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64-606: DSOM , a distributed variant based on CORBA , allowed objects on different computers to communicate. A SOM library can be updated without requiring client code to be rebuilt. If a library is changed to add new classes or methods, or to change the internal implementation of classes or methods, a consuming program can still use it without being rebuilt. In this way, SOM addresses the fragile binary interface problem that affects other library technology such as C++ . SOM allows classes to be defined in one programming language and used in another. A client can create and use objects from

128-443: A solution for each instance. Instances are questions that we can ask, and solutions are desired answers to these questions. Theoretical computer science seeks to understand which computational problems can be solved by using a computer ( computability theory ) and how efficiently ( computational complexity theory ). Traditionally, it is said that a problem can be solved by using a computer if we can design an algorithm that produces

192-400: A .NET World SOM is often compared to component object model (COM). Both support a library format that can be used from more than one language. Some consider SOM to be more robust since it only supports a language-neutral calling mechanism that is similar to COM late binding . COM also supports early binding , a.k.a. custom interface, that is less safe although more performant. It allows

256-470: A client to access an object via a function table that is compatible with C and therefore compatible with the binary layout of the virtual table of C++ objects (at least in Microsoft's C++ compiler). With a compatible C++ compiler, a custom interface can be defined as a pure virtual C++ class. The interface can be called by any language that can call C functions via a pointer. A risk of a custom interface

320-474: A common goal for their work. The terms " concurrent computing ", " parallel computing ", and "distributed computing" have much overlap, and no clear distinction exists between them. The same system may be characterized both as "parallel" and "distributed"; the processors in a typical distributed system run concurrently in parallel. Parallel computing may be seen as a particularly tightly coupled form of distributed computing, and distributed computing may be seen as

384-520: A correct solution for any given instance. Such an algorithm can be implemented as a computer program that runs on a general-purpose computer: the program reads a problem instance from input , performs some computation, and produces the solution as output . Formalisms such as random-access machines or universal Turing machines can be used as abstract models of a sequential general-purpose computer executing such an algorithm. The field of concurrent and distributed computing studies similar questions in

448-624: A deadlock. This problem is PSPACE-complete , 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. XPCOM Cross Platform Component Object Model ( XPCOM ) is a cross-platform component model from Mozilla . It is similar to Component Object Model (COM), Common Object Request Broker Architecture (CORBA) and system object model (SOM). It features multiple language bindings and interface description language (IDL) descriptions; thus programmers can plug their custom functions into

512-504: 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 . 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. In the analysis of distributed algorithms, more attention is usually paid on communication operations than computational steps. Perhaps

576-827: A distributed system communicate and coordinate their actions by passing messages to one another in order to achieve a common goal. Three significant challenges of distributed systems are: maintaining concurrency of components, overcoming the 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 SOA-based systems to microservices to massively multiplayer online games to peer-to-peer applications . Distributed systems cost significantly more than monolithic architectures, primarily due to increased needs for additional hardware, servers, gateways, firewalls, new subnets, proxies, and so on. Also, distributed systems are prone to fallacies of distributed computing . On

640-446: A fundamental concept of OO programming; the main reason is that it is difficult to know where a base class exists in memory where libraries are loaded in a order unknown at design time. COM demands that the programmer specify the exact base class at compile time, making it impossible to insert other derived classes in the middle; at least in other COM libraries. SOM instead uses an algorithm, looking for potential base classes by following

704-401: A loosely coupled form of parallel computing. Nevertheless, it is possible to roughly classify concurrent systems as "parallel" or "distributed" using the following criteria: The figure on the right illustrates the difference between distributed and parallel systems. Figure (a) is a schematic view of a typical distributed system; the system is represented as a network topology in which each node

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768-431: A much wider sense, even referring to autonomous processes that run on the same physical computer and interact with each other by message passing. While there is no single definition of a distributed system, the following defining properties are commonly used as: A distributed system may have a common goal, such as solving a large computational problem; the user then perceives the collection of autonomous processors as

832-424: A problem is divided into many tasks, each of which is solved by one or more computers, which communicate with each other via message passing. The word distributed in terms such as "distributed system", "distributed programming", and " distributed algorithm " originally referred to computer networks where individual computers were physically distributed within some geographical area. The terms are nowadays used in

896-654: A schematic architecture allowing for live environment relay. This enables distributed computing functions both within and beyond the parameters of a networked database. Reasons for using distributed systems and distributed computing may include: Examples of distributed systems and applications of distributed computing include the following: According to Reactive Manifesto, reactive distributed systems are responsive, resilient, elastic and message-driven. Subsequently, Reactive systems are more flexible, loosely-coupled and scalable. To make your systems reactive, you are advised to implement Reactive Principles. Reactive Principles are

