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Dijkstra Prize
The Edsger W. Dijkstra Paper Prize in Distributed Computing is given for outstanding papers on the principles of distributed computing, whose significance and impact on the theory and/or practice of distributed computing has been evident for at least a decade. The paper prize has been presented annually since 2000. Originally the paper prize was presented at the ACM Symposium on Principles of Distributed Computing (PODC), and it was known as the PODC Influential-Paper Award. It was renamed in honor of Edsger W. Dijkstra in 2003, after he received the award for his work in self-stabilization in 2002 and died shortly thereafter. Since 2007,––– the paper prize is sponsored jointly by PODC and the EATCS International Symposium on Distributed Computing (DISC), and the presentation takes place alternately at PODC (even years) and DISC (odd years). The paper prize includes an award of $2000. Winners Funding The award is financed by ACM PODC and EATCS DISC, each providing an e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distributed Computing
A distributed system is a system whose components are located on different computer network, networked computers, which communicate and coordinate their actions by message passing, 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 clock synchronization, 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 service-oriented architecture, SOA-based systems to massively multiplayer online games to peer-to-peer, peer-to-peer applications. A computer program that runs within a distributed system is called a distributed program, and ''distributed programming' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Byzantine Agreement Problem
A Byzantine fault (also Byzantine generals problem, interactive consistency, source congruency, error avalanche, Byzantine agreement problem, and Byzantine failure) is a condition of a computer system, particularly distributed computing systems, where components may fail and there is imperfect information on whether a component has failed. The term takes its name from an allegory, the "Byzantine generals problem", developed to describe a situation in which, in order to avoid catastrophic failure of the system, the system's actors must agree on a concerted strategy, but some of these actors are unreliable. In a Byzantine fault, a component such as a server can inconsistently appear both failed and functioning to failure-detection systems, presenting different symptoms to different observers. It is difficult for the other components to declare it failed and shut it out of the network, because they need to first reach a consensus regarding which component has failed in the first pla ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Non-blocking Algorithm
In computer science, an algorithm is called non-blocking if failure or suspension of any thread cannot cause failure or suspension of another thread; for some operations, these algorithms provide a useful alternative to traditional blocking implementations. A non-blocking algorithm is lock-free if there is guaranteed system-wide progress, and wait-free if there is also guaranteed per-thread progress. "Non-blocking" was used as a synonym for "lock-free" in the literature until the introduction of obstruction-freedom in 2003. The word "non-blocking" was traditionally used to describe telecommunications networks that could route a connection through a set of relays "without having to re-arrange existing calls" (see Clos network). Also, if the telephone exchange "is not defective, it can always make the connection" (see nonblocking minimal spanning switch). Motivation The traditional approach to multi-threaded programming is to use locks to synchronize access to shared resourc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Population Protocol
A population protocol is a distributed computing model formed by resource-limited mobile agents which meet in a random way according to an interaction graph. Functions are computed by updating the state of agents whenever they meet based on their previous state, and the result of the computation can be read in the states of the agents once the computation has converged. Model There is a set N = \ of nodes. Each node is a finite automaton with s states. An important class of population protocols are majority algorithms, where the goal is to compute the majority bit: each node starts with a belief bit in \and the goal is to design a protocol at the end of which the belief bit of every node is the correct initial majority bit. The discrete time version of the model is as follows: at each point t=1,2,\ldotsin time, some node i is selected uniformly at random. Then the node is matched with another node j, which is chosen uniformly at random from the set of neighbors of node i. Afte ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Edge Coloring
In graph theory, an edge coloring of a graph is an assignment of "colors" to the edges of the graph so that no two incident edges have the same color. For example, the figure to the right shows an edge coloring of a graph by the colors red, blue, and green. Edge colorings are one of several different types of graph coloring. The edge-coloring problem asks whether it is possible to color the edges of a given graph using at most different colors, for a given value of , or with the fewest possible colors. The minimum required number of colors for the edges of a given graph is called the chromatic index of the graph. For example, the edges of the graph in the illustration can be colored by three colors but cannot be colored by two colors, so the graph shown has chromatic index three. By Vizing's theorem, the number of colors needed to edge color a simple graph is either its maximum degree or . For some graphs, such as bipartite graphs and high-degree planar graphs, the number of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Maximal Independent Set
In graph theory, a maximal independent set (MIS) or maximal stable set is an independent set that is not a subset of any other independent set. In other words, there is no vertex outside the independent set that may join it because it is maximal with respect to the independent set property. For example, in the graph , a path with three vertices , , and , and two edges and , the sets and are both maximally independent. The set is independent, but is not maximal independent, because it is a subset of the larger independent set In this same graph, the maximal cliques are the sets and A MIS is also a dominating set in the graph, and every dominating set that is independent must be maximal independent, so MISs are also called independent dominating sets. A graph may have many MISs of widely varying sizes; the largest, or possibly several equally large, MISs of a graph is called a maximum independent set. The graphs in which all maximal independent sets have the same siz ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Algorithms
In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can perform automated deductions (referred to as automated reasoning) and use mathematical and logical tests to divert the code execution through various routes (referred to as automated decision-making). Using human characteristics as descriptors of machines in metaphorical ways was already practiced by Alan Turing with terms such as "memory", "search" and "stimulus". In contrast, a heuristic is an approach to problem solving that may not be fully specified or may not guarantee correct or optimal results, especially in problem domains where there is no well-defined correct or optimal result. As an effective method, an algorithm can be expressed within a finite amount of space and ... [...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] |
Randomized Algorithms
A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure. The algorithm typically uses uniformly random bits as an auxiliary input to guide its behavior, in the hope of achieving good performance in the "average case" over all possible choices of random determined by the random bits; thus either the running time, or the output (or both) are random variables. One has to distinguish between algorithms that use the random input so that they always terminate with the correct answer, but where the expected running time is finite (Las Vegas algorithms, for example Quicksort), and algorithms which have a chance of producing an incorrect result (Monte Carlo algorithms, for example the Monte Carlo algorithm for the MFAS problem) or fail to produce a result either by signaling a failure or failing to terminate. In some cases, probabilistic algorithms are the only practical means of solving a problem. In common practice, randomized algor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fault Tolerance
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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Chandy–Lamport Algorithm
The Chandy–Lamport algorithm is a snapshot algorithm that is used in distributed systems for recording a consistent global state of an asynchronous communication, asynchronous system. It was developed by and named after Leslie Lamport and K. Mani Chandy. Leslie Lamport, K. Mani Chandy''Distributed Snapshots: Determining Global States of a Distributed System'' In: ''ACM Transactions on Computer Systems 3''. Nr. 1, Februar 1985.PDF; 1 MB History According t “The distributed snapshot algorithm described here came about when I visited Chandy, who was then at the University of Texas at Austin, University of Texas in Austin. He posed the problem to me over dinner, but we had both had too much wine to think about it right then. The next morning, in the shower, I came up with the solution. When I arrived at Chandy's office, he was waiting for me with the same solution.” Definition The assumptions of the algorithm are as follows: * There are no failures and all messages arrive ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Transactional Memory
In computer science and engineering, transactional memory attempts to simplify concurrent programming by allowing a group of load and store instructions to execute in an atomic way. It is a concurrency control mechanism analogous to database transactions for controlling access to shared memory in concurrent computing. Transactional memory systems provide high-level abstraction as an alternative to low-level thread synchronization. This abstraction allows for coordination between concurrent reads and writes of shared data in parallel systems. Motivation In concurrent programming, synchronization is required when parallel threads attempt to access a shared resource. Low-level thread synchronization constructs such as locks are pessimistic and prohibit threads that are outside a critical section from making any changes. The process of applying and releasing locks often functions as additional overhead in workloads with little conflict among threads. Transactional memory provides o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
