DOCSLIB.ORG

Storing and Managing Data in a Distributed Hash Table

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Storing and Managing Data in a Distributed Hash Table Storing and Managing Data in a Distributed Hash Table by Emil Sit S.B., Computer Science (1999); S.B., Mathematics (1999); M.Eng., Computer Science (2000) Massachusetts Institute of Technology Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of MASSACHUSETTS iNS Doctor of Philosophy in Computer Science OF TEHNOLO at the JUL 0 1 2008 MASSACHUSETTS INSTITUTE OF TECHNOLOGY LIBRARIES June 2008 AC.NV8 @ Massachusetts Institute of Technology 2008. All rights reserved. Author ................ Department of Electrical Engineering and Computer Science 4,A• • tMay 1,2008 Certified by..... WM. Frans Kaashoek Professor / 1l Thesis Supervisor Certified by .......................................... Robert T. Morris Associate Professor Thesis Supervisor Accepted by... ................... Terry P. Orlando Chair, Department Committee on Graduate Students Storing and Managing Data in a Distributed Hash Table by Emil Sit Submitted to the Department of Electrical Engineering and Computer Science on May 1, 2008, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science Abstract Distributed hash tables (DHTs) have been proposed as a generic, robust storage infrastruc- ture for simplifying the construction of large-scale, wide-area applications. For example, UsenetDHT is a new design for Usenet News developed in this thesis that uses a DHT to cooperatively deliver Usenet articles: the DHT allows a set of N hosts to share storage of Usenet articles, reducing their combined storage requirements by a factor of O(N). Usenet generates a continuous stream of writes that exceeds 1 Tbyte/day in volume, comprising over ten million writes. Supporting this and the associated read workload requires a DHT engineered for durability and efficiency. Recovering from network and machine failures efficiently poses a challenge for DHT replication maintenance algorithms that provide durability. To avoid losing the last replica, replica maintenance must create additional replicas when failures are detected. However, creating replicas after every failure stresses network and storage resources unnecessarily. Tracking the location of every replica of every object would allow a replica maintenance algorithm to create replicas only when necessary, but when storing terabytes of data, such tracking is difficult to perform accurately and efficiently. This thesis describes a new algorithm, Passing Tone, that maintains durability efficiently, in a completely decentralized manner, despite transient and permanent failures. Passing Tone nodes make replication decisions with just basic DHT routing state, without maintaining state about the number or location of extant replicas and without responding to every transient failure with a new replica. Passing Tone is implemented in a revised version of DHash, optimized for both disk and network performance. A sample 12 node deployment of Passing Tone and UsenetDHT supports a partial Usenet feed of 2.5 Mbyte/s (processing over 80 Tbyte of data per year), while providing 30 Mbyte/s of read throughput, limited currently by disk seeks. This deployment is the first public DHT to store terabytes of data. These results indicate that DHT-based designs can successfully simplify the construction of large-scale, wide-area systems. Thesis Supervisor: M. Frans Kaashoek Title: Professor Thesis Supervisor: Robert T. Morris Title: Associate Professor Previously Published Material Portions of this thesis are versions of material that were originally published in the following publications: SIT, E., DABEK, F., AND ROBERTSON, J. UsenetDHT: A low overhead Usenet server. In Proc. of the 3rd InternationalWorkshop on Peer-to-PeerSystems (Feb. 2004). CHUN, B.-G., DABEK, F., HAEBERLEN, A., SIT, E., WEATHERSPOON, H., KAASHOEK, F., KUBIATOWICZ, J., AND MORRIS, R. Efficient replica main- tenance for distributed storage systems. In Proc. of the 3rd Symposium on Networked Systems Design and Implementation (May 2006). SIT, E., MORRIS, R., AND KAASHOEK, M. F. UsenetDHT: A low overhead design for Usenet. In Proc. of the 5th Symposium on Networked Systems Design and Implementation (Apr. 2008). Acknowledgments This thesis would not have been possible without collaboration with my colleagues, and the support of my friends and family. My advisors, M. Frans Kaashoek and Robert Morris, have been an endless source of wisdom, optimism and advice; by example, they have taught me how to conduct and present systems research. In addition to their support and feedback, they have created a fun and engaging environment at PDOS. The members of PDOS and other CSAIL systems students and faculty have been invalu- able in