960-405: A sequential general-purpose computer? 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: In the case of distributed algorithms, computational problems are typically related to graphs. Often the graph that describes the structure of the computer network

1024-457: A set of principles and patterns which help to make your cloud native application as well as edge native applications more reactive. Many tasks that we would like to automate by using a computer are of question–answer type: we would like to ask a question and the computer should produce an answer. In theoretical computer science , such tasks are called computational problems . Formally, a computational problem consists of instances together with

1088-431: A strong versioning system, allowing library authors to ship new versions along with the old, thereby guaranteeing backward compatibility at the cost of disk space. Distributed computing Distributed computing is a field of computer science that studies distributed systems , defined as computer systems whose inter-communicating components are located on different networked computers . The components of

1152-695: A token ring network in which the token has been lost. Coordinator election algorithms are designed to be economical in terms of total bytes transmitted, and time. The algorithm suggested by Gallager, Humblet, and Spira 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

1216-434: A unit. Alternatively, each computer may have its own user with individual needs, and the purpose of the distributed system is to coordinate the use of shared resources or provide communication services to the users. Other typical properties of distributed systems include the following: Here are common architectural patterns used for distributed computing: Distributed systems are groups of networked computers which share

1280-477: Is the problem instance. This is illustrated in the following example. Consider the computational problem of finding a coloring of a given graph G . Different fields might take the following approaches: 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

1344-545: Is Netlabs Object Model (NOM), which is technically the same, but binary incompatible. Another is somFree, which is a clean room design of IBM SOM, and binary compatible. SOM can be compared compiled libraries: As of 2015, most of the information in the linked table is applicable to modern versions, except Objective-C 2.0 getting so called non-fragile instance variables. Some solutions remained experimental: SGI Delta/C++ or Sun OBI. Most approaches based on one programming language were phased out or were never used actively in

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1408-416: Is a computer and each line connecting the nodes is a communication link. Figure (b) shows the same distributed system in more detail: each computer has its own local memory, and information can be exchanged only by passing messages from one node to another by using the available communication links. Figure (c) shows a parallel system in which each processor has a direct access to a shared memory. The situation

1472-403: Is also focused on understanding the asynchronous nature of distributed systems: Note that in distributed systems, latency should be measured through "99th percentile" because "median" and "average" can be misleading. 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

1536-482: Is also not known much in this role and not known to be marketed this way, but its runtime is one of the most friendly to similar use cases. Generic C++ is still being used in Qt and the K Desktop Environment ( KDE ). Qt and KDE are notable for describing efforts it takes to maintain binary compatibility without special support in development tools. GObject only aimed to avoid dependence on C++ compiler, but RRBC issues are

1600-419: 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. Typically an algorithm which solves a problem in polylogarithmic time in the network size is considered efficient in this model. Another commonly used measure

1664-581: Is further complicated by the traditional uses of the terms parallel and distributed algorithm that do not quite match the above definitions of parallel and distributed systems (see below for more detailed discussion). Nevertheless, as a rule of thumb, high-performance parallel computation in a shared-memory multiprocessor uses parallel algorithms while the coordination of a large-scale distributed system uses distributed algorithms. The use of concurrent processes which communicate through message-passing has its roots in operating system architectures studied in

1728-478: Is necessary to interconnect processes running on those CPUs with some sort of communication system . Whether these CPUs share resources or not determines a first distinction between three types of architecture: Distributed programming typically falls into one of several basic architectures: client–server , three-tier , n -tier , or peer-to-peer ; or categories: loose coupling , or tight coupling . Another basic aspect of distributed computing architecture

1792-532: Is one of the main things making the Mozilla application environment an actual framework. It is a development environment that provides the following features for the cross-platform software developer: This component object model makes virtually all of the functionality of Gecko available as a series of components, or reusable cross-platform libraries , that can be accessed from the web browser or scripted from any Mozilla application. Applications that must access

1856-658: Is supported. The flexibility to reuse the XPCOM components from the Gecko library and develop new components that run on different platforms facilitates rapid application development and results in an application that is more productive and easier to maintain. The networking library, for example, is a set of XPCOM components that can be accessed and used by any Mozilla application. File I/O, security, password management, and profiles are also separate XPCOM components that programmers can use in their own application development. XPCOM adds

1920-504: Is that an incompatibility can result in undefined behavior . In particular, if a version of the object is published with a modified custom interface, a client may crash. This is an example of the fragile base class problem. To prevent the problem, a rule for COM development is that once published, a custom interface cannot be changed. To add or change the exposed features of an object, it can implement additional custom interfaces. SOM avoid this issue by providing only late binding – allowing

1984-492: Is the method of communicating and coordinating work among concurrent processes. Through various message passing protocols, processes may communicate directly with one another, typically in a main/sub relationship. Alternatively, a "database-centric" architecture can enable distributed computing to be done without any form of direct inter-process communication , by utilizing a shared database . Database-centric architecture in particular provides relational processing analytics in

