|
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 rotatin ...[...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 some ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Failure Detector
In a distributed computing system, a failure detector is a computer application or a subsystem that is responsible for the detection of node failures or crashes. Failure detectors were first introduced in 1996 by Chandra and Toueg in their book ''Unreliable Failure Detectors for Reliable Distributed Systems''. The book depicts the failure detector as a tool to improve consensus (the achievement of reliability) and atomic broadcast (the same sequence of messages) in the distributed system. In other word, failure detectors seek for errors in the process, and the system will maintain a level of reliability. In practice, after failure detectors spot crashes, the system will ban the processes that are making mistakes to prevent any further serious crashes or errors. In the 21st century, failure detectors are widely used in distributed computing systems to detect application errors, such as a software application stops functioning properly. As the distributed computing projects (see L ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Timeout (computing)
In telecommunications and related engineering (including computer networking and programming), the term timeout or time-out has several meanings, including: * A network parameter related to an enforced event designed to occur at the conclusion of a predetermined elapsed time. * A specified period of time that will be allowed to elapse in a system before a specified event is to take place, unless another specified event occurs first; in either case, the period is terminated when either event takes place. Note: A timeout condition can be canceled by the receipt of an appropriate time-out cancellation signal. * An event that occurs at the end of a predetermined period of time that began at the occurrence of another specified event. The timeout can be prevented by an appropriate signal. Timeouts allow for more efficient usage of limited resources without requiring additional interaction from the agent interested in the goods that cause the consumption of these resources. The ba ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Timestamp
A timestamp is a sequence of characters or encoded information identifying when a certain event occurred, usually giving date and time of day, sometimes accurate to a small fraction of a second. Timestamps do not have to be based on some absolute notion of time, however. They can have any epoch, can be relative to any arbitrary time, such as the power-on time of a system, or to some arbitrary time in the past. The term "timestamp" derives from rubber stamps used in offices to stamp the current date, and sometimes time, in ink on paper documents, to record when the document was received. Common examples of this type of timestamp are a postmark on a letter or the "in" and "out" times on a time card. In modern times usage of the term has expanded to refer to digital date and time information attached to digital data. For example, computer files contain timestamps that tell when the file was last modified, and digital cameras add timestamps to the pictures they take, recordin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distributed Algorithms
A distributed algorithm is an algorithm designed to run on computer hardware constructed from interconnected processors. Distributed algorithms are used in different application areas of distributed computing, such as telecommunications, scientific computing, distributed information processing, and real-time process control. Standard problems solved by distributed algorithms include leader election, consensus, distributed search, spanning tree generation, mutual exclusion, and resource allocation. Distributed algorithms are a sub-type of parallel algorithm, typically executed concurrently, with separate parts of the algorithm being run simultaneously on independent processors, and having limited information about what the other parts of the algorithm are doing. One of the major challenges in developing and implementing distributed algorithms is successfully coordinating the behavior of the independent parts of the algorithm in the face of processor failures and unreliable communica ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
