Combining Cloud Computing and Service-Oriented Architecture. A cloud has some key characteristics: elasticity, self-service provisioning, standards based interfaces, and pay as you go. This type of functionality has to be engineered into the software. To accomplish this type of engineering requires that the foundation for the cloud be well designed and well architected.
What about cloud architecture makes this approach possible? The fact is that the services and structure behind the cloud should be based on a modular architectural approach. A modular, component-based architecture enables flexibility and reuse. A Service-Oriented Architecture (SOA) is what lies beneath this flexibility. SOA is much more than a technological approach and methodology for creating IT systems. Cloud services benefit the business by taking the best practices and business process focus of SOA to the next level. Category:Distributed computing architecture. Architectural, organisational, and engineering aspects of distributed computing. Computer architectures, software architectures, software frameworks, and network architectures related to distributed computing and distributed systems. Different “styles” of distributed computing. See also[edit] Communication protocols and standards related to distributed computing: Programming languages and tools related to distributed computing: Subcategories This category has the following 17 subcategories, out of 17 total.
Pages in category "Distributed computing architecture" The following 92 pages are in this category, out of 92 total. Understanding Service-Oriented Architecture. David Sprott and Lawrence Wilkes CBDI Forum January 2004 Summary: Gives a concise explanation of service-oriented architecture, what it is, and how it affects what architects, CIOs, project managers, business analysts, and lead developers do. (13 printed pages) Contents IntroductionPrinciples and DefinitionsSOA BasicsProcess MattersArchitecturesThe Service ArchitectureThe SOA PlatformThe Enterprise SOASummary Introduction It seems probable that eventually most software capabilities will be delivered and consumed as services. Over time, the level of abstraction at which functionality is specified, published and or consumed has gradually become higher and higher. Like objects and components, services represent natural building blocks that allow us to organize capabilities in ways that are familiar to us.
For many organizations, the logical starting place for investigating service-oriented architecture is the consideration of Web services. Principles and Definitions Service A Service Definition. A Quick Look at Architectural Styles and Patterns. Chapter 3: Architectural Patterns and Styles. For more details of the topics covered in this guide, see Contents of the Guide. This chapter describes and discusses high level patterns and principles commonly used for applications today. These are often referred to as the architectural styles, and include patterns such as client/server, layered architecture, component-based architecture, message bus architecture, and service-oriented architecture (SOA). For each style, you will find an overview, key principles, major benefits, and information that will help you choose the appropriate architectural styles for your application.
It is important to understand that the styles describe different aspects of applications. For example, some architectural styles describe deployment patterns, some describe structure and design issues, and others describe communication factors. “ߪa; family of systems in terms of a pattern of structural organization. An understanding of architectural styles provides several benefits. Higher security. List of software architecture styles and patterns. List of software architecture styles and patterns From Wikipedia, the free encyclopedia Jump to: navigation, search Contents [hide] Catalog of architectural patterns[edit] Catalog of architectural styles[edit] Structure[edit] Shared memory[edit] Messaging[edit] Adaptable systems[edit] Distributed systems[edit] References[edit] Retrieved from " Categories: Navigation menu Personal tools Namespaces Variants Views More Navigation Interaction Tools Print/export Languages Edit links This page was last modified on 20 January 2015, at 08:14.
Tuple space. A tuple space is an implementation of the associative memory paradigm for parallel/distributed computing. It provides a repository of tuples that can be accessed concurrently. As an illustrative example, consider that there are a group of processors that produce pieces of data and a group of processors that use the data. Producers post their data as tuples in the space, and the consumers then retrieve data from the space that match a certain pattern. This is also known as the blackboard metaphor. Tuple space may be thought as a form of distributed shared memory. Object Spaces[edit] Object Spaces is a paradigm for development of distributed computing applications. Object Space can be thought of as a virtual repository, shared amongst providers and accessors of network services, which are themselves abstracted as objects. An object, when deposited into a space, needs to be registered with an Object Directory in the Object Space.
This paradigm inherently provides mutual exclusion. Event-driven architecture. Building applications and systems around an event-driven architecture allows these applications and systems to be constructed in a manner that facilitates more responsiveness, because event-driven systems are, by design, more normalized to unpredictable and asynchronous environments.[2] Event-driven architecture can complement service-oriented architecture (SOA) because services can be activated by triggers fired on incoming events.[2][3] This paradigm is particularly useful whenever the sink does not provide any self-contained executive[clarify]. SOA 2.0 evolves the implications SOA and EDA architectures provide to a richer, more robust level by leveraging previously unknown causal relationships to form a new event pattern.
[vague] This new business intelligence pattern triggers further autonomous human or automated processing that adds exponential value to the enterprise by injecting value-added information into the recognized pattern which could not have been achieved previously. Service-oriented architecture. See also the client-server model, a progenitor concept A Service-Oriented Architecture (SOA) is a design pattern in which software/application components provide services to other software/application components via a protocol, typically over a network and in a loosely-coupled way. The principles of service-orientation are independent of any vendor, product or technology.[1] A service is a self-contained unit of functionality, such as retrieving an online bank statement.[2] By that definition, a service is a discretely invokable operation.
