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sequential general purpose computer citation needed the discussion below focuses on the case of multiple computers although many of the issues are the same for concurrent processes running on a single computer three viewpoints are commonly used parallel algorithms in shared memory model all processors have access to a shared memory the algorithm designer chooses the program executed by each processor one theoretical model is the parallel random access machines pram that are used 59 however the classical pram model assumes synchronous access to the shared memory shared memory programs can be extended to distributed systems if the underlying operating system encapsulates the communication between nodes and virtually unifies the memory across all individual systems a model that is closer to the behavior of real world multiprocessor machines and takes into account the use of machine instructions such as compare and swap cas is that of asynchronous shared memory there is a wide body of work on this model a summary of which can be found in the literature 60 61 parallel algorithms in message passing model the algorithm designer chooses the structure of the network as well as the program executed by each computer models such as boolean circuits and sorting networks are used 62 a boolean circuit can be seen as a computer network each gate is a computer that runs an extremely simple computer program similarly a sorting network can be seen as a computer network each comparator is a computer distributed algorithms in message passing model the algorithm designer only chooses the computer program all computers run the same program the system must work correctly regardless of the structure of the network a commonly used model is a graph with one finite state machine per node in the case of distributed algorithms computational problems are typically related to graphs often the graph that describes the structure of the computer network is the problem instance this is illustrated in the following example 63 an example edit consider the computational problem of finding a coloring of a given graph g different fields might take the following approaches centralized algorithms 63 the graph g is encoded as a string and the string is given as input to a computer the computer program finds a coloring of the graph encodes the coloring as a string and outputs the result parallel algorithms again the graph g is encoded as a string however multiple computers can access the same string in parallel each computer might focus on one part of the graph and produce a coloring for that part the main focus is on high performance computation that exploits the processing power of multiple computers in parallel distributed algorithms the graph g is the structure of the computer network there is one computer for each node of g and one communication link for each edge of g initially each computer only knows about its immediate neighbors in the graph g the computers must exchange messages with each other to discover more about the structure of g each computer must produce its own color as output the main focus is on coordinating the operation of an arbitrary distributed system 63 while the field of parallel algorithms has a different focus than the field of distributed algorithms there is much interaction between the two fields for example the cole vishkin algorithm for graph coloring 64 was originally presented as a parallel algorithm but the same technique can also be used directly as a distributed algorithm moreover a parallel algorithm can be implemented either in a parallel system using shared memory or in a distributed system using message passing 65 the traditional boundary between parallel and distributed algorithms choose a suitable network vs run in 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 consists of a collection of processes that work concurrently and communicate by explicit message passing each process can access a set of variables which are disjoint from the variables that can be changed by any other process andrews 2000 dolev 2000 ghosh 2007 p 10 magnoni l 2015 modern messaging for distributed sytems sic journal of physics conference series 608 1 012038 bibcode 2015jphcs 608a2038m doi 10 1088 1742 6596 608 1 012038 issn 1742 6596 godfrey 2002 1 2 andrews 2000 p 291 292 dolev 2000 p 5 lynch 1996 p 1 1 2 ghosh 2007 p 10 andrews 2000 pp 8 9 291 dolev 2000 p 5 ghosh 2007 p 3 lynch 1996 p xix 1 peleg 2000 p xv andrews 2000 p 291 ghosh 2007 p 3 peleg 2000 p 4 ghosh 2007 p 3 4 peleg 2000 p 1 ghosh 2007 p 4 peleg 2000 p 2 ghosh 2007 p 4 8 lynch 1996 p 2 3 peleg 2000 p 4 lynch 1996 p 2 peleg 2000 p 1 ghosh 2007 p 7 lynch 1996 p xix 2 peleg 2000 p 4 fundamentals of software architecture an engineering approach o reilly media 2020 isbn 978 1 4920 4345 4 1 2 3 4 kleppmann martin 2017 designing data intensive applications the big ideas behind reliable scalable and maintainable systems o reilly media isbn 978 1 4493 7332 0 1 2 3 4 building event driven microservices leveraging organizational data at scale isbn 978 ...
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