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

Xu, Xiaofei; Motta, Gianmario; Tu, Zhiying; Xu, Hanchuan; Wang, Zhongjie; Wang, Xianzhi

doi:10.1007/s00607-018-0602-0

Cited by 29 publications

(17 citation statements)

References 15 publications

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“…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: ⎧ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎨ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎩…”

Section: Case Studymentioning

confidence: 99%

“…e essence of a transboundary service is the deep convergence of multiple independent services from different industries, different organisations, and different value chains [1]. e Internet of Services (IoS) [2] and Big Service [3] are two similar terms that have attracted wide attention in recent years. e design of transboundary services requires two phases: functional design and quality/capability design.…”

Section: Introductionmentioning

confidence: 99%

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

Liu

et al. 2020

Mathematical Problems in Engineering

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The “transboundary”, an emerging phenomenon in the Internet service ecosystem, is leading to the flourishing of innovative services. A transboundary service incorporates services, resources, and technologies from multiple domains into its business to create a particular competitive advantage and unique user experiences. It is difficult to comprehensively consider all the constraints from multiple domains to precisely design the nonfunctional characteristics of transboundary services, such as quality attributes and capability attributes. We propose a two-phase quality design method for transboundary services called value quality deployment-quality capability deployment (VQD-QCD) based on quality function deployment (QFD). Given the restrictions of transboundary services, VQD-QCD translates the value expectations of multiple stakeholders into an optimal configuration for global quality parameters (GQPs), local quality parameters, and capability parameters. Details of VQD are illustrated. Considering the inherent vagueness and uncertainty of relationships between value expectations and GQPs, and among GQPs, fuzzy least absolute regression and fuzzy nonlinear programming methods are incorporated into QFD to identify the quantitative relations between value indicators and GQPs, and among GQPs, and obtain an optimal configuration scheme for GQPs. Usability of the proposed method is validated through a case study on the “DiDi mobile transportation service”, which is a representative transboundary service in China. Compared with the current method, which is inaccurate and inefficient because its translation between value expectations and relevant quality and capability parameters is artificial and subjective, the proposed method integrates fuzzy least absolute regression and fuzzy nonlinear programming methods into QFