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59-429: FLP may refer to: Computer science [ edit ] FLP impossibility proof in computer science Functional logic programming Organizations [ edit ] Family Limited Partnership , holding companies Forever Living Products , a US MLM company Politics [ edit ] Farmer–Labor Party , a former US party Fatherland Party (Norway) ,

118-511: A distributed lock service library called Chubby . Chubby maintains lock information in small files which are stored in a replicated database to achieve high availability in the face of failures. The database is implemented on top of a fault-tolerant log layer which is based on the Paxos consensus algorithm . In this scheme, Chubby clients communicate with the Paxos master in order to access/update

177-473: A process is the instance of a computer program that is being executed by one or many threads . There are many different process models, some of which are light weight, but almost all processes (even entire virtual machines ) are rooted in an operating system (OS) process which comprises the program code, assigned system resources, physical and logical access permissions, and data structures to initiate, control and coordinate execution activity. Depending on

236-402: A shell pipeline , the output of the first process needs to pass to the second one, and so on. Another example is a task that has been decomposed into cooperating but partially independent processes which can run simultaneously (i.e., using concurrency, or true parallelism – the latter model is a particular case of concurrent execution and is feasible whenever multiple CPU cores are available for

295-740: A virtual memory system, where regions of a process's memory may be really on disk and not in main memory at any time. Even portions of active processes/tasks (executing programs) are eligible for swapping to disk, if the portions have not been used recently. Not all parts of an executing program and its data have to be in physical memory for the associated process to be active. An operating system kernel that allows multitasking needs processes to have certain states . Names for these states are not standardised, but they have similar functionality. When processes need to communicate with each other they must share parts of their address spaces or use other forms of inter-process communication (IPC). For instance in

354-447: A 'proof of stake' over a 'proof of work' system, is the high energy consumption demanded by the latter. As an example, bitcoin mining (2018) is estimated to consume non-renewable energy sources at an amount similar to the entire nations of Czech Republic or Jordan, while the total energy consumption of Ethereum, the largest proof of stake network, is just under that of 205 average US households. Some cryptocurrencies, such as Ripple, use

413-457: A Byzantine consensus algorithm, simply by creating enough virtual participants to overwhelm the fault tolerance threshold. A permissionless consensus protocol, in contrast, allows anyone in the network to join dynamically and participate without prior permission, but instead imposes a different form of artificial cost or barrier to entry to mitigate the Sybil attack threat. Bitcoin introduced

472-428: A difficulty adjustment function and a reorganization function to achieve permissionless consensus in its open peer-to-peer network. To extend bitcoin's blockchain or distributed ledger , miners attempt to solve a cryptographic puzzle, where probability of finding a solution is proportional to the computational effort expended in hashes per second. The node that first solves such a puzzle has their proposed version of

531-902: A former party (Norwegian: Fedrelandspartiet ) Fiji Labour Party Finnish Rural Party , a former party (Swedish: Finlands landsbygdsparti ) Le front de libération populaire , a former party in Quebec, Canada Popular Liberation Front (Spain) , a former party (Spanish: Frente de Liberación Popular ) Science [ edit ] Flurbiprofen Frustrated Lewis pair Transportation [ edit ] Lugano–Ponte Tresa railway (Italian: Ferrovia Lugano–Ponte Tresa ) Marion County Regional Airport , in Arkansas, United States Satish Dhawan Space Centre First Launch Pad , in India See also [ edit ] Windows Fundamentals for Legacy PCs (WinFLP) Topics referred to by

590-630: A higher consensus number. The consensus numbers form what is called Herlihy 's hierarchy of synchronization objects. According to the hierarchy, read/write registers cannot solve consensus even in a 2-process system. Data structures like stacks and queues can only solve consensus between two processes. However, some concurrent objects are universal (notated in the table with ∞ {\displaystyle \infty } ), which means they can solve consensus among any number of processes and they can simulate any other objects through an operation sequence. Process (computing) In computing ,

649-544: A lengthy delay. Of the two types of failures, Byzantine failures are far more disruptive. Thus, a consensus protocol tolerating Byzantine failures must be resilient to every possible error that can occur. A stronger version of consensus tolerating Byzantine failures is given by strengthening the Integrity constraint: The consensus problem may be considered in the case of asynchronous or synchronous systems. While real world communications are often inherently asynchronous, it

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708-400: A limited number of faulty processes . These protocols must satisfy several requirements to be useful. For instance, a trivial protocol could have all processes output binary value 1. This is not useful; thus, the requirement is modified such that the production must depend on the input. That is, the output value of a consensus protocol must be the input value of some process. Another requirement

767-472: A polynomial time binary consensus protocol that tolerates Byzantine failures is the Phase King algorithm by Garay and Berman. The algorithm solves consensus in a synchronous message passing model with n processes and up to f failures, provided n > 4 f . In the phase king algorithm, there are f + 1 phases, with 2 rounds per phase. Each process keeps track of its preferred output (initially equal to

826-460: A process may undergo, a crash failure or a Byzantine failure . A crash failure occurs when a process abruptly stops and does not resume. Byzantine failure s are failures in which absolutely no conditions are imposed. For example, they may occur as a result of the malicious actions of an adversary. A process that experiences a Byzantine failure may send contradictory or conflicting data to other processes, or it may sleep and then resume activity after

885-561: A public value and generate a consensus vector with the following requirements: It can be shown that variations of these problems are equivalent in that the solution for a problem in one type of model may be the solution for another problem in another type of model. For example, a solution to the Weak Byzantine General problem in a synchronous authenticated message passing model leads to a solution for Weak Interactive Consistency. An interactive consistency algorithm can solve

944-540: A single consensus value. The consensus problem is a fundamental problem in controlling multi-agent systems. One approach to generating consensus is for all processes (agents) to agree on a majority value. In this context, a majority requires at least one more than half of the available votes (where each process is given a vote). However, one or more faulty processes may skew the resultant outcome such that consensus may not be reached or may be reached incorrectly. Protocols that solve consensus problems are designed to deal with

1003-556: A stronger, transferable form of authentication, where each message is signed by the sender, so that a receiver knows not just the immediate source of every message, but the participant that initially created the message. This stronger type of authentication is achieved by digital signatures, and when this stronger form of authentication is available, protocols can tolerate a larger number of faults. The two different authentication models are often called oral communication and written communication models. In an oral communication model,

1062-931: A system of validating nodes to validate the ledger. This system used by Ripple, called Ripple Protocol Consensus Algorithm (RPCA), works in rounds: Other participation rules used in permissionless consensus protocols to impose barriers to entry and resist sybil attacks include proof of authority , proof of space , proof of burn, or proof of elapsed time. Contrasting with the above permissionless participation rules, all of which reward participants in proportion to amount of investment in some action or resource, proof of personhood protocols aim to give each real human participant exactly one unit of voting power in permissionless consensus, regardless of economic investment. Proposed approaches to achieving one-per-person distribution of consensus power for proof of personhood include physical pseudonym parties, social networks, pseudonymized government-issued identities, and biometrics. To solve

1121-403: A time: it is impossible to run more programs at the same time. A program might need some resource , such as an input device, which has a large delay, or a program might start some slow operation, such as sending output to a printer. This would lead to processor being "idle" (unused). To keep the processor busy at all times, the execution of such a program is halted and the operating system switches

1180-455: A transaction committed to a database. A special case of the single-value consensus problem, called binary consensus , restricts the input, and hence the output domain, to a single binary digit {0,1}. While not highly useful by themselves, binary consensus protocols are often useful as building blocks in more general consensus protocols, especially for asynchronous consensus. In multi-valued consensus protocols such as Multi-Paxos and Raft ,

1239-410: A value v {\displaystyle v} to all processes such that: It is also known as The General's Problem. Formal requirements for a consensus protocol may include: For n processes in a partially synchronous system (the system alternates between good and bad periods of synchrony), each process chooses a private value. The processes communicate with each other by rounds to determine

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1298-416: Is "something that takes up time", as opposed to "memory", which is "something that takes up space". The above description applies to both processes managed by an operating system, and processes as defined by process calculi . If a process requests something for which it must wait, it will be blocked. When the process is in the blocked state , it is eligible for swapping to disk, but this is transparent in

