 | This article may be confusing or unclear to readers.(January 2015) |
Safe semantics is a computer hardware consistency model. It describes one type of guarantee that a data register provides when it is shared by several processors in a parallel computer or in a network of computers working together.
Safe semantics was first defined by Leslie Lamport in 1985. [1] It was formally defined in Lamport's "On Interprocess Communication" in 1986. [2]
Safe register has been implemented in many distributed systems.
Safe semantics are defined for a variable with a single writer but multiple readers (SWMR). A SWMR register is safe if each read operation satisfies these properties:
In particular, given concurrency of a read and a write operation, the read can return a value that has not been written by a write. The return value need only belong to the register domain.
A binary safe register can be seen as modeling a bit flickering. Whatever the previous value of the register is, its value could flicker until the write finishes. Therefore, the read that overlaps with a write could return 0 or 1.
Churn refers to the entry and exit of servers to/from a distributed system. Baldoni et al. show that no register can have the stronger property of regular semantics in a synchronous system under continuous churn. [3] However, a safe register can be implemented under continuous churn in a non-synchronous system. [4] Modeling and implementing a type of storage memory (Safe Register) under non-quiescent churn requires some system models such as client and server systems. [4] Client systems contains a finite, arbitrary number of processes that are responsible for reading and writing the server system. However, the server system must ensure that read and write operations happen properly.
Safe register implementation involves:
Safe register is maintained by the set of active servers.
Clients maintain no register information.
Eventually synchronous system
Quora (set of server or client systems)
Size of the Read and Write operation executed on quora = n – f – J (n is the number of servers, J is the number of servers that enter and exit, and f is the number of Byzantine failures.
Algorithms such as join, read, and write. [4]
A server (si) that wants to enter a server system broadcasts an inquiry message to other servers to inform them of its entry, si requests a current value of the register. Once other server receive this inquiry they send reply messages to si. After si receives enough replies from other servers, it collects the replies and saves them into a reply set. Si waits until it gets enough replies (n-f-j) from other servers then it picks the most frequently received value. Si also:
The read algorithm is a basic version of join. The difference is the broadcast mechanism used by the read operation. A client (cw) broadcasts a message to the system and once a server receives the inquiry, it sends a reply message to the client. Once the client receives enough replies (n-f-j) it stops sending an inquiry.
Client (cw) sends an inquiry into the system in different rounds and waits until it receives two acknowledgment. (sn =sequence number)
The reason for receiving two acknowledgments is to avoid danger in a system. When a process sends an acknowledgement (ack), it may die after one millisecond. Therefore, no confirmation is received by the client.
The validity of the safe register (If a read is not concurrent with any write, return the last value written) was proved based on the quorum system. [4] Given two quorum systems (Qw, Qr) Qw indicates the servers that know about the latest value, and Qr indicates values of read responses. The size of each quorum is equal to n-f-j. [4] Proving the safe register's validity requires proving
were B is the number of Byzantine failures.
Proof : Red region indicates (Qw∩Qr)\B and the blue region indicates Qr∩B. From the assumption, the size of each quorum is n-f-j, so the red region has n-3f-2j active servers. Therefore,
is strictly greater than f.
Atomic semantics is a type of guarantee provided by a data register shared by several processors in a parallel machine or in a network of computers working together. Atomic semantics are very strong. An atomic register provides strong guarantees even when there is concurrency and failures.
In computing and in systems theory, FIFO is an acronym for first in, first out, a method for organizing the manipulation of a data structure where the oldest (first) entry, or "head" of the queue, is processed first.
Regular semantics is a computing term which describes one type of guarantee provided by a data register shared by several processors in a parallel machine or in a network of computers working together. Regular semantics are defined for a variable with a single writer but multiple readers. These semantics are stronger than safe semantics but weaker than atomic semantics: they guarantee that there is a total order to the write operations which is consistent with real-time and that read operations return either the value of the last write completed before the read begins, or that of one of the writes which are concurrent with the read.
