Peer-to-peer

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]

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]

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. 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: Presentation tier This is the topmost level of the application. Application tier (business logic, logic tier, or middle tier)

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. Services can be combined to provide the complete functionality of a large software application.[3] A SOA makes it easier for software components on computers connected over a network to cooperate. Definitions[edit] A paradigm for organizing and utilizing distributed capabilities that may be under the control of different ownership domains. The Open Group's definition is: Overview[edit] SOA framework[edit] Design concept[edit] Principles[edit]

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. Computing machinery and sensing devices (like sensors, actuators, controllers) can detect state changes of objects or conditions and create events which can then be processed by a service or system. Event structure[edit] Event flow layers[edit] Event generator[edit]

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]

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.

Distributed systems 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 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. Distributed computing also refers to the use of distributed systems to solve computational problems. Introduction[edit] A distributed system may have a common goal, such as solving a large computational problem.[9] 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.[10] Other typical properties of distributed systems include the following: (a)–(b) A distributed system. Architecture[edit]

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.

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. “&#2026a; family of systems in terms of a pattern of structural organization. An understanding of architectural styles provides several benefits. Higher security.

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