A new paradigm of software service engineering in big data and big service era

Abstract

Servitization is one of the most significant trends that reshapes the information world and society in recent years. The requirement of collecting, storing, processing, and sharing of the Big Data has led to massive software resources being developed and made accessible as web-based services to facilitate such process. These services that handle the Big Data come from various domains and heterogeneous networks, and converge into a huge complicated service network (or ecosystem), called the Big Service. The key issue facing the big data and big service ecosystem is how to optimally configure and operate the related service resources to serve the specific requirements of possible applications, i.e., how to reuse the existing service resources effectively and efficiently to develop the new applications or software services, to meet the massive individualized requirements of end-users. Based on analyzing the big service ecosystem, we present in this paper a new paradigm for software service engineering, RE2SEP (Requirement-Engineering Two-Phase of Service Engineering Paradigm), which includes three components: serviceoriented requirement engineering, domain-oriented service engineering, and

A QFD-Based Quality and Capability Design Method for Transboundary Services

“…By substituting the upper and lower bounds of the λ-cut set into the nonlinear programming model, two nonlinear programming models that consist of precise parameters are obtained: (1) 11 d (1) 12 d (1) 16 d (1) 21 d (1) 22 d (1) d (1) 61 d (1) 61 (2) 11 d (2) 12 d (2) 16 d (2) 21 d (2) 22 d (2) 26 d (2) 61 d (2) 61 To convert FComJM into FConJM by using the following formula: ⎧ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎨ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎩…”

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Green Tourism Courses Customized with Digital Maps

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“…This becomes a multi-objective optimization problem (characterized as a NP-hard problem) similar to web service composition. 2,3 Metaheuristic algorithms are applied for solving many real-world applications. These algorithms try to identify the global optimal solution by exploring the overall search space.…”