PPT-Paxos

Author : alexa-scheidler | Published Date : 2016-06-23

and Replicated State Machine RSM Outline Basic Concepts of Replicated State Machine Paxos Made Simple Replicated State Machine We can replicate data how can we

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Paxos: Transcript

and Replicated State Machine RSM Outline Basic Concepts of Replicated State Machine Paxos Made Simple Replicated State Machine We can replicate data how can we guarantee it is correctly replicated. Cheap Paxos a variant of the Paxos al gorithm guarantees liveness under the additional as sumption that the set of nonfaulty processors does not jump around too fast but uses only F 1 main pro cessors that actually execute the system and F auxiliar Presenter-. Kurchi. . S. ubhra. . H. azra. Agenda. Basic Algorithms such as Leader Election. Consensus in Distributed Systems. Replication and Fault Tolerance in Distributed Systems. GFS as an example of a Distributed System. A Consensus Algorithm for . Fault Tolerant Replication. CS 5204 – Fall, 2008. System Model. Messages. possible indefinite delay. possible duplication or loss. delivered messages not corrupted. . . .. COMS 6998-. 8. , Fall 2013. Instructor: Li . Erran. Li (. lierranli@cs.columbia.edu. ). http://www.cs.columbia.edu/~lierranli/coms6998-8SDNFall2013/. 10/. 29/. 2013: SDN . Traffic Management. Outline. Replication. Lecture 16. , Oct 22. nd. 2015 . How’d we get here?. Failures & single systems; fault tolerance techniques added redundancy (ECC memory, RAID, etc.). Conceptually, ECC & RAID both put a “master” in front of the redundancy to mask it from clients -- ECC handled by memory controller, RAID looks like a very reliable hard drive behind a (special) controller. Globally-Distributed Database. James C. Corbett, Jeffrey Dean, Michael Epstein, Andrew . Fikes. , Christopher Frost, JJ . Furman,Sanjay. . Ghemawat. , . Andrey. . Gubarev. , Christopher . Heiser. , Peter . Cezara. . Drăgoi. , INRIA ENS CNRS. Thomas A. . Henzinger. , IST Austria. Damien Zufferey. , MIT CSAIL. SNAPL, 2015.05.04. Fault-tolerant distributed algorithms. How to get it right when things go wrong ?. Cezara. . Drăgoi. , INRIA ENS CNRS. Thomas A. . Henzinger. , IST Austria. Damien Zufferey. , MIT CSAIL. SNAPL, 2015.05.04. Fault-tolerant distributed algorithms. How to get it right when things go wrong ?. Distributed Systems. Lecture 12. Michael Freedman. Let different replicas assume role of primary over time. System moves through a sequence of views. How do the nodes agree on view / primary?. 2. Recall the use of Views. Fault Tolerant Replication. CS 5204 – Fall, 2008. System Model. Messages. possible indefinite delay. possible duplication or loss. delivered messages not corrupted. . . .. replicas. client. Replicas. . Distributed. . Systems. Crash. . Fault. . Tolerance. Sisi. . Duan. Assistant. . Professor. Information. . Systems. sduan@umbc.edu. Outline. A. . brief. . history. . of. . consensus. Paxos. Lecture 11, . Oct 6. th. . 2016 . How’d we get here?. Failures & single systems; fault tolerance techniques added redundancy (ECC memory, RAID, etc.). Conceptually, ECC & RAID both put a “master” in front of the redundancy to mask it from clients -- ECC handled by memory controller, RAID looks like a very reliable hard drive behind a (special) controller. Lecture 16. , Oct 22. nd. 2015 . How’d we get here?. Failures & single systems; fault tolerance techniques added redundancy (ECC memory, RAID, etc.). Conceptually, ECC & RAID both put a “master” in front of the redundancy to mask it from clients -- ECC handled by memory controller, RAID looks like a very reliable hard drive behind a (special) controller. Each 42the OI 2DSeuTli and zPage wIIPwC hwaccuracy Page wcash Seive trading Page won iiaiiOtiS urior Oii7i bligaiioris 1Page wPaxos Page wIn MIX32 bSPage wiv ZZ Page wParticipant vJii reyuird O c27gQ

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