Integration of Micro-Services in The Industrial Internet Era
The need for integration arises when companies start considering “boundary-less” information flows across a plateau of multiple enterprise information systems. Adding a new application to the system or replacing one of the existing applications requires the establishment of interfaces with a specific software tool for each of them. The classical way to solve this problem in a large-scale organization is to use a central integration platform based on service-oriented architecture (Service-Oriented Architecture (SOA)). In this work, we forecast the increase of granularity of services and application of micro-services to enhance traditional SOA in the prototypes of industrial internet and Web 3.0.
The author regards the main principles of an overall method of assessing the investment attractiveness of IT-projects and underlines the diffusion of service-oriented architecture (SOA) at the moment. Among modern works taking SOA into consideration in the framework of the methodology of assessing information systems (IS) economic efficiency, he detaches the approach based on event-driven process chain (EPC) extension.
This book constitutes the proceedings of the 9th International Workshop on Enterprise and Organizational Modeling and Simulation, EOMAS 2013, held in conjunction with CAiSE 2013 in Valencia, Spain, in June 2013.
Tools and methods for modeling and simulation are widely used in enterprise engineering, organizational studies, and business process management. In monitoring and evaluating business processes and the interactions of actors in a realistic environment, modeling and simulation have proven to be both powerful, efficient, and economic, especially if complemented by animation and gaming elements.
The ten contributions in this volume were carefully reviewed and selected from 22 submissions. They explore the above topics, address the underlying challenges, find and improve solutions, and show the application of modeling and simulation in the domains of enterprises, their organizations and underlying business processes.
Despite all the advantages brought by service-oriented architecture (SOA), experts argue that SOA introduces more complexity into information systems rather than resolving it. The problem of service integration challenges modern companies taking the risk of implementing SOA. One of important aspects of this problem relates to dynamic service composition, which has to take into account many types of information and restrictions existing in each enterprise. Moreover, all the changes in business logic should also be promptly reflected. This chapter proposes the approach to solution of the stated problem based on such concepts as model-driven architecture (MDA), ontology modelling and logical analysis. The approach consists of several steps of modelling and finite scope logical analysis for automated translation of business processes into the sequence of service invocations. Formal language of relational logic is proposed as a key element of the proposed approach which is responsible for logical analysis and service workflow generation. We present a logical theory to automatically specialize generic orchestration templates which are close to semantic specification of abstract services in OWL-S. The developed logical theory is described formally in terms of Relational Logic. Our approach is implemented and tested using MIT Alloy Analyzer software.
Pattern structures, an extension of FCA to data with complex descriptions, propose an alternative to conceptual scaling (binarization) by giving direct way to knowledge discovery in complex data such as logical formulas, graphs, strings, tuples of numerical intervals, etc. Whereas the approach to classification with pattern structures based on preceding generation of classifiers can lead to double exponent complexity, the combination of lazy evaluation with projection approximations of initial data, randomization and parallelization, results in reduction of algorithmic complexity to low degree polynomial, and thus is feasible for big data.
The proceedings of the 11th International Conference on Service-Oriented Computing (ICSOC 2013), held in Berlin, Germany, December 2–5, 2013, contain high-quality research papers that represent the latest results, ideas, and positions in the field of service-oriented computing. Since the first meeting more than ten years ago, ICSOC has grown to become the premier international forum for academics, industry researchers, and practitioners to share, report, and discuss their ground-breaking work. ICSOC 2013 continued along this tradition, in particular focusing on emerging trends at the intersection between service-oriented, cloud computing, and big data.
In 2015-2016 the Department of Communication, Media and Design of the National Research University “Higher School of Economics” in collaboration with non-profit organization ROCIT conducted research aimed to construct the Index of Digital Literacy in Russian Regions. This research was the priority and remain unmatched for the momentIn 2015-2016 the Department of Communication, Media and Design of the National Research University “Higher School of Economics” in collaboration with non-profit organization ROCIT conducted research aimed to construct the Index of Digital Literacy in Russian Regions. This research was the priority and remain unmatched for the moment
The study identifies operational risks within service-oriented architecture (SOA) of information systems. As a part of operational risks a new error classification scheme is proposed for SOA applications. It is based on errors of the information systems which are service providers for application with service-oriented architecture. The proposed classification approach was used to classify system errors from two different enterprises (oil and gas industry, metal and mining industry). Besides we conducted a research to identify possible losses from operational risks and estimated losses for each error group per day.
The article is dedicated to the analysis of Big Data perspective in jurisprudence. It is proved that Big Data have to be used as the explanatory and predictable tool. The author describes issues concerning Big Data application in legal research. The problems are technical (data access, technical imperfections, data verification) and informative (interpretation of data and correlations). It is concluded that there is the necessity to enhance Big Data investigations taking into account the abovementioned limits.