However, in the Web Services Definition Language (WSDL), a service is an interface definition that may list several discrete services/operations. And elsewhere, the term service is used for a component that is encapsulated behind an interface. This widespread ambiguity is reflected in what follows. Definitions[edit] A paradigm for organizing and utilizing distributed capabilities that may be under the control of different ownership domains.
Representational state transfer. Representational State Transfer (REST) is a software architecture style consisting of guidelines and best practices for creating scalable web services.[1][2] REST is a coordinated set of constraints applied to the design of components in a distributed hypermedia system that can lead to a more performant and maintainable architecture.[3] REST has gained widespread acceptance across the Web[citation needed] as a simpler alternative to SOAP and WSDL-based Web services. RESTful systems typically, but not always, communicate over the Hypertext Transfer Protocol with the same HTTP verbs (GET, POST, PUT, DELETE, etc.) used by web browsers to retrieve web pages and send data to remote servers.[3] The REST architectural style was developed by W3C Technical Architecture Group (TAG) in parallel with HTTP 1.1, based on the existing design of HTTP 1.0.[4] The World Wide Web represents the largest implementation of a system conforming to the REST architectural style.
Architectural properties[edit] Space-based architecture. The SBA model is closely related to other patterns that have been proved successful in addressing the application scalability challenge, such as shared nothing architecture (SN), used by Google, Amazon.com and other well-known companies. The model has also been applied by many firms in the securities industry for implementing scalable electronic securities trading applications. Components of Space-Based Architecture[edit] An application built on the principles of space-based architecture typically has the following components: Processing Unit — the unit of scalability and fail-over.
Normally, a processing unit is built out of a POJO (Plain Old Java Object) container, such as that provided by the Spring Framework.Virtual Middleware — a common runtime and clustering model, used across the entire middleware stack. See also[edit] Literature[edit] Articles/papers, technical: References[edit] Peer-to-peer. A peer-to-peer (P2P) network in which interconnected nodes ("peers") share resources amongst each other without the use of a centralized administrative system Peer-to-peer (P2P) computing or networking is a distributed application architecture that partitions tasks or work loads between peers. Peers are equally privileged, equipotent participants in the application. They are said to form a peer-to-peer network of nodes. Peers make a portion of their resources, such as processing power, disk storage or network bandwidth, directly available to other network participants, without the need for central coordination by servers or stable hosts.[1] Peers are both suppliers and consumers of resources, in contrast to the traditional client-server model in which the consumption and supply of resources is divided.
Historical development[edit] Therefore, a distributed messaging system that is often likened as an early peer-to-peer architecture was established: USENET. Applications[edit] Multitier architecture. In software engineering, multi-tier architecture (often referred to as n-tier architecture) is a client–server architecture in which presentation, application processing, and data management functions are physically separated. The most widespread use of multi-tier architecture is the three-tier architecture. N-tier application architecture provides a model by which developers can create flexible and reusable applications. By segregating an application into tiers, developers acquire the option of modifying or adding a specific layer, instead of reworking the entire application.
A three-tier architecture is typically composed of a presentation tier, a domain logic tier, and a data storage tier. While the concepts of layer and tier are often used interchangeably, one fairly common point of view is that there is indeed a difference. Three-tier architecture[edit] Visual overview of a Three-tiered application The three-tier model is a software architecture pattern. Three-tier architecture: Client–server model. Examples of computer applications that use the client–server model are Email, network printing, and the World Wide Web. Client and server roles[edit] The client–server characteristic describes the relationship of cooperating programs in an application.
The server component provides a function or service to one or many clients, which initiate requests for such services. Whether a computer is a client, a server, or both, is determined by the nature of the application that requires the service functions. For example, a single computer can run web server and file server software at the same time to serve different data to clients making different kinds of requests. Client and server communication[edit] Clients and servers exchange messages in a request-response messaging pattern: The client sends a request, and the server returns a response.
Example[edit] In each step of this sequence of client–server message exchanges, a computer processes a request and returns data. Early history[edit] Distributed computing. "Distributed Information Processing" redirects here. For the computer company, see DIP Research. Distributed computing is a field of computer science that studies distributed systems. A distributed system is a software system in which components located on networked computers communicate and coordinate their actions by passing messages.[1] The components interact with each other in order to achieve a common goal. Three significant characteristics of distributed systems are: concurrency of components, lack of a global clock, and independent failure of components.[1] Examples of distributed systems vary from SOA-based systems to massively multiplayer online games to peer-to-peer applications.
A computer program that runs in a distributed system is called a distributed program, and distributed programming is the process of writing such programs.[2] There are many alternatives for the message passing mechanism, including RPC-like connectors and message queues. Introduction[edit] History[edit] Distributed systems.