Developing service oriented architectures for increasing software application's reliability

Following September 11 2001, company ABC zeroed in on a home-grown fat client system, System E, as the enterprise data warehouse for risk management. It became mission critical for System E to remove key person dependencies and migrate from C++, a niche technology, to a more accessible platform. Under the leadership of a new hire, System E adopted an Service Oriented Architecture (SOA) approach to re-architecture. As company ABC’s IT unit is under a flat headcount constraint, an incremental SOA approach was the only way to get upper management approval. A pilot is well underway and scheduled to complete in December 2005. This paper presents the current/target architectures of System E, a theoretical framework for SOA, the Unified Modeling Language class diagram for SOA Model at ABC, and concludes with lessons learned from the pilot to date. Key contributions of the paper include SOA Model at ABC, and lessons learned regarding enterprise architecture initiatives.

In this article we address the integration of functional models with non-functional models in the context of service-oriented enterprise architecture. Starting from the observation that current approaches to model-driven development have a strong focus on functionality, we argue the necessity of including non-functional aspects as early as possible in the service design process. We distinguish two modelling spaces, the design space and the analysis space, which can be integrated by means of model transformations. Quantitative results obtained in the analysis space, using special-purpose analysis techniques, can be related back to the design models by means of a reverse transformation. This provides a framework for incorporating non-functional analysis into methodological support for e-service development. While, for detailed design models, performance analysis is more or less covered by existing techniques, there is still a gap at the architectural overview level. Therefore, we propose an approach for performance analysis of layered, service-oriented architecture models, which consists of two phases: a ‘‘top-down’’ propagation of workload parameters, and a “bottom-up’’ propagation of performance or cost measures. By means of an example, we demonstrate the application of the approach and show that a seamless integration with detailed performance analysis methods (e.g., queueing analysis) can be achieved.

Understanding Service-Oriented Architecture (SOA): A systematic literature review and directions for further investigation

Enterprise application integration makes data sharing easier, efficient and provides flexibility for organizations to seize opportunities and respond to stakeholder needs. Faculty of Mathematics and Natural Sciences (FMIPA) Tanjungpura University is an organization that wants to apply information technology effectively to support its business processes. Currently the application at FMIPA is built with different platforms and databases so that it cannot be integrated to share data between parts of the organization. FMIPA intends to build a service-oriented technology architecture to support the realization of organizational goals. SOA (Service Oriented Architecture) can be used as a framework for enterprise application integration. SOA adoption is often not as expected because organizations do not plan their processes comprehensively. It is necessary to measure the maturity level of the organization's SOA adoption so that the current state of the organization's SOA and future expectations can be found. ISO/IEC 16680 (OSIMM) is a method for measuring the SOA maturity level with 7 levels of maturity and 7 dimensions. To expedite the SOA adoption process in FMIPA, SOA maturity level was measured using ISO/IEC 16680. Based on measurements of the seven dimensions of SOA at ISO/IEC 16680, it was found that the current level of SOA adoption maturity (As-Is) at FMIPA Untan was at the level one (Silo), while the expected maturity level (To-Be) is level four (Service). Gap analysis then carried out related to the gap in maturity levels, and is followed by making recommendations dan roadmap for SOA adoption.

A key indicator of today's global business system supported by service oriented architecture (SOA), is the reliability and uptime. This concern is crucial for e-commerce sites and mission-critical business applications. SOA modelling is used to implement the concept of digital business ecosystem (DBE). In computing environment of DBE a chain of components link business applications together, and the strength of this chain, in terms of reliability and performance, will determine the success or failure of the business. One way to make the chain stronger is to increase the reliability of all components involved, especially the critical components of the chain. In this paper, we address the reliability issue of digital ecosystem's transactions. The major contribution of this research is to propose a framework for reliable transactions in DE, via the analysis of the reliability for Web services computing.

A service-oriented architectural (SOA) model is proposed for power system reliability analysis especially for generating capacity adequacy evaluation. Generating system adequacy evaluation is performed to evaluate the ability of the system generating capacity to meet the total system demand. The proposed SOA model is composed of generation system reliability (GSR) service provider, power system service registry and service requester. The data pertaining to power system reliability analysis are represented in extensible markup language (XML) for exchanging the reliability data among the users and service providers. The GSR service provider describes the reliability evaluation services and publishes them to the power system service registry. The calling sequences of reliability evaluation services along with required data are configured as SOAP (Simple Object Access Protocol) messages and the proposed SOA model communicates between the service provider and the service requester with formally defined messages. The proposed model for generating system reliability analysis is highly distributed and has inherent features such as scalability and flexibility and provides a loosely coupled environment for power system reliability analysis.

Current learning approaches are teacher oriented. The teacher is in control of the elements of the entire learning process. But different students have different capabilities and constraints. The student should be able to select the teaching style and method that best meets his requirements, while taking into consideration his capabilities and constraints. Due to the wide popularity of service-oriented architecture (SOA) and cloud computing, we propose an extended SOA model. This model extends traditional SOA models to support the provision of richer services that enable service providers to reach a wide range of customers and enable service requesters to find services that best match their requirements taking into consideration their capabilities. In the context of this paper, service providers are course providers and service requesters are the students. This paper also introduces a novel formal model for the specification of our newly introduced richer services.