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2048-492: Is the most promising competitor to SOM (although not being actively marketed as multi-language platform), and SOM should preferably be compared to Objective-C as opposed to COM as it happened historically. With non-fragile instance variables in Objective-C 2.0 it is the best alternative amongst actively supported. COM , XPCOM are being used actively, but they only manage interfaces, not implementations, and thus are not on

2112-410: Is the number of synchronous communication rounds required to complete the task. 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

2176-511: Is the total number of bits transmitted in the network (cf. communication complexity ). 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. Traditional computational problems take the perspective that the user asks a question, a computer (or a distributed system) processes

2240-399: 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. The definition of this problem is often attributed to LeLann, who formalized it as a method to create a new token in

2304-518: The 1960s. The first widespread distributed systems were local-area networks such as Ethernet , which was invented in the 1970s. ARPANET , one of the predecessors of the Internet , was introduced in the late 1960s, and ARPANET e-mail was invented in the early 1970s. E-mail became the most successful application of ARPANET, and it is probably the earliest example of a large-scale distributed application . In addition to ARPANET (and its successor,

2368-419: The case of either multiple computers, or a computer that executes a network of interacting processes: which computational problems can be solved in such a network and how efficiently? However, it is not at all obvious what is meant by "solving a problem" in the case of a concurrent or distributed system: for example, what is the task of the algorithm designer, and what is the concurrent or distributed equivalent of

2432-400: The cost of supporting fewer languages. Multi-language support was important to IBM as they wanted to support both Smalltalk ( single inheritance and dynamic dispatch ) with C++ ( multiple inheritance and fixed dispatch). A notable difference is support for inheritance. COM does not. Although may think it odd that Microsoft produced an object library technology that could not support such

2496-459: The desktop to use a mainframe for processing and data storage. IBM produced versions of SOM/DSOM for OS/2, Microsoft Windows and various Unix flavors (notably IBM's own AIX ). For some time after the formation of the AIM alliance , SOM/DSOM was also used by Apple Computer for similar purposes. It was most widely used in their OpenDoc framework, but saw limited use in other roles as well. Perhaps

2560-528: The exposed classes and derive subclasses from the exposed classes even if the client language does not support class typing. SOM provides an application programming interface (API) that provides access to library metadata . Each object exposes methods that provide the class name and whether the object implements a particular method, for example. SOM was intended to be used universally in IBM's mainframe and desktop ( OS/2 ) computers, allowing programs designed for

2624-401: 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. 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

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2688-502: The framework and connect it with other components. The most prominent usage of XPCOM is within the Firefox web browser. Many of its internal components interact via XPCOM interfaces. Furthermore, Firefox used to allow add-ons extensive XPCOM access, but this was removed in 2017 and replaced with the less-permissive WebExtensions API . (Two forks of Firefox still support XPCOM add-on capability: Pale Moon and Basilisk . ) XPCOM

2752-452: The general case, and naturally understanding the behaviour of a computer network is at least as hard as understanding the behaviour of one computer. 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

2816-483: The global Internet), other early worldwide computer networks included Usenet and FidoNet from the 1980s, both of which were used to support distributed discussion systems. The study of distributed computing became its own branch of computer science in the late 1970s and early 1980s. The first conference in the field, Symposium on Principles of Distributed Computing (PODC), dates back to 1982, and its counterpart International Symposium on Distributed Computing (DISC)

2880-489: The infra cost must be considered. A computer program that runs within a distributed system is called a distributed program , and distributed programming is the process of writing such programs. There are many different types of implementations for the message passing mechanism, including pure HTTP, RPC-like connectors and message queues . Distributed computing also refers to the use of distributed systems to solve computational problems. In distributed computing ,

2944-478: The inheritance tree and stopping at the first one that matches. This is the idea behind inheritance in most cases. The downside to this approach is that it is possible that new versions of this base class may no longer work even if the API remains the same. This possibility exists in any program, not only those using a shared library, but a problem can become difficult to resolve if it exists in someone else's code. In SOM,

3008-456: The issue of the graph family from the design of the coordinator election algorithm was suggested by Korach, Kutten, and Moran. 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. So far

3072-510: The most widespread uses of SOM within IBM were in later versions of OS/2, which used it for most code, including the Workplace Shell . Object REXX for OS/2 is able to deal with SOM classes and objects including WPS. SOMobjects were not completely shut down by IBM. They were ported to OS/390, and are still available on this OS. One can read documentation on IBM website. In 1996 Tandem Computers Inc. obtained SOMobjects technology. Tandem

