Atomic Broadcast
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Atomic Broadcast
In fault-tolerant distributed computing, an atomic broadcast or total order broadcast is a broadcast where all correct processes in a system of multiple processes receive the same set of messages in the same order; that is, the same sequence of messages. The broadcast is termed " atomic" because it either eventually completes correctly at all participants, or all participants abort without side effects. Atomic broadcasts are an important distributed computing primitive. Properties The following properties are usually required from an atomic broadcast protocol: # Validity: if a correct participant broadcasts a message, then all correct participants will eventually receive it. # Uniform Agreement: if one correct participant receives a message, then all correct participants will eventually receive that message. # Uniform Integrity: a message is received by each participant at most once, and only if it was previously broadcast. # Uniform Total Order: the messages are totally order ...
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Fault-tolerant
Fault tolerance is the property that enables a system to continue operating properly in the event of the failure of one or more faults within some of its components. If its operating quality decreases at all, the decrease is proportional to the severity of the failure, as compared to a naively designed system, in which even a small failure can cause total breakdown. Fault tolerance is particularly sought after in high-availability, mission-critical, or even life-critical systems. The ability of maintaining functionality when portions of a system break down is referred to as graceful degradation. A fault-tolerant design enables a system to continue its intended operation, possibly at a reduced level, rather than failing completely, when some part of the system fails. The term is most commonly used to describe computer systems designed to continue more or less fully operational with, perhaps, a reduction in throughput or an increase in response time in the event of some partial fa ...
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Nancy Lynch
Nancy Ann Lynch (born January 19, 1948) is a mathematician, a theorist, and a professor at the Massachusetts Institute of Technology. She is the NEC Professor of Software Science and Engineering in the EECS department and heads the "Theory of Distributed Systems" research group at MIT's Computer Science and Artificial Intelligence Laboratory. Education and early life Lynch was born in Brooklyn, and her academic training was in mathematics. She attended Brooklyn College and MIT, where she received her Ph.D. in 1972 under the supervision of Albert R. Meyer. Work She served on the math and computer science faculty at several other universities, including Tufts University, the University of Southern California, Florida International University, and the Georgia Institute of Technology (Georgia Tech), prior to joining the MIT faculty in 1982. Since then, she has been working on applying mathematics to the tasks of understanding and constructing complex distributed systems. Her 1985 ...
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Ken Birman
Kenneth P. Birman (born November 18, 1955) is a professor in the Department of Computer Science at Cornell University. He currently holds the N. Rama Rao Chair in Computer Science. Education Birman received his B.S. from Columbia University and Ph.D. from University of California, Berkeley. Research and publications Birman's research is mainly concerned with scalability of distributed systems, security technologies, and system management tools employed in cloud computing. An ACM Fellow and IEEE Fellow, Birman was Editor in Chief of ''ACM Transactions on Computer Systems'' from 1993-1998. He is also the author of several books, most recently ''Reliable Distributed Computing: Technologies, Web Services, and Applications'', published by Springer-Verlag in May 2007. Virtual Synchrony, Derecho, and the Isis Toolkit He is best known for developing the Isis Toolkit, which introduced the virtual synchrony execution model for multicast communication. Birman founded Isis Distribute ...
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Hadoop
Apache Hadoop () is a collection of open-source software utilities that facilitates using a network of many computers to solve problems involving massive amounts of data and computation. It provides a software framework for distributed storage and processing of big data using the MapReduce programming model. Hadoop was originally designed for computer clusters built from commodity hardware, which is still the common use. It has since also found use on clusters of higher-end hardware. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common occurrences and should be automatically handled by the framework. The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part which is a MapReduce programming model. Hadoop splits files into large blocks and distributes them across nodes in a cluster. It then transfers packaged code into nodes to process the data in parallel. This appro ...
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Apache ZooKeeper
Apache ZooKeeper is an open-source server for highly reliable distributed coordination of cloud applications. It is a project of the Apache Software Foundation. ZooKeeper is essentially a service for distributed systems offering a hierarchical key-value store, which is used to provide a distributed configuration service, synchronization service, and naming registry for large distributed systems (see ''Use cases''). ZooKeeper was a sub-project of Hadoop but is now a top-level Apache project in its own right. Overview ZooKeeper's architecture supports high availability through redundant services. The clients can thus ask another ZooKeeper leader if the first fails to answer. ZooKeeper nodes store their data in a hierarchical name space, much like a file system or a tree data structure. Clients can read from and write to the nodes and in this way have a shared configuration service. ZooKeeper can be viewed as an atomic broadcast system, through which updates are totally ordere ...
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Chandra–Toueg Consensus Algorithm
The Chandra–Toueg consensus algorithm, published by Tushar Deepak Chandra and Sam Toueg in 1996, is an algorithm for solving consensus in a network of unreliable processes equipped with an ''eventually strong'' failure detector. The failure detector is an abstract version of timeouts; it signals to each process when other processes may have crashed. An eventually strong failure detector is one that never identifies ''some'' specific non-faulty process as having failed after some initial period of confusion, and, at the same time, eventually identifies ''all'' faulty processes as failed (where a faulty process is a process which eventually fails or crashes and a non-faulty process never fails). The Chandra–Toueg consensus algorithm assumes that the number of faulty processes, denoted by , is less than n/2 (i.e. the minority), i.e. it assumes < /2, where n is the total number of processes.