The Service Oriented Architecture (SOA) is embraced in distributed and grid computing to produce high performance results for long time. SOA is likened by application programmers for its trademark characteristics of programmability, efficiency in heterogeneous conditions and fault-tolerance. It has worked well for high performance financial applications. but not for scientific applications which are too fine grained and communication intensive to be efficient on distributed environments. This paper argues that to make SOA model work well for those scientific applications, we need to reduce overhead costs associated with smaller task loads arising from finer granularity and increased communications in those applications. This paper proposes a data service to be used along with the existing compute services in SOA middlewares to enable inter-communication of finer tasks with out loosing SOA properties of programmability and efficiency under heterogeneity. This data service shall better enable high performance scientific computing of medium to fine grained scientific applications.

Cloud computing, a more recent computing paradigm, has evolved from a variety of legacy technologies that include Service oriented Architecture (SOA) and Web services besides several others. The software services in a cloud must be developed based on the service-oriented approach, in order to derive their full potential and benefits. Since, SOA inherently nurtures interoperability; it will enhance the integration and interaction among the cloud software services. Also, leveraging the Model Driven Architecture (MDA) approach to develop individual cloud software services will result in services that are more robust, flexible and agile in the wake of ever changing technologies. This paper is an attempt by the authors to lay emphasis on the convergence of Cloud computing, SOA and MDA in development of optimum business solutions.KeywordsCloud computingCloud SaaSService Oriented Architecture (SOA)Model-Driven Architecture (MDA)Computation Independent Model (CIM)Platform Independent Model (PIM)Platform Specific Model (PSM)Interoperability

Integrating MDA and SOA for improving telemedicine services

Business Intelligence and Service Oriented Architecture – Improving IT Investments

Information Technology does not solve business problems. Rather, IT can be used as an enabler to meet goals, targets and position the organization in the minds of the customer. A Service Oriented Architecture (SOA) can enable higher level services from more primitive business processes. The result is a flexible, agile organization. However, in some cases, without a business model, an SOA can be implemented but the result is islands of incompatible services. In the era of data analytics, the evolution of business intelligence has assumed a more dominant role. Proponents argue that Business Intelligence subsumes SOA. Other practitioners argue that Business Intelligence (BI) and SOA are distinct from each other as each aims to deliver different perspectives to an organization. This chapter challenges this view by developing a framework where both SOA and BI are pivotal to delivering the business model. The analytics, business intelligence and data mining handshake with the SOA, allowing decision makers to plan, coordinate and control resources to meet the goals, targets and performance measures set for the organization. Business Intelligence and SOA need not operate on different levels for an organisation. In an era where companies are trying to go from barely surviving IT expenses towards developing an IT portfolio, the more options for technologies supporting asset data management, warehousing and mining to interact and co-exist are necessary. Putting aside arguments of Business Intelligence versus SOA, we propose that they can handshake and bring out the collaborative synergies to enable organizational decision making to address the competitive challenges in today’s global marketplace.KeywordsDecision support and optimization methods and toolsBusiness intelligenceSOA

The use of a service-oriented architecture (SOA) has been identified as a promising approach for improving health care by facilitating reliable clinical decision support (CDS). A review of the literature through October 2013 identified 44 articles on this topic. The review suggests that SOA related technologies such as Business Process Model and Notation (BPMN) and Service Component Architecture (SCA) have not been generally adopted to impact health IT systems' performance for better care solutions. Additionally, technologies such as Enterprise Service Bus (ESB) and architectural approaches like Service Choreography have not been generally exploited among researchers and developers. Based on the experience of other industries and our observation of the evolution of SOA, we found that the greater use of these approaches have the potential to significantly impact SOA implementations for CDS.

Nowadays, a Service Oriented Architecture (SOA) seems to be one of the most promising paradigms for leveraging enterprise information systems. SOA creates opportunities for enterprises to provide value added service tailored for on demand enterprise collaboration. With the emergence and rapid development of Web services technologies, SOA is being paid increasing attention and has become widespread. In spite of the popularity of SOA, a standardized framework for modeling and implementing business services are still in progress. For the purpose of supporting these service-oriented solutions, we adopt a model driven development approach. This paper outlines the Contextual Service Oriented Modeling and Analysis (CSOMA) methodology and presents UML profiles for the PIM level service-oriented architectural modeling, as well as its corresponding meta-models. The proposed PIM (Platform Independent Model) describes the business SOA at a high level of abstraction regardless of techniques involved in the application employment. In addition, all essential service-specific concerns required for delivering quality and context-aware service are covered. Some of the advantages of this approach are that it is generic and thus not closely allied with Web service technology as well as specifically treating the service adaptability during the design stage.

Emerging business models such as digital ecosystems involving collaborative innovation, participatory decision-making and flexible organizational structures are set to significantly affect inter- and intra-enterprise structure and functionality. This has seen the appearance of increasingly complex Service-oriented Architecture (SOA) scenarios featuring various partnership levels, increased resilience and adaptation to tougher compliance regulations, more seamless integration with process layers, etc. This complexity has brought about the need to broaden the SOA paradigm, so as to include business, infrastructure and multi-layering, resulting in an evolved concept known as Service-Oriented Enterprise Architecture (SOEA). This paper aims to describe the way new business and technology paradigms continue to affect the new SOEA approach and how the inherently holistic Enterprise Architecture (EA) frameworks and related practices can support the emerging complex dynamic, multi-layered and value-chained service-based scenario.