3136-691: The only solution is testing of new versions of libraries. While SOM and COM were contrapositioned by IBM, they were not mutually exclusive. In 1995 Novell contributed ComponentGlue technology to OpenDoc for Windows. This technology provided different means to integrate between COM and SOM components. In particular, SOM objects can be made available to OLE2 applications by either late binding bridge (based on IDispatch) or COM interfaces having higher performance. In essence, SOM classes are implementing COM interfaces this way. Similar technologies, such as Distributed Objects Everywhere , also support full inheritance. Portable Distributed Objects avoided these issues via

3200-401: The other hand, a well designed distributed system is more scalable, more durable, more changeable and more fine-tuned than a monolithic application deployed on a single machine. According to Marc Brooker: "a system is scalable in the range where marginal cost of additional workload is nearly constant." Serverless technologies fit this definition but the total cost of ownership, and not just

3264-408: 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

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3328-629: 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 , Byzantine fault tolerance , and self-stabilisation . Much research

3392-511: The run-time linker to re-build the table on the fly. This way, changes to the underlying libraries are resolved when they are loaded into programs. SOM is more robust in terms of supporting object-oriented (OO) features. Whereas COM essentially defines a cut-down version of C++ to program to, SOM supports almost all common features. It also supports some less common features such as multiple inheritance , metaclasses and dynamic dispatching , which had led most SOM/COM-like systems to be simpler at

3456-479: The same as in generic C++. Without special runtime many other programming languages will have the same issues, e.g., Delphi , Ada . It can be illustrated by so-called unprecedented approach it took to produce Delphi 2006 binary compatible Delphi 2007 release: How to add a "published" property without breaking DCU compatibility Archived 2015-12-08 at the Wayback Machine Objective-C

3520-418: The same level as SOM, GObject and Objective-C . Windows Runtime under closer look behaves much like COM. Its metadata description is based on .NET, but since WinRT does not contain special runtime to resolve RRBC issues, like in Objective-C or SOM, several restrictions had to be applied that limit WinRT on procedural level: Type System (C++/CX) Windows Runtime Components - Windows Runtime Components in

3584-403: The same place as the boundary between parallel and distributed systems (shared memory vs. message passing). 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

3648-582: The same way. For instance, Netscape Plugin Application Programming Interface ( NPAPI ) browser plugins were written using Java API initially (LiveConnect), but Java Virtual Machine (JVM) was later excluded from the chain. It can be seen as Java replaced with Cross Platform Component Object Model ( XPCOM ). Common Lisp Object System (CLOS) and Smalltalk are not known as being chain links like Java in LiveConnect. Objective-C

3712-423: 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

3776-432: 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. The network nodes communicate among themselves in order to decide which of them will get into

3840-900: The various Mozilla XPCOM libraries ( networking , security , DOM , etc.) use a special layer of XPCOM called XPConnect , which reflects the library interfaces into JavaScript , or other languages. XPConnect glues the front end to the C++ , C , or Rust programming language based components in XPCOM, and it can be extended to include scripting support for other languages: PyXPCOM already offers support for Python . wxWidgets provide support for Perl , and there are efforts underway to add Common Language Infrastructure (CLI) and Ruby language support for XPConnect. For developers, XPCOM allows writing components in C++ , C , JavaScript , Python , or other languages for which special bindings have been created, and compile and run those components on dozens of different platforms, including these and others where Mozilla

3904-540: Was first held in Ottawa in 1985 as the International Workshop on Distributed Algorithms on Graphs. Various hardware and software architectures are used for distributed computing. At a lower level, it is necessary to interconnect multiple CPUs with some sort of network, regardless of whether that network is printed onto a circuit board or made up of loosely coupled devices and cables. At a higher level, it

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3968-423: 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). The traditional boundary between parallel and distributed algorithms (choose a suitable network vs. run in any given network) does not lie in

4032-827: Was replaced with Objective-C already being in use in OPENSTEP (to become Mac OS X later). SOM/DSOM development faded, and is no longer actively developed, although it continues to be included and used in OS/2-based systems such as ArcaOS . Despite effective death of OS/2 and OpenDoc, SOM could have yet another niche: Windows and cross-platform development. SOM 3.0 for WinNT was generally available in December 1996. The reasons for not advancing in these directions go beyond market adoption problems. They involve opportunities missed by IBM , and destructive incompatible changes: Two projects of open-source SOM implementations exist. One

4096-575: Was sold to Compaq, Compaq was sold to Hewlett-Packard. NonStop DOM and some other technologies eventually merged into NonStop CORBA, but current documentation of NonStop products does not contain signs of SOM technology still powering NonStop products. With the "death" of OS/2 in the mid-1990s, the raison d'être for SOM/DSOM largely disappeared; if users would not be running OS/2 on the desktop, there would be no universal object library anyway. In 1997, when Steve Jobs returned to Apple and ended many development efforts including Copland and OpenDoc , SOM

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