The algorithm

The algorithm proceeds in rounds and uses a rotating ...
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Consensus (computer Science)
A fundamental problem in distributed computing and multi-agent systems is to achieve overall system reliability in the presence of a number of faulty processes. This often requires coordinating processes to reach consensus, or agree on some data value that is needed during computation. Example applications of consensus include agreeing on what transactions to commit to a database in which order, state machine replication, and atomic broadcasts. Real-world applications often requiring consensus include cloud computing, clock synchronization, PageRank, opinion formation, smart power grids, state estimation, control of UAVs (and multiple robots/agents in general), load balancing, blockchain, and others. Problem description The consensus problem requires agreement among a number of processes (or agents) for a single data value. Some of the processes (agents) may fail or be unreliable in other ways, so consensus protocols must be fault tolerant or resilient. The processes must someho ...
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Mike Paterson
Michael Stewart Paterson, is a British computer scientist, who was the director of the Centre for Discrete Mathematics and its Applications (DIMAP) at the University of Warwick until 2007, and chair of the department of computer science in 2005. He received his Doctor of Philosophy (Ph.D.) from the University of Cambridge in 1967, under the supervision of David Park. He spent three years at Massachusetts Institute of Technology (MIT) and moved to University of Warwick in 1971, where he remains Professor Emeritus. Paterson is an expert on theoretical computer science with more than 100 publications, especially the design and analysis of algorithms and computational complexity. Paterson's distinguished career was recognised with the EATCS Award in 2006, and a workshop in honour of his 66th birthday in 2008, including contributions of several Turing Award and Gödel Prize laureates. A further workshop was held in 2017 in honour of his 75th birthday, co-located with the workshop f ...
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Michael J
Michael may refer to: People * Michael (given name), a given name * Michael (surname), including a list of people with the surname Michael Given name "Michael" * Michael (archangel), ''first'' of God's archangels in the Jewish, Christian and Islamic religions * Michael (bishop elect), English 13th-century Bishop of Hereford elect * Michael (Khoroshy) (1885–1977), cleric of the Ukrainian Orthodox Church of Canada * Michael Donnellan (1915–1985), Irish-born London fashion designer, often referred to simply as "Michael" * Michael (footballer, born 1982), Brazilian footballer * Michael (footballer, born 1983), Brazilian footballer * Michael (footballer, born 1993), Brazilian footballer * Michael (footballer, born February 1996), Brazilian footballer * Michael (footballer, born March 1996), Brazilian footballer * Michael (footballer, born 1999), Brazilian footballer Rulers =Byzantine emperors= *Michael I Rangabe (d. 844), married the daughter of Emperor Nikephoros I * M ...
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Distributed Systems
A distributed system is a system whose components are located on different networked computers, which communicate and coordinate their actions by passing messages to one another from any system. Distributed computing is a field of computer science that studies distributed systems. The components of a distributed system interact with one another in order to achieve a common goal. Three significant challenges of distributed systems are: maintaining concurrency of components, overcoming the lack of a global clock, and managing the independent failure of components. When a component of one system fails, the entire system does not fail. Examples of distributed systems vary from SOA-based systems to massively multiplayer online games to peer-to-peer applications. A computer program that runs within a distributed system is called a distributed program, and ''distributed programming'' is the process of writing such programs. There are many different types of implementations for t ...
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Consensus (computing)
A fundamental problem in distributed computing and multi-agent systems is to achieve overall system reliability in the presence of a number of faulty processes. This often requires coordinating processes to reach consensus, or agree on some data value that is needed during computation. Example applications of consensus include agreeing on what transactions to commit to a database in which order, state machine replication, and atomic broadcasts. Real-world applications often requiring consensus include cloud computing, clock synchronization, PageRank, opinion formation, smart power grids, state estimation, control of UAVs (and multiple robots/agents in general), load balancing, blockchain, and others. Problem description The consensus problem requires agreement among a number of processes (or agents) for a single data value. Some of the processes (agents) may fail or be unreliable in other ways, so consensus protocols must be fault tolerant or resilient. The processes must somehow ...
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Multicast
In computer networking, multicast is group communication where data transmission is addressed to a group of destination computers simultaneously. Multicast can be one-to-many or many-to-many distribution. Multicast should not be confused with physical layer point-to-multipoint communication. Group communication may either be application layer multicast or network-assisted multicast, where the latter makes it possible for the source to efficiently send to the group in a single transmission. Copies are automatically created in other network elements, such as routers, switches and cellular network base stations, but only to network segments that currently contain members of the group. Network assisted multicast may be implemented at the data link layer using one-to-many addressing and switching such as Ethernet multicast addressing, Asynchronous Transfer Mode (ATM), point-to-multipoint virtual circuits (P2MP) or InfiniBand multicast. Network-assisted multicast may also be impl ...
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