preparing talks, thus in-directly refining the presentation of ideas in this thesis. In addition to my advisors, particular thanks go to Russ Cox, who can always be counted on to attend yet another practice and offer suggestions for improvement. Systems research requires the development of significant software. Frank Dabek worked closely with me to develop many of the ideas in this thesis and implement the core Chord and DHash infrastructure. Josh Cates wrote the initial Merkle tree implementation and devised the earliest maintenance protocols used in DHash. Jeremy Stribling has also been a close collaborator on papers and code; he implemented the initial prototypes of Passing Tone and on- disk Merkle tree storage. Andreas Haeberlen implemented the early version of the simulator used to evaluate Passing Tone and Carbonite; his ability to transform ideas or questions into software and graphs overnight is inspiring. Max Krohn and Russ Cox were often sounding boards for my questions about coding and debugging; I am particularly grateful to them for taking on the burden of keeping the computer systems at PDOS running smoothly. Jinyang Li, Athicha Muthitacharoen, James Robertson and Benjie Chen also contributed code and ideas to what has become the work in this thesis. Garrett Wollman provided the live Usenet feed from CSAIL used for evaluation and graciously answered many questions. Trace data used in Chapter 3 was provided by Vivek Pai and Aaron Klingaman. The evaluation in Chapter 6 made use of the PlanetLab and the RON test-beds. David Andersen helped solve many problems with accessing and using RON nodes. Additional nodes were provided by Magda Balazinska (University of Washington), Kevin Fu (University of Massachusetts, Amherst), Jinyang Li (New York University), and Alex Snoeren (University of California, San Diego). My graduate studies were funded by the Cambridge-MIT Institute (as part of the Design and Implementation of Third Generation Peer-to-Peer Systems project), an NSF ITR grant (ANI-0225660 for Robust Large-Scale Distributed Systems), and various teaching assistant positions. Graduate school is only partly about research. My life has been immeasurably enriched by my wife, Aleksandra Mozdzanowska, who has loved and supported me through my years in graduate school, and the many hobbies and distractions I acquired along the way. These last few years were made wonderful by the time I spent with my teachers and friends at the Back Bay and South Boston Yoga studios, most notably David Vendetti, whose wisdom has guided me and so many others. Finally, my parents deserve thanks for instilling a life-long interest in learning and supporting me along the way. Contents 1 Introduction 11 1.1 Motivating application: UsenetDHT .................. .. .. 12 1.2 Goals . .. 13 1.2.1 Bandwidth-efficient durability ................... 14 1.2.2 Perform ance ............................. 15 1.3 Contributions ................................. 16 1.4 Sum mary .................... 17 2 Requirements and challenges 19 2.1 Workloads and requirements ......................... 19 2.2 DHT challenges ................................. 21 2.2.1 Failure handling ............ ..... ........ .. 22 2.2.2 Limited disk capacity ......................... 23 2.2.3 Managing object movement ..................... 26 2.2.4 Efficient maintenance ......................... 27 2.2.5 I/O performance ........................... 28 3 Achieving efficient durability 29 3.1 A lgorithm .................... 30 3.1.1 Local maintenance ........................... 31 3.1.2 Global maintenance ......................... 33 3.1.3 Synchronization ........................... 34 3.1.4 Expiration support ......................... 34 3.2 Design discussion .................... ........... 35 3.2.1 Context ............................... 35 3.2.2 Importance of re-integration ................... .. 36 3.2.3 Setting replication level ................... .... 37 3.2.4 Scope and parallelism ........................ 39 3.3 Evaluation .... ....... .. .......... ... ... ... 40 4 Implementation 43 4.1 D H ash ..................................... 43 4.1.1 Process structure ........................... 44 4.1.2 Storage .... ... .... .. ... ....... .. .. ... 45 4.1.3 Efficient data transfer .............. .. .. .. .. 45 4.2 M aintenance ....... ..... ... .. ... ........... 47 4.3 Synchronization ................. ........ .. .... 48 4.4 Routing and node management . .... .. .. .. .. 50 5 Application: UsenetDHT 53 5.1 Usenet ... ...... .. ... ...... ....... ...... 54 5.2 Architecture .......... ... ............. ....... 55 5.2.1 Design ..................... ........... 55 5.2.2 Write and read walk-through ..................... 57 5.2.3 Expiration .. ... .. .. .. .. ... .. .. .. ... .. .. 58 5.2.4 Trade-offs .......
