Traditional approaches to software development - the ones embodied in CASE tools and modeling frameworks - are appropriate for building individual software components, but they are not designed to face the challenges of open environments. Service-oriented computing provides a way to create a new architecture that reflects components' trends toward autonomy and heterogeneity. We thus emphasize SOC concepts instead of how to deploy Web services in accord with current standards. To begin the series, we describe the key concepts and abstractions of SOC and the elements of a corresponding engineering methodology.

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Service-oriented computing

The current growth of the service sector in global economies is unparalleled in human history—by scale and speed of labor migration. Even large manufacturing firms are seeing dramatic shifts in percent revenue derived from services. The need for service innovations to fuel further economic growth and to raise the quality and productivity levels of services has never been greater. Services are moving to center stage in the global arena, especially knowledge-intensive business services aimed at business performance transformation. One challenge to systematic service innovation is the interdisciplinary nature of service, integrating technology, business, social, and client (demand) innovations. This paper describes the emergence of service science, a new interdisciplinary area of study that aims to address the challenge of becoming more systematic about innovating in service.

The Emergence of Service Science: Toward Systematic Service Innovations to Accelerate Co‐Creation of Value

The distributed transaction commit problem requires reaching agreement on whether a transaction is committed or aborted. The classic Two-Phase Commit protocol blocks if the coordinator fails. Fault-tolerant consensus algorithms also reach agreement, but do not block whenever any majority of the processes are working. The Paxos Commit algorithm runs a Paxos consensus algorithm on the commit/abort decision of each participant to obtain a transaction commit protocol that uses 2F p 1 coordinators and makes progress if at least F p 1 of them are working properly. Paxos Commit has the same stable-storage write delay, and can be implemented to have the same message delay in the fault-free case as Two-Phase Commit, but it uses more messages. The classic Two-Phase Commit algorithm is obtained as the special F = 0 case of the Paxos Commit algorithm.

/pdf/consensus-on-transaction-commit-zf3n4tiinu.pdf

Consensus on transaction commit

Many industrial enterprises acquire disparate systems and applications over the years. The need to integrate these different systems and applications is often prominent for satisfying business requirements and needs. In an effort to help researchers in industrial informatics understand the state-of-the-art of the enterprise application integration, we examined the architectures and technologies for integrating distributed enterprise applications, illustrated their strengths and weaknesses, and identified research trends and opportunities in this increasingly important area.

http://romisatriawahono.net/lecture/rm/survey/information%20systems/He%20-%20Distributed%20Enterprise%20Applications%20-%202013.pdf

Integration of Distributed Enterprise Applications: A Survey

https://www.mit.edu/~caoj/pub/doc/jcao_j_gridagent.pdf

Grid load balancing using intelligent agents

Web services are a new breed of Web applications. These independent application components are published on to the Web in such a way that other Web applications can find and use them. They take the Web to its next stage of evolution, in which software components can discover other software components and conduct business transactions. Examples of Web services include a credit card service that processes credit card transactions for a given account number, a market data service that provides stock market data associated with a specified stock symbol, and an airline service that provides flight schedule, availability, and reservation functionalities. Major vendors like IBM, Microsoft, Hewlett-Packard, and Sun, among others, are investing heavily in Web services technology. Ranging from simple to complex, Web services bring the promise of flexible, open-standards-based, distributed computing to the Internet.

Understanding Web services

Machine learning-based computational health care systems using medical images have undergone rapid advancement in clinical disease diagnosis support. It is very crucial to identify the most common form of dementia, which is Alzheimer's Disease (AD), that progress from a pre-clinical stage called Mild Cognitive Impairment (MCI). This work focuses on the classifications of different progression stages of cognitive impairment to Alzheimer's Disease (AD), using 2D T1 weighted axial MRI images. The images obtained from the ADNI database correspond to various stages of cognitive impairment like Cognitive Normal (CN), Mild Cognitive Impairment (MCI), Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and Alzheimer's Disease (AD) with 3000 samples of each class. As the focus of the work is to identify the different development stages of cognitive impairment which progress to AD, it proposes a CNN-based two-class classification network for AD/MCI, AD/CN, and MCI/CN and a five-stage CNN classifier for classifying AD vs CN vs EMCI vs LMCI vs MCI stages, the result thus obtained is compared with transfer learning-based model, the Xception architecture, by performing the binary and five class classification tasks with the same dataset. The proposed CNN-based model gives an accuracy of 93.28% for AD/MCI, 91.92% for AD/CN, and 91.90% for MCI/CN, the overall accuracy of the five class classification using the CNN-based model is 93%. The Transfer learning-based work produced an accuracy of 91.33% for AD/MCI, 88.83% for AD/CN, and 86.9% for MCI/CN, 93.89% for five class classifications. The work also evaluates the class-wise performance of the five class classification tasks with both models to analyze the effectiveness of each class in the classification of cognitive impairment progression stages. The results show that both models classify all five progression stages with good accuracy and high specificity, which assures lesser false positive classification.

A. Ramanujan

Papers

Understanding Web services

Deep Learning Enabled Classification of Cognitive Impairment Stages Using MRI Images