1357-421: Is allowed, whereas in others processes are completely anonymous. Shared memory models in which processes communicate by accessing objects in shared memory are also an important area of research. In most models of communication protocol participants communicate through authenticated channels. This means that messages are not anonymous, and receivers know the source of every message they receive. Some models assume

1416-465: Is called concurrency . For security and reliability, most modern operating systems prevent direct communication between independent processes, providing strictly mediated and controlled inter-process communication. In general, a computer system process consists of (or is said to own ) the following resources: The operating system holds most of this information about active processes in data structures called process control blocks . Any subset of

1475-522: Is different from Wikidata All article disambiguation pages All disambiguation pages Consensus (computer science)#Solvability results for some agreement problems 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 put forth their candidate values, communicate with one another, and agree on

1534-589: Is given in Big O notation in the number of rounds of message exchange as a function of some input parameters (typically the number of processes and/or the size of the input domain). Message complexity refers to the amount of message traffic that is generated by the protocol. Other factors may include memory usage and the size of messages. Varying models of computation may define a "consensus problem". Some models may deal with fully connected graphs, while others may deal with rings and trees. In some models message authentication

1593-430: Is more practical and often easier to model synchronous systems, given that asynchronous systems naturally involve more issues than synchronous ones. In synchronous systems, it is assumed that all communications proceed in rounds . In one round, a process may send all the messages it requires, while receiving all messages from other processes. In this manner, no message from one round may influence any messages sent within

1652-550: Is no consensus solution that can tolerate one or more crash failures even when only requiring the non triviality property. This result is sometimes called the FLP impossibility proof named after the authors Michael J. Fischer , Nancy Lynch , and Mike Paterson who were awarded a Dijkstra Prize for this significant work. The FLP result has been mechanically verified to hold even under fairness assumptions . However, FLP does not state that consensus can never be reached: merely that under

1711-439: Is provided by CPU's time-sharing that is a method for interleaving the execution of users' processes and threads, and even of independent kernel tasks – although the latter feature is feasible only in preemptive kernels such as Linux . Preemption has an important side effect for interactive processes that are given higher priority with respect to CPU bound processes, therefore users are immediately assigned computing resources at

1770-403: Is said to own resources, of which an image of its program (in memory) is one such resource. However, in multiprocessing systems many processes may run off of, or share, the same reentrant program at the same location in memory, but each process is said to own its own image of the program. Processes are often called "tasks" in embedded operating systems. The sense of "process" (or task)

1829-406: Is that a process may decide upon an output value only once, and this decision is irrevocable. A method is correct in an execution if it does not experience a failure. A consensus protocol tolerating halting failures must satisfy the following properties. Variations on the definition of integrity may be appropriate, according to the application. For example, a weaker type of integrity would be for

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1888-416: Is the number of failures and n {\displaystyle n} is the number of processes. For systems with n {\displaystyle n} processors, of which f {\displaystyle f} are Byzantine, it has been shown that there exists no algorithm that solves the consensus problem for n ≤ 3 f {\displaystyle n\leq 3f} in

1947-413: The oral-messages model . The proof is constructed by first showing the impossibility for the three-node case n = 3 {\displaystyle n=3} and using this result to argue about partitions of processors. In the written-messages model there are protocols that can tolerate n = f + 1 {\displaystyle n=f+1} . In a fully asynchronous system there

2006-461: The OS, a process may be made up of multiple threads of execution that execute instructions concurrently . While a computer program is a passive collection of instructions typically stored in a file on disk, a process is the execution of those instructions after being loaded from the disk into memory. Several processes may be associated with the same program; for example, opening up several instances of

2065-500: The appearance of many processes executing simultaneously (that is, in parallel ), though in fact only one process can be executing at any one time on a single CPU (unless the CPU has multiple cores, then multithreading or other similar technologies can be used). It is usual to associate a single process with a main program, and child processes with any spin-off, parallel processes, which behave like asynchronous subroutines. A process

2124-579: The consensus problem by having each process choose the majority value in its consensus vector as its consensus value. There is a t-resilient anonymous synchronous protocol which solves the Byzantine Generals problem , if t n < 1 3 {\displaystyle {\tfrac {t}{n}}<{\tfrac {1}{3}}} and the Weak Byzantine Generals case where t {\displaystyle t}

