careers music pages publications technology calendar stories photos papers community data history arrow submit www s web library wiki header education go internet b in advertise spam a nav mail users Images members topics disclaimer store clear feeds c awards 2002 Default general pics dir signup solutions map News public doc de weblog index2 shop contacts fr homepage travel button pixel list viewtopic documents overview tips adclick contact_us movies wp-content catalog us p staff hardware wireless global screenshots apps online version directory mobile other advertising tech welcome admin t policy faqs link 2001 training releases space member static join health
    [Show full text]
  • Survey of Search and Replication Schemes in Unstructured P2p Networks
    SURVEY OF SEARCH AND REPLICATION SCHEMES IN UNSTRUCTURED P2P NETWORKS Sabu M. Thampi Department of Computer Science and Engineering, Rajagiri School of Engineering and Technology. Rajagiri Valley, Kakkanad, Kochi- 682039, Kerala (India) Tel: +91-484-2427835 E-mail: [email protected] Chandra Sekaran. K Department of Computer Engineering, National Institute of Technology Karnataka. Surathkal-575025, Karnataka (India) Tel: +91-824-2474000 E-mail: [email protected] Abstract P2P computing lifts taxing issues in various areas of computer science. The largely used decentralized unstructured P2P systems are ad hoc in nature and present a number of research challenges. In this paper, we provide a comprehensive theoretical survey of various state-of-the-art search and replication schemes in unstructured P2P networks for file-sharing applications. The classifications of search and replication techniques and their advantages and disadvantages are briefly explained. Finally, the various issues on searching and replication for unstructured P2P networks are discussed. Keywords: Replication, Searching, Unstructured P2P network. 1 1. Introduction Computing has passed through many transformations since the birth of the first computing machines. A centralized solution has one component that is shared by users all the time. All resources are accessible, but there is a single point of control as well as a single point of failure. A distributed system is a group of autonomous computers connected to a computer network, which appears to the clients of the system as a single computer. Distributed system software allows computers to manage their activities and to share the resources of the system, so that clients recognize the system as a single, integrated computing facility.
    [Show full text]
  • Defending P2ps from Overlay Flooding-Based Ddos
    Defending P2Ps from Overlay Flooding-based DDoS Yunhao Liu1, Xiaomei Liu2, Chen Wang2, and Li Xiao2 1Department of Computer Science, Hong Kong University of Science and Technology, Kowloon, Hong Kong 2Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA Abstract DDoS. In DD-POLICE, peers monitor the traffic from and to each of their neighbors. If a peer receives a large number of queries from one of its neighbors, it will mark this neighbor as a A flooding-based search mechanism is often used in un- suspicious DDoS peer. This peer will exchange query volume structured P2P systems. Although a flooding-based search information with the suspicious peer‘s neighbors so that it can mechanism is simple and easy to implement, it is vulnerable to figure out the number of queries originally issued by the suspi- overlay distributed denial-of-service (DDoS) attacks. Most pre- cious peer. Based on this number, this peer makes a final deci- vious security techniques protect networks from network-layer sion on whether the suspicious neighbor is a DDoS peer and DDoS attacks, but cannot be applied to overlay DDoS attacks. should be disconnected. Overlay flooding-based DDoS attacks can be more damaging in The remainder of this paper proceeds as follows. Section 2 that a small number of messages are inherently propagated to analyzes the characteristics of overlay DDoS. Section 3 presents consume a large amount of bandwidth and computation re- the design of DD-POLICE. Performance evaluation of sources. We propose a distributed and scalable method, DD-POLICE is presented in Section 5.