Coda is a distributed file system developed as a research project at Carnegie Mellon University since 1987 under the direction of Mahadev Satyanarayanan. It descended directly from an older version of Andrew File System (AFS-2) and offers many similar features. The InterMezzo file system was inspired by Coda.
In computer science, inter-process communication or interprocess communication (IPC) refers specifically to the mechanisms an operating system provides to allow the processes to manage shared data. Typically, applications can use IPC, categorized as clients and servers, where the client requests data and the server responds to client requests. Many applications are both clients and servers, as commonly seen in distributed computing.
In computer science, a consistency model specifies a contract between the programmer and a system, wherein the system guarantees that if the programmer follows the rules for operations on memory, memory will be consistent and the results of reading, writing, or updating memory will be predictable. Consistency models are used in distributed systems like distributed shared memory systems or distributed data stores. Consistency is different from coherence, which occurs in systems that are cached or cache-less, and is consistency of data with respect to all processors. Coherence deals with maintaining a global order in which writes to a single location or single variable are seen by all processors. Consistency deals with the ordering of operations to multiple locations with respect to all processors.
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In computer science, message passing is a technique for invoking behavior on a computer. The invoking program sends a message to a process and relies on that process and its supporting infrastructure to then select and run some appropriate code. Message passing differs from conventional programming where a process, subroutine, or function is directly invoked by name. Message passing is key to some models of concurrency and object-oriented programming.
Eventual consistency is a consistency model used in distributed computing to achieve high availability that informally guarantees that, if no new updates are made to a given data item, eventually all accesses to that item will return the last updated value. Eventual consistency, also called optimistic replication, is widely deployed in distributed systems and has origins in early mobile computing projects. A system that has achieved eventual consistency is often said to have converged, or achieved replica convergence. Eventual consistency is a weak guarantee – most stronger models, like linearizability, are trivially eventually consistent.
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.NET Remoting is a Microsoft application programming interface (API) for interprocess communication released in 2002 with the 1.0 version of .NET Framework. It is one in a series of Microsoft technologies that began in 1990 with the first version of Object Linking and Embedding (OLE) for 16-bit Windows. Intermediate steps in the development of these technologies were Component Object Model (COM) released in 1993 and updated in 1995 as COM-95, Distributed Component Object Model (DCOM), released in 1997, and COM+ with its Microsoft Transaction Server (MTS), released in 2000. It is now superseded by Windows Communication Foundation (WCF), which is part of the .NET Framework 3.0.
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Synchronous Interprocess Messaging Project for LINUX (SIMPL) is a free and open-source project that allows QNX-style synchronous message passing by adding a Linux library using user space techniques like shared memory and Unix pipes to implement SendMssg/ReceiveMssg/ReplyMssg inter-process messaging mechanisms.
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In distributed computing, a shared snapshot object is a type of data structure, which is shared between several threads or processes. For many tasks, it is important to have a data structure, that can provide a consistent view of the state of the memory. In practice, it turns out that it is not possible to get such a consistent state of the memory by just accessing one shared register after another, since the values stored in individual registers can be changed at any time during this process. To solve this problem, snapshot objects store a vector of n components and provide the following two atomic operations: update(i,v) changes the value in the ith component to v, and scan returns the values stored in all n components. Snapshot objects can be constructed using atomic single-writer multi-reader shared registers.
In distributed computing, shared-memory systems and message-passing systems are two means of interprocess communication which have been heavily studied. In shared-memory systems, processes communicate by accessing shared data structures. A shared (read/write) register, sometimes just called a register, is a fundamental type of shared data structure which stores a value and has two operations: read, which returns the value stored in the register, and write, which updates the value stored. Other types of shared data structures include read–modify–write, test-and-set, compare-and-swap etc. The memory location which is concurrently accessed is sometimes called a register.