2183-421: The consensus problem in a shared-memory system, concurrent objects must be introduced. A concurrent object, or shared object, is a data structure which helps concurrent processes communicate to reach an agreement. Traditional implementations using critical sections face the risk of crashing if some process dies inside the critical section or sleeps for an intolerably long time. Researchers defined wait-freedom as

2242-510: The decision value to equal a value that some correct process proposed – not necessarily all of them. There is also a condition known as validity in the literature which refers to the property that a message sent by a process must be delivered. A protocol that can correctly guarantee consensus amongst n processes of which at most t fail is said to be t-resilient . In evaluating the performance of consensus protocols two factors of interest are running time and message complexity . Running time

2301-402: The delta to their own game state and comparing the game state hashes. If the hashes do not agree then a vote is cast, and those players whose game state is in the minority are disconnected and removed from the game (known as a desync.) Another well-known approach is called MSR-type algorithms which have been used widely from computer science to control theory. Bitcoin uses proof of work ,

2360-957: The first permissionless consensus protocol using proof of work and a difficulty adjustment function, in which participants compete to solve cryptographic hash puzzles, and probabilistically earn the right to commit blocks and earn associated rewards in proportion to their invested computational effort. Motivated in part by the high energy cost of this approach, subsequent permissionless consensus protocols have proposed or adopted other alternative participation rules for Sybil attack protection, such as proof of stake , proof of space , and proof of authority . Three agreement problems of interest are as follows. A collection of n {\displaystyle n} processes, numbered from 0 {\displaystyle 0} to n − 1 , {\displaystyle n-1,} communicate by sending messages to one another. Process 0 {\displaystyle 0} must transmit

2419-406: The first round and serves as a tie breaker. Each process then updates its preferred value as follows. If the count of the majority value the process observed in the first round is greater than n /2 + f , the process changes its preference to that majority value; otherwise it uses the phase king's value. At the end of f + 1 phases the processes output their preferred values. Google has implemented

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2478-439: The goal is to agree on not just a single value but a series of values over time, forming a progressively-growing history. While multi-valued consensus may be achieved naively by running multiple iterations of a single-valued consensus protocol in succession, many optimizations and other considerations such as reconfiguration support can make multi-valued consensus protocols more efficient in practice. There are two types of failures

2537-487: The guarantee that the algorithm completes in a finite number of steps. The consensus number of a concurrent object is defined to be the maximum number of processes in the system which can reach consensus by the given object in a wait-free implementation. Objects with a consensus number of n {\displaystyle n} can implement any object with a consensus number of n {\displaystyle n} or lower, but cannot implement any objects with

2596-438: The immediate source of information is known, whereas in stronger, written communication models, every step along the receiver learns not just the immediate source of the message, but the communication history of the message. In the most traditional single-value consensus protocols such as Paxos , cooperating nodes agree on a single value such as an integer, which may be of variable size so as to encode useful metadata such as

2655-463: The model's assumptions, no algorithm can always reach consensus in bounded time. In practice it is highly unlikely to occur. The Paxos consensus algorithm by Leslie Lamport , and variants of it such as Raft , are used pervasively in widely deployed distributed and cloud computing systems. These algorithms are typically synchronous, dependent on an elected leader to make progress, and tolerate only crashes and not Byzantine failures. An example of

2714-458: The network. Consensus algorithms traditionally assume that the set of participating nodes is fixed and given at the outset: that is, that some prior (manual or automatic) configuration process has permissioned a particular known group of participants who can authenticate each other as members of the group. In the absence of such a well-defined, closed group with authenticated members, a Sybil attack against an open consensus group can defeat even

2773-558: The network. In most normal situations, process scheduling has a degree of natural randomness. In an asynchronous model, some forms of failures can be handled by a synchronous consensus protocol. For instance, the loss of a communication link may be modeled as a process which has suffered a Byzantine failure. Randomized consensus algorithms can circumvent the FLP impossibility result by achieving both safety and liveness with overwhelming probability, even under worst-case scheduling scenarios such as an intelligent denial-of-service attacker in