    [Show full text]
  • Advances in Peer-To-Peer Content Search
    J Sign Process Syst (2010) 59:309–318 DOI 10.1007/s11265-009-0343-6 Advances In Peer-To-Peer Content Search Madjid Merabti & Zhu Liu & Heather Yu & Deepa Kundur Received: 10 February 2008 /Revised: 12 December 2008 /Accepted: 19 January 2009 /Published online: 5 February 2009 # 2009 Springer Science + Business Media, LLC. Manufactured in The United States Abstract Peer-to-peer (P2P) computer networks have Keywords Peer-to-peer . Content search recently received tremendous attention due to their inherent scalability and flexibility, which facilitates a broad spectrum of innovative multimedia applications. Such networks rely 1 Introduction on the power of participant nodes of the network (called peers) for communications and computation. Traditional The power to access relevant and salient information in a applications of P2P multimedia include decentralized file timely and cost-effective manner is critical in today’s sharing and content distribution. Yet, the value of the information age. Models for information sharing between virtually unlimited amount of data distributed in the P2P ad hoc groups of users are currently being investigated for network will be sacrificed if effective and efficient ways to collaborative and cooperative multimedia sharing applica- locate the content are missing. This challenge has stimulated tions. The most common model to date is based on the extensive research in recent years, and many new P2P peer-to-peer (P2P) communication network model. Ideally, content search methods have been proposed. This paper a P2P network consists of equal peer nodes that can take on provides a timely review of influential work in the area of the roles of both client and server to other peer network peer-to-peer (P2P) content search.
    [Show full text]
  • Distributed Data Management
    Distributed Data Management Christoph Lofi José Pinto Institut für Informationssysteme Technische Universität Braunschweig http://www.ifis.cs.tu-bs.de 6 Structured P2P Networks 6.1 Hash Tables 6.2 Distributed Hash Tables 6.3 CHORD – Basics – Routing – Peer Management 6.4 Other DHTs – CAN – Pastry – Symphony Distributed Data Management – Christoph Lofi – IfIS – TU Braunschweig 2 6.0 Unstructured P2P Client-Server Peer-to-Peer 1. Server is the central 1. Resources are shared between the peers entity and only provider 2. Resources can be accessed directly from other peers of service and content. 3. Peer is provider and requestor (Servent concept) Network managed by the Server Unstructured P2P Structured P2P 2. Server as the higher performance system. Centralized P2P Pure P2P Hybrid P2P Pure P2P (DHT Based) 3. Clients as the lower performance system 1. All features of Peer-to- 1. All features of Peer-to-Peer 1. All features of Peer-to-Peer 1. All features of Peer-to-Peer Peer included included included included Example: WWW 2. Central entity is necessary 2. Any terminal entity can be 2. Any terminal entity can be 2. Any terminal entity can be removed to provide the service removed without loss of removed without loss of without loss of functionality 3. Central entity is some kind functionality functionality 3. No central entities of index/group database 3. No central entities 3. dynamic central entities 4. Connections in the overlay are Example: Napster Examples: Gnutella 0.4, Freenet Example: Gnutella 0.6, JXTA “fixed” Examples: Chord,
    [Show full text]
  • Peer to Peer and SPAM in the Internet
    Networking Laboratory Department of Electrical and Communications Engineering Helsinki University of Technology Peer to Peer and SPAM in the Internet Report based a Licentiate Seminar on Networking Technology Fall 2003 Editor: Raimo Kantola Abstract: This report is a collection of papers prepared by PhD students on Peer-to-Peer applications and unsolicited e-mail or spam. The phenomena are covered from different angles including the main algorithms, protocols and application programs, the content, the operator view, legal issues, the economic aspects and the user point of view. Most papers are based on literature review including the latest sources on the web, some contain limited simulations and a few introduce new ideas on aspects of the phenomena under scrutiny. Before presenting the papers we will try to give some economic and social background to the phenomena. Overall, the selection of papers provides a good overview of the two phenomena providing light into what is happening in the Internet today. Finally, we provide a short discussion on where the development is taking us and how we should react to these new phenomena. Acknowledgements My interest in Peer-to-peer traffic and applications originates in the discussions that took place in the Special Interest Group on Broadband networks hosted within the TEKES NETS program during 2003. In particular, I would like to thank Pete Helenius of Rommon for his insights. The Broadband group organised an open seminar in Dipoli on November 20th that brought the topic into a wider discussion involving people from both the networking side as well as the content business.
    [Show full text]