Load more

Recommended publications
  • Compsci 514: Computer Networks Lecture 13: Distributed Hash Table
    CompSci 514: Computer Networks Lecture 13: Distributed Hash Table Xiaowei Yang Overview • What problems do DHTs solve? • How are DHTs implemented? Background • A hash table is a data structure that stores (key, object) pairs. • Key is mapped to a table index via a hash function for fast lookup. • Content distribution networks – Given an URL, returns the object Example of a Hash table: a web cache http://www.cnn.com0 Page content http://www.nytimes.com ……. 1 http://www.slashdot.org ….. … 2 … … … • Client requests http://www.cnn.com • Web cache returns the page content located at the 1st entry of the table. DHT: why? • If the number of objects is large, it is impossible for any single node to store it. • Solution: distributed hash tables. – Split one large hash table into smaller tables and distribute them to multiple nodes DHT K V K V K V K V A content distribution network • A single provider that manages multiple replicas. • A client obtains content from a close replica. Basic function of DHT • DHT is a virtual hash table – Input: a key – Output: a data item • Data Items are stored by a network of nodes. • DHT abstraction – Input: a key – Output: the node that stores the key • Applications handle key and data item association. DHT: a visual example K V K V (K1, V1) K V K V K V Insert (K1, V1) DHT: a visual example K V K V (K1, V1) K V K V K V Retrieve K1 Desired properties of DHT • Scalability: each node does not keep much state • Performance: look up latency is small • Load balancing: no node is overloaded with a large amount of state • Dynamic reconfiguration: when nodes join and leave, the amount of state moved from nodes to nodes is small.
    [Show full text]
  • Cisco SCA BB Protocol Reference Guide
    Cisco Service Control Application for Broadband Protocol Reference Guide Protocol Pack #60 August 02, 2018 Cisco Systems, Inc. www.cisco.com Cisco has more than 200 offices worldwide. Addresses, phone numbers, and fax numbers are listed on the Cisco website at www.cisco.com/go/offices. THE SPECIFICATIONS AND INFORMATION REGARDING THE PRODUCTS IN THIS MANUAL ARE SUBJECT TO CHANGE WITHOUT NOTICE. ALL STATEMENTS, INFORMATION, AND RECOMMENDATIONS IN THIS MANUAL ARE BELIEVED TO BE ACCURATE BUT ARE PRESENTED WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED. USERS MUST TAKE FULL RESPONSIBILITY FOR THEIR APPLICATION OF ANY PRODUCTS. THE SOFTWARE LICENSE AND LIMITED WARRANTY FOR THE ACCOMPANYING PRODUCT ARE SET FORTH IN THE INFORMATION PACKET THAT SHIPPED WITH THE PRODUCT AND ARE INCORPORATED HEREIN BY THIS REFERENCE. IF YOU ARE UNABLE TO LOCATE THE SOFTWARE LICENSE OR LIMITED WARRANTY, CONTACT YOUR CISCO REPRESENTATIVE FOR A COPY. The Cisco implementation of TCP header compression is an adaptation of a program developed by the University of California, Berkeley (UCB) as part of UCB’s public domain version of the UNIX operating system. All rights reserved. Copyright © 1981, Regents of the University of California. NOTWITHSTANDING ANY OTHER WARRANTY HEREIN, ALL DOCUMENT FILES AND SOFTWARE OF THESE SUPPLIERS ARE PROVIDED “AS IS” WITH ALL FAULTS. CISCO AND THE ABOVE-NAMED SUPPLIERS DISCLAIM ALL WARRANTIES, EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION, THOSE OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OR ARISING FROM A COURSE OF DEALING, USAGE, OR TRADE PRACTICE. IN NO EVENT SHALL CISCO OR ITS SUPPLIERS BE LIABLE FOR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, OR INCIDENTAL DAMAGES, INCLUDING, WITHOUT LIMITATION, LOST PROFITS OR LOSS OR DAMAGE TO DATA ARISING OUT OF THE USE OR INABILITY TO USE THIS MANUAL, EVEN IF CISCO OR ITS SUPPLIERS HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
    [Show full text]
  • Peer-To-Peer Systems
    Peer-to-Peer Systems Winter semester 2014 Jun.-Prof. Dr.-Ing. Kalman Graffi Heinrich Heine University Düsseldorf Peer-to-Peer Systems Unstructured P2P Overlay Networks – Unstructured Heterogeneous Overlays This slide set is based on the lecture "Communication Networks 2" of Prof. Dr.-Ing. Ralf Steinmetz at TU Darmstadt Unstructured Heterogeneous P2P Overlays Unstructured P2P Structured P2P Centralized P2P Homogeneous P2P Heterogeneous P2P DHT-Based Heterogeneous P2P 1. All features of 1. All features of 1. All features of 1. All features of 1. All features of Peer-to-Peer Peer-to-Peer Peer-to-Peer Peer-to-Peer Peer-to-Peer included included included included included 2. Central entity is 2. Any terminal 2. Any terminal 2. Any terminal 2. Peers are necessary to entity can be entity can be entity can be organized in a provide the removed without removed without removed hierarchical service loss of loss of without loss of manner 3. Central entity is functionality functionality functionality 3. Any terminal some kind of 3. ! no central 3. ! dynamic central 3. ! No central entity can be index/group entities entities entities removed without database 4. Connections in loss of functionality the overlay are Examples: “fixed” Examples: Examples: § Gnutella 0.6 Examples: Examples: § Napster § Gnutella 0.4 § Fasttrack § Chord • AH-Chord § Freenet § eDonkey § CAN • Globase.KOM § Kademlia from R.Schollmeier and J.Eberspächer, TU München HHU – Technology of Social Networks – JProf. Dr. Kalman Graffi – Peer-to-Peer Systems – http://tsn.hhu.de/teaching/lectures/2014ws/p2p.html
    [Show full text]
  • A Fog Storage Software Architecture for the Internet of Things Bastien Confais, Adrien Lebre, Benoît Parrein
    A Fog storage software architecture for the Internet of Things Bastien Confais, Adrien Lebre, Benoît Parrein To cite this version: Bastien Confais, Adrien Lebre, Benoît Parrein. A Fog storage software architecture for the Internet of Things. Advances in Edge Computing: Massive Parallel Processing and Applications, IOS Press, pp.61-105, 2020, Advances in Parallel Computing, 978-1-64368-062-0. 10.3233/APC200004. hal- 02496105 HAL Id: hal-02496105 https://hal.archives-ouvertes.fr/hal-02496105 Submitted on 2 Mar 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. November 2019 A Fog storage software architecture for the Internet of Things Bastien CONFAIS a Adrien LEBRE b and Benoˆıt PARREIN c;1 a CNRS, LS2N, Polytech Nantes, rue Christian Pauc, Nantes, France b Institut Mines Telecom Atlantique, LS2N/Inria, 4 Rue Alfred Kastler, Nantes, France c Universite´ de Nantes, LS2N, Polytech Nantes, Nantes, France Abstract. The last prevision of the european Think Tank IDATE Digiworld esti- mates to 35 billion of connected devices in 2030 over the world just for the con- sumer market. This deep wave will be accompanied by a deluge of data, applica- tions and services.