2832-568: The next block of transactions added to the ledger and eventually accepted by all other nodes. As any node in the network can attempt to solve the proof-of-work problem, a Sybil attack is infeasible in principle unless the attacker has over 50% of the computational resources of the network. Other cryptocurrencies (e.g. Ethereum , NEO, STRATIS, ...) use proof of stake , in which nodes compete to append blocks and earn associated rewards in proportion to stake , or existing cryptocurrency allocated and locked or staked for some time period. One advantage of

2891-532: The operating system implementation, switches could be performed when tasks initiate and wait for completion of input/output operations, when a task voluntarily yields the CPU, on hardware interrupts , and when the operating system scheduler decides that a process has expired its fair share of CPU time (e.g, by the Completely Fair Scheduler of the Linux kernel ). A common form of multitasking

2950-426: The process's own input value). In the first round of each phase each process broadcasts its own preferred value to all other processes. It then receives the values from all processes and determines which value is the majority value and its count. In the second round of the phase, the process whose id matches the current phase number is designated the king of the phase. The king broadcasts the majority value it observed in

3009-629: The processes that are ready to run). It is even possible for two or more processes to be running on different machines that may run different operating system (OS), therefore some mechanisms for communication and synchronization (called communications protocols for distributed computing) are needed (e.g., the Message Passing Interface {MPI}). By the early 1960s, computer control software had evolved from monitor control software , for example IBSYS , to executive control software . Over time, computers got faster while computer time

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3068-400: The processor to run another program. To the user, it will appear that the programs run at the same time (hence the term "parallel"). Shortly thereafter, the notion of a "program" was expanded to the notion of an "executing program and its context". The concept of a process was born, which also became necessary with the invention of re-entrant code . Threads came somewhat later. However, with

3127-399: The replicated log; i.e., read/write to the files. Many peer-to-peer online real-time strategy games use a modified lockstep protocol as a consensus protocol in order to manage game state between players in a game. Each game action results in a game state delta broadcast to all other players in the game along with a hash of the total game state. Each player validates the change by applying

3186-607: The resources, typically at least the processor state, may be associated with each of the process' threads in operating systems that support threads or child processes. The operating system keeps its processes separate and allocates the resources they need, so that they are less likely to interfere with each other and cause system failures (e.g., deadlock or thrashing ). The operating system may also provide mechanisms for inter-process communication to enable processes to interact in safe and predictable ways. A multitasking operating system may just switch between processes to give

3245-408: The same program often results in more than one process being executed. Multitasking is a method to allow multiple processes to share processors (CPUs) and other system resources. Each CPU (core) executes a single process at a time. However, multitasking allows each processor to switch between tasks that are being executed without having to wait for each task to finish ( preemption ). Depending on

3304-504: The same round. In a fully asynchronous message-passing distributed system, in which at least one process may have a crash failure , it has been proven in the famous 1985 FLP impossibility result by Fischer, Lynch and Paterson that a deterministic algorithm for achieving consensus is impossible. This impossibility result derives from worst-case scheduling scenarios, which are unlikely to occur in practice except in adversarial situations such as an intelligent denial-of-service attacker in

3363-403: The same term [REDACTED] This disambiguation page lists articles associated with the title FLP . If an internal link led you here, you may wish to change the link to point directly to the intended article. Retrieved from " https://en.wikipedia.org/w/index.php?title=FLP&oldid=1223563064 " Category : Disambiguation pages Hidden categories: Short description

3422-428: The simple pressing of a key or when moving a mouse. Furthermore, applications like video and music reproduction are given some kind of real-time priority, preempting any other lower priority process. In time-sharing systems, context switches are performed rapidly, which makes it seem like multiple processes are being executed simultaneously on the same processor. This seemingly-simultaneous execution of multiple processes

3481-626: Was still neither cheap nor fully utilized; such an environment made multiprogramming possible and necessary. Multiprogramming means that several programs run concurrently . At first, more than one program ran on a single processor, as a result of underlying uniprocessor computer architecture, and they shared scarce and limited hardware resources; consequently, the concurrency was of a serial nature. On later systems with multiple processors , multiple programs may run concurrently in parallel . Programs consist of sequences of instructions for processors. A single processor can run only one instruction at

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