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any given network does not lie in the same place as the boundary between parallel and distributed systems shared memory vs message passing complexity measures edit in parallel algorithms yet another resource in addition to time and space is the number of computers indeed often there is a trade off between the running time and the number of computers the problem can be solved faster if there are more computers running in parallel see speedup if a decision problem can be solved in polylogarithmic time by using a polynomial number of processors then the problem is said to be in the class nc 66 the class nc can be defined equally well by using the pram formalism or boolean circuits pram machines can simulate boolean circuits efficiently and vice versa 67 in the analysis of distributed algorithms more attention is usually paid on communication operations than computational steps perhaps the simplest model of distributed computing is a synchronous system where all nodes operate in a lockstep fashion this model is commonly known as the local model during each communication round all nodes in parallel 1 receive the latest messages from their neighbours 2 perform arbitrary local computation and 3 send new messages to their neighbors in such systems a central complexity measure is the number of synchronous communication rounds required to complete the task 68 this complexity measure is closely related to the diameter of the network let d be the diameter of the network on the one hand any computable problem can be solved trivially in a synchronous distributed system in approximately 2 d communication rounds simply gather all information in one location d rounds solve the problem and inform each node about the solution d rounds on the other hand if the running time of the algorithm is much smaller than d communication rounds then the nodes in the network must produce their output without having the possibility to obtain information about distant parts of the network in other words the nodes must make globally consistent decisions based on information that is available in their local d neighbourhood many distributed algorithms are known with the running time much smaller than d rounds and understanding which problems can be solved by such algorithms is one of the central research questions of the field 69 typically an algorithm which solves a problem in polylogarithmic time in the network size is considered efficient in this model another commonly used measure is the total number of bits transmitted in the network cf communication complexity 70 the features of this concept are typically captured with the congest b model which is similarly defined as the local model but where single messages can only contain b bits other problems edit traditional computational problems take the perspective that the user asks a question a computer or a distributed system processes the question then produces an answer and stops however there are also problems where the system is required not to stop including the dining philosophers problem and other similar mutual exclusion problems in these problems the distributed system is supposed to continuously coordinate the use of shared resources so that no conflicts or deadlocks occur there are also fundamental challenges that are unique to distributed computing for example those related to fault tolerance examples of related problems include consensus problems 71 byzantine fault tolerance 72 and self stabilisation 73 much research is also focused on understanding the asynchronous nature of distributed systems synchronizers can be used to run synchronous algorithms in asynchronous systems 74 logical clocks provide a causal happened before ordering of events 75 clock synchronization algorithms provide globally consistent physical time stamps 76 note that in distributed systems latency should be measured through 99th percentile because median and average can be misleading 77 election edit coordinator election or leader election is the process of designating a single process as the organizer of some task distributed among several computers nodes before the task is begun all network nodes are either unaware which node will serve as the coordinator or leader of the task or unable to communicate with the current coordinator after a coordinator election algorithm has been run however each node throughout the network recognizes a particular unique node as the task coordinator 78 the network nodes communicate among themselves in order to decide which of them will get into the coordinator state for that they need some method in order to break the symmetry among them for example if each node has unique and comparable identities then the nodes can compare their identities and decide that the node with the highest identity is the coordinator 78 the definition of this problem is often attributed to lelann who formalized it as a method to create a new token in a token ring network in which the token has been lost 79 coordinator election algorithms are designed to be economical in terms of total bytes transmitted and time the algorithm suggested by gallager humblet and spira 80 for general undirected graphs has had a strong impact on the design of distributed algorithms in general and won the dijkstra prize for an influential paper in distributed computing many other algorithms were suggested for different kinds of network graphs such as undirected rings unidirectional rings complete graphs grids directed euler