    [Show full text]
  • Peer-To-Peer Systems: Taxonomy and Characteristics 1B
    IJCST VOL . 3, Iss UE 2, APR I L - JUNE 2012 ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print) Peer-to-Peer Systems: Taxonomy and Characteristics 1B. Lalitha, 2Dr. Ch. D. V. Subbarao 1Dept. of CSE, JNTUCE, Anantapur, AP, India 2Dept. of CSE, S.V University, Tirupathi, AP, India Abstract Various types of networks include: The limitations of client/server systems became a proof in large scale distributed systems for emerging of peer to peer systems, A. Centralized Networks which is the basis for decentralized distributed computing. In peer Centralized P2P protocols consist of a centralized file list. In this to peer model each node takes both the roles of client and server. model a user can send a query for a file to the centralized server. As a client, it can query and download its wanted data files from The server would then send back a list of peers that have the other nodes (peers) and as a server, it can provide data files to requested file. Once the user chooses which peer to download the other nodes. This paper provides the taxonomy of P2P systems file from the centralized would then facilitate the connection of gives an overview of structured and unstructured P2P systems, the peers then remove itself from the process as illustrated in Fig also discusses the characteristics and applications of peer to peer 1. Examples of centralized networks are Napster and eDonkey systems". in its early stages. Keywords Peer-To-Peer, Distributed Systems, Structured P2P, Unstructured P2P Systems. I. Introduction A Peer-to-Peer (P2P) computing or networking is a distributed application architecture that partitions tasks or workloads between peers.
    [Show full text]
  • 2.3 Blockchain
    POLITECNICO DI TORINO Corso di Laurea Magistrale in Ingegneria Informatica - Data Science Tesi di Laurea Magistrale Supporting the portability of profiles using the blockchain in the Mastodon social network Relatore Candidato prof. Giovanni Squillero Alessandra Rossaro Anno Accademico 2018-2019 École polytechnique de Louvain Supporting the portability of profiles using the blockchain in the Mastodon social network Authors: Alessandra ROSSARO, Corentin SURQUIN Supervisors: Etienne RIVIERE, Ramin SADRE Readers: Lionel DRICOT, Axel LEGAY, Giovanni SQUILLERO Academic year 2018–2019 Master [120] in Computer Science Acknowledgements We would like to thank anyone who made the writing of this thesis possible, directly or indirectly. First of all, we would like to thank our supervisors, Prof. Etienne Riviere and Prof. Ramin Sadre for their continous support and advice during the year. We would never have gone this far without them. Secondly, we thank Lionel Dricot, Prof. Axel Legay and Prof. Giovanni Squillero for accepting to be the readers of this thesis. Alessandra First of all, I would like to thank my family, my parents Claudia and Alberto, my brother Stefano and my sister Eleonora, that from the beginning of my studies believed in me, every time urging me to give more and sustaining me each time that I had difficulties. They are my strength and I feel really lucky to have them in my life. Another thanks is to my friends, to Soraya, Beatrice, Sinto and Stefano and especially to Matteo and Edoardo that each time that I needed, remember me to believe in myself and don’t give up. Thank you, sincerely! I would like to thank also my partner, Corentin, because we were a great team, sometimes with some misunderstandings, but I appreciated to work at this project with him! Corentin I must express my deep gratitude to my family and friends for their moral support.
    [Show full text]
  • Challenges in the Decentralised Web: the Mastodon Case∗
    Challenges in the Decentralised Web: The Mastodon Case∗ Aravindh Raman1, Sagar Joglekar1, Emiliano De Cristofaro2;3, Nishanth Sastry1, and Gareth Tyson3;4 1King’s College London, 2University College London, 3Alan Turing Institute, 4Queen Mary University of London faravindh.raman,sagar.joglekar,[email protected], [email protected], [email protected] Abstract cols to let instances interact and aggregate their users to offer a globally integrated service. The Decentralised Web (DW) has recently seen a renewed mo- DW platforms intend to offer a number of benefits. For ex- mentum, with a number of DW platforms like Mastodon, Peer- ample, data is spread among many independent instances, thus Tube, and Hubzilla gaining increasing traction. These offer al- possibly making privacy-intrusive data mining more difficult. ternatives to traditional social networks like Twitter, YouTube, Data ownership is more transparent, and the lack of centralisa- and Facebook, by enabling the operation of web infrastruc- tion could make the overall system more robust against techni- ture and services without centralised ownership or control. cal, legal or regulatory attacks. Although their services differ greatly, modern DW platforms mostly rely on two key innovations: first, their open source However, these properties may also bring inherent chal- software allows anybody to setup independent servers (“in- lenges that are difficult to avoid, particularly when consid- stances”) that people can sign-up to and use within a local ering the natural pressures towards centralisation in both so- community; and second, they build on top of federation pro- cial [12, 49] and economic [42] systems.
    [Show full text]
  • Distributed Hash Tables CS6450: Distributed Systems Lecture 12
    Distributed Hash Tables CS6450: Distributed Systems Lecture 12 Ryan Stutsman Material taken/derived from Princeton COS-418 materials created by Michael Freedman and Kyle Jamieson at Princeton University. Licensed for use under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. 1 Some material taken/derived from MIT 6.824 by Robert Morris, Franz Kaashoek, and Nickolai Zeldovich. Consistency models Linearizability Causal Eventual Sequential 2 Recall use of logical clocks • Lamport clocks: C(a) < C(z) Conclusion: None • Vector clocks: V(a) < V(z) Conclusion: a → … → z • Distributed bulletin board application • Each post gets sent to all other users • Consistency goal: No user to see reply before the corresponding original message post • Conclusion: Deliver message only after all messages that causally precede it have been delivered 3 Causal Consistency 1. Writes that are potentially P1 P2 P3 causally related must be seen by a all machines in same order. f b c 2. Concurrent writes may be seen d in a different order on different e machines. g • Concurrent: Ops not causally related Physical time ↓ Causal Consistency Operations Concurrent? P1 P2 P3 a, b N a f b, f Y b c c, f Y d e, f Y e e, g N g a, c Y a, e N Physical time ↓ Causal Consistency: Quiz Causal Consistency: Quiz • Valid under causal consistency • Why? W(x)b and W(x)c are concurrent • So all processes don’t (need to) see them in same order • P3 and P4 read the values ‘a’ and ‘b’ in order as potentially causally related.
    [Show full text]
  • Distributed Systems Security Knowledge Area Issue 1.0
    Distributed Systems Security Knowledge Area Issue 1.0 Neeraj Suri Lancaster University EDITOR Emil Lupu Imperial College London REVIEWERS Konstantin Beznosov University of British Columbia Marko Vukolic´ IBM Research The Cyber Security Body Of Knowledge www.cybok.org COPYRIGHT © Crown Copyright, The National Cyber Security Centre 2019. This information is licensed under the Open Government Licence v3.0. To view this licence, visit: http://www.nationalarchives.gov.uk/doc/open-government-licence/ When you use this information under the Open Government Licence, you should include the following attribution: CyBOK © Crown Copyright, The National Cyber Security Centre 2018, li- censed under the Open Government Licence: http://www.nationalarchives.gov.uk/doc/open- government-licence/. The CyBOK project would like to understand how the CyBOK is being used and its uptake. The project would like organisations using, or intending to use, CyBOK for the purposes of education, training, course development, professional development etc. to contact it at con- [email protected] to let the project know how they are using CyBOK. Issue 1.0 is a stable public release of the Distributed Systems Security Knowledge Area. How- ever, it should be noted that a fully-collated CyBOK document which includes all of the Knowl- edge Areas is anticipated to be released by the end of July 2019. This will likely include up- dated page layout and formatting of the individual Knowledge Areas KA Distributed Systems Security j October 2019 Page 1 The Cyber Security Body Of Knowledge
    [Show full text]
  • Distributed Hash Tables in P2P Systems - a Literary Survey
    Distributed Hash Tables in P2P Systems - A literary survey Timo Tanner Helsinki University of Technology [email protected] Abstract networking, every node in the network has a Globally unique identifier. (GUID) Each node functions as a container for the Distributed Hash Tables (DHT) are algorithms used in mod- distributed data. ern peer-to-peer applications, which provide a reliable, scal- Nodes in this type of P2P network are arranged to a Net- able, fault tolerant and efficient way to manage P2P networks work overlay, which for example dictates how the nodes are in a true peer to peer manner. A lot of literature has been connected and to how many neighbors each node can con- published on the subject to analyze various different DHT nect to. A network overlay is a virtual network that runs algorithms, their properties and performance. on top of another network and can be managed indepen- The purpose of this paper is to find out about recent re- dently. A network overlay can utilize the underlying pro- search conducted on the subject and wrap up a literary survey tocols as seen fit. Some DHTs prefer using connectionless containing a comparison of four different DHT algorithms. UDP whereas others resort to the connection oriented TCP. The algorithms chosen for the survey are Chord, Tapestry, In P2P world, the network overlay functions on the applica- CAN and Kademlia. The comparison concentrates on the tion level. relative efficiencies of the different DHTs, presents them and Distributed Hash Tables promote several ideas that distin- analyzes the factors that affect the efficiency of a Distributed guish them from traditional Client-Server oriented services: Hash Table.
    [Show full text]
  • Distributed Hash Tables and Chord
    Distributed Hash Tables and Chord Hari Balakrishnan 6.829 Fall 2018 October 30, 2018 What is a P2P system? Node Node Node Internet Node Node • A distributed system architecture in which: • There’s no centralized control • Nodes are symmetric in function • Large number of (unreliable) nodes What can P2P teach us about infrastructure design? • Resistant to DoS and failures • Safety in numbers, no single point of failure • Self-assembling • Nodes insert themselves into structure • No manual configuration or oversight • Flexible: nodes can be • Widely distributed or colocated • Powerful hosts or low-end PCs • Each peer brings a little bit to the dance • Aggregate is equivalent to a big distributed server farm behind a fat network pipe General Abstraction? • Big challenge for P2P: finding content • Many machines, must find one that holds data • Not too hard to find hay, but what about needles? • Essential task: lookup(key) • Given key, find host that has data (value) corresponding to that key • Higher-level interface: put(key,val)/get(key) • Easy to layer on top of lookup() • Allows application to ignore details of storage • Good for some apps, not for others Data-centric network abstraction • TCP provides a conversation abstraction socket = connect (IP address, port); send(data on socket); /* goes to IP addr / TCP port */ • A DHT provides a data-centric abstraction as an overlay over the Internet • A key is a semantic-free identifier for data • E.g., key = hash(filename) put(key, value) Distributed application get (key) value (data) DHT Infrastructure DHT layering Distributed application put(key, data) get (key) data Distributed hash table lookup(key) node IP address Lookup service node node ….
    [Show full text]
  • P2P and Bittorrent
    inf5040 - Presentation by group 1 nghial, baardehe, chricar 30.10.08 Goals of today After this lecture you should have a general understanding of what P2P and bittorrent is be able to recognize the main differences of bitTorrent and other P2P networks A way of organizing resource sharing in computer networks What is P2P? Server/client model Peer-to-peer model Characteristics of P2P networks Peers act as equals Peers function as both client and server No central server managing the network No central router Examples of ”pure” P2P networks Gnutella, Freenet (filesharing) In short Decentralization and multirole BUT! Most networks and applications described as P2P actually contain or rely on some non-peer elements History 1970 – SMTP, NNTP (Usenet) One process both server and client IBM, 1984 ”Advanced Peer to Peer Networking” Software for filesharing in a LAN 1990 – IRC (DCC), MBONE One client can both send and receive 1997 – Napster Created a lot of controversy Convicted because of the centralized file indexing Advantages of P2P networks Better performance and reliability compared to server/client scheme Popular resources will be available at several locations Principle of locality -> less delay and faster transmission Overlay routing Application layer routing (middleware) Two ways of searching for files Flooding DHT (Distributed Hash Table) Area of application Mostly used in ad hoc networks Often categorized by what it’s used for Filesharing Media streaming Telephony (skype) Discussion forums Used to distribute
    [Show full text]