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Brooks–Iyengar Algorithm
The Brooks–Iyengar algorithm or FuseCPA Algorithm or Brooks–Iyengar hybrid algorithm is a distributed algorithm that improves both the precision and accuracy of the interval measurements taken by a distributed sensor network, even in the presence of faulty sensors. The sensor network does this by exchanging the measured value and accuracy value at every node with every other node, and computes the accuracy range and a measured value for the whole network from all of the values collected. Even if some of the data from some of the sensors is faulty, the sensor network will not malfunction. The algorithm is fault-tolerant and distributed. It could also be used as a sensor fusion method. The precision and accuracy bound of this algorithm have been proved in 2016. Background The Brooks–Iyengar hybrid algorithm for distributed control in the presence of noisy data combines Byzantine agreement with sensor fusion. It bridges the gap between sensor fusion and Byzantine fault toleran ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distributed Algorithm
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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
History Of Brooks-Iyengar Algorithm
History is the systematic study of the past, focusing primarily on the human past. As an academic discipline, it analyses and interprets evidence to construct narratives about what happened and explain why it happened. Some theorists categorize history as a social science, while others see it as part of the humanities or consider it a hybrid discipline. Similar debates surround the purpose of history—for example, whether its main aim is theoretical, to uncover the truth, or practical, to learn lessons from the past. In a more general sense, the term ''history'' refers not to an academic field but to the past itself, times in the past, or to individual texts about the past. Historical research relies on primary and secondary sources to reconstruct past events and validate interpretations. Source criticism is used to evaluate these sources, assessing their authenticity, content, and reliability. Historians strive to integrate the perspectives of several sources to develop a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Intersection Algorithm
The intersection algorithm is an agreement algorithm used to select sources for estimating accurate time from a number of noisy time sources. It forms part of the modern Network Time Protocol. It is a modified form of Marzullo's algorithm.Digital Time Service Functional Specification Version T.1.0.5. Digital Equipment Corporation, 1989. While Marzullo's algorithm will return the smallest interval consistent with the largest number of sources, the returned interval does not necessarily include the center point (calculated offset) of all the sources in the intersection. The intersection algorithm returns an interval that includes that returned by Marzullo's algorithm but may be larger since it will include the center points. This larger interval allows using additional statistical data to select a point within the interval, reducing the jitter in repeated execution. Method Given ''M'' intervals of the form ''c'' ± ''r'' (which means 'c''−''r'',''c''+''r'', the alg ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Marzullo's Algorithm
Marzullo's algorithm, invented by Keith Marzullo for his Ph.D. dissertation in 1984, is an ''agreement algorithm'' used to select sources for estimating accurate time from a number of noise, noisy time sources. A refined version of it, renamed the "intersection algorithm", forms part of the modern Network Time Protocol. Marzullo's algorithm is also used to compute the relaxed intersection of n boxes (or more generally ''n'' subsets of R''n''), as required by several Set_estimation, robust set estimation methods. Purpose Marzullo's algorithm is efficient in terms of time for producing an optimal value from a set of estimates with confidence intervals where the actual value may be outside the confidence interval for some sources. In this case the best estimate is taken to be the smallest interval consistent with the largest number of sources. If we have the estimates 10 ± 2, 12 ± 1 and 11 ± 1 then these intervals are [8,12], [11,13] and [10,12] whic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Raft Consensus Algorithm
Raft is a consensus algorithm designed as an alternative to the Paxos family of algorithms. It was meant to be more understandable than Paxos by means of separation of logic, but it is also formally proven safe and offers some additional features. Raft offers a generic way to distribute a state machine across a cluster of computing systems, ensuring that each node in the cluster agrees upon the same series of state transitions. It has a number of open-source reference implementations, with full-specification implementations in Go, C++, Java, and Scala. It is named after Reliable, Replicated, Redundant, And Fault-Tolerant. Raft is not a Byzantine fault tolerant (BFT) algorithm; the nodes trust the elected leader. Basics Raft achieves consensus via an elected leader. A server in a raft cluster is either a ''leader'' or a ''follower'', and can be a ''candidate'' in the precise case of an election (leader unavailable). The leader is responsible for log replication to the fol ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Paxos (computer Science)
Paxos is a family of protocols for solving consensus in a network of unreliable or fallible processors. Consensus is the process of agreeing on one result among a group of participants. This problem becomes difficult when the participants or their communications may experience failures. Consensus protocols are the basis for the state machine replication approach to distributed computing, as suggested by Leslie Lamport and surveyed by Fred Schneider. State machine replication is a technique for converting an algorithm into a fault-tolerant, distributed implementation. Ad-hoc techniques may leave important cases of failures unresolved. The principled approach proposed by Lamport et al. ensures all cases are handled safely. The Paxos protocol was first submitted in 1989 and named after a fictional legislative consensus system used on the Paxos island in Greece, where Lamport wrote that the parliament had to function "even though legislators continually wandered in and out of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 rotati ...[...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) on 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 p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fault Tolerance
Fault tolerance is the ability of a system to maintain proper operation despite failures or faults in one or more of its components. This capability is essential for high-availability, mission-critical, or even life-critical systems. Fault tolerance specifically refers to a system's capability to handle faults without any degradation or downtime. In the event of an error, end-users remain unaware of any issues. Conversely, a system that experiences errors with some interruption in service or graceful degradation of performance is termed 'resilient'. In resilience, the system adapts to the error, maintaining service but acknowledging a certain impact on performance. Typically, fault tolerance describes computer systems, ensuring the overall system remains functional despite hardware or software issues. Non-computing examples include structures that retain their integrity despite damage from fatigue, corrosion or impact. History The first known fault-tolerant computer was ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sensor Fusion
Sensor fusion is a process of combining sensor data or data derived from disparate sources so that the resulting information has less uncertainty than would be possible if these sources were used individually. For instance, one could potentially obtain a more accurate location estimate of an indoor object by combining multiple data sources such as video cameras and WiFi localization signals. The term ''uncertainty reduction'' in this case can mean more accurate, more complete, or more dependable, or refer to the result of an emerging view, such as stereoscopic vision (calculation of depth information by combining two-dimensional images from two cameras at slightly different viewpoints). The data sources for a fusion process are not specified to originate from identical sensors. One can distinguish ''direct fusion'', ''indirect fusion'' and fusion of the outputs of the former two. Direct fusion is the fusion of sensor data from a set of heterogeneous or homogeneous sensors, soft s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distributed Sensor Network
Wireless sensor networks (WSNs) refer to networks of spatially dispersed and dedicated sensors that monitor and record the physical conditions of the environment and forward the collected data to a central location. WSNs can measure environmental conditions such as temperature, sound, pollution levels, humidity and wind. These are similar to wireless ad hoc networks in the sense that they rely on wireless connectivity and spontaneous formation of networks so that sensor data can be transported wirelessly. WSNs monitor physical conditions, such as temperature, sound, and pressure. Modern networks are bi-directional, both collecting data and enabling control of sensor activity. The development of these networks was motivated by military applications such as battlefield surveillance. Such networks are used in industrial and consumer applications, such as industrial process monitoring and control and machine health monitoring and agriculture. A WSN is built of "nodes" – from a fe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Two Generals' Problem
In computing, the Two Generals' Problem is a thought experiment meant to illustrate the pitfalls and design challenges of attempting to coordinate an action by communicating over an unreliable link. In the experiment, two generals are only able to communicate with one another by sending a messenger through enemy territory. The experiment asks how they might reach an agreement on the time to launch an attack, while knowing that any messenger they send could be captured. The Two Generals' Problem appears often as an introduction to the more general Byzantine Generals problem in introductory classes about computer networking (particularly with regard to the Transmission Control Protocol, where it shows that TCP cannot guarantee state consistency between endpoints and why this is the case), though it applies to any type of two-party communication where failures of communication are possible. A key concept in epistemic logic, this problem highlights the importance of common knowledge. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