graphs and others a general method that decouples the issue of the graph family from the design of the coordinator election algorithm was suggested by korach kutten and moran 81 in order to perform coordination distributed systems employ the concept of coordinators the coordinator election problem is to choose a process from among a group of processes on different processors in a distributed system to act as the central coordinator several central coordinator election algorithms exist 82 properties of distributed systems edit so far the focus has been on designing a distributed system that solves a given problem a complementary research problem is studying the properties of a given distributed system 83 84 the halting problem is an analogous example from the field of centralised computation we are given a computer program and the task is to decide whether it halts or runs forever the halting problem is undecidable in the general case and naturally understanding the behaviour of a computer network is at least as hard as understanding the behaviour of one computer 85 however there are many interesting special cases that are decidable in particular it is possible to reason about the behaviour of a network of finite state machines one example is telling whether a given network of interacting asynchronous and non deterministic finite state machines can reach a deadlock this problem is pspace complete 86 i e it is decidable but not likely that there is an efficient centralised parallel or distributed algorithm that solves the problem in the case of large networks other topics edit linearizability see also edit actor model model of concurrent computation code mobility process in distributed computing dataflow programming computer programming paradigm decentralized computing distribution of jobs across different computers distributed algorithm algorithm run on hardware built from interconnected processors distributed algorithmic mechanism design distributed cache type of computer cache distributed networking multi source interconnected computing distributed operating system operating system designed to operate on multiple systems over a network computer eventual consistency consistency model used in distributed computing to achieve high availability edsger w dijkstra prize in distributed computing annual conference on computing pages displaying short descriptions of redirect targets federation information technology group of network or telecommunication providers agreeing upon interoperability standards flat neighborhood network fog computing architecture that uses edge devices grid computing use of widely distributed computer resources to reach a common goal internet gis internet technologies regarding spatial data jungle computing type of distributed computing layered queueing network library oriented architecture loa list of distributed computing conferences list of volunteer computing projects model checking computer science field parallel distributed processing cognitive science approach pages displaying short descriptions of redirect targets parallel programming model abstraction of parallel computer architecture shared nothing architecture type of distributed computing architecture notes edit 1 2 tanenbaum andrew s steen maarten van 2002 distributed systems principles and paradigms upper saddle river nj pearson prentice hall isbn 0 13 088893 1 archived from the original on 2020 08 12 retrieved 2020 08 28 distributed programs texts in computer science london springer london 2010 pp 373 406 doi 10 1007 978 1 84882 745 5_11 isbn 978 1 84882 744 8 issn 1868 0941 systems consist of a number of physically distributed components that work independently using their private storage but also communicate from time to time by explicit message passing such systems are called distributed systems dusseau dusseau 2016 p 1 2 ford neal march 3 2020 fundamentals of software architecture an engineering approach 1st ed o reilly media pp 146 147 isbn 978 1 4920 4345 4 monolith to microservices evolutionary patterns to transform your monolith o reilly media isbn 978 1 4920 4781 0 building serverless applications on knative o reilly media isbn 978 1 0981 4204 9 distributed programs texts in computer science london springer london 2010 pp 373 406 doi 10 1007 978 1 84882 745 5_11 isbn 978 1 84882 744 8 issn 1868 0941 distributed programs are abstract descriptions of distributed systems a distributed program 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reilly media isbn 978 1 4919 5035 7 richardson chris 2019 microservices patterns with examples in java shelter island ny manning publications isbn 978 1 61729 454 9 christudas binildas 2019 practical microservices architectural patterns event based java microservices with spring boot and spring cloud berkeley ca apress l p isbn 978 1 4842 4501 9 newman sam 2015 02 20 building microservices o reilly media isbn 978 1 4919 5035 7 richardson chris 2019 microservices patterns with examples in java shelter island ny manning publications isbn 978 1 61729 454 9 christudas binildas 2019 practical microservices architectural patterns event based java microservices with spring boot and spring cloud berkeley ca apress l p isbn 978 1 4842 4501 9 elmasri navathe 2000 section 24 1 2 andrews 2000 p 10 11 ghosh 2007 p 4 6 lynch 1996 p xix 1 peleg 2000 p xv elmasri navathe 2000 section 24 haussmann j 2019 cost efficient parallel processing of irregularly structured problems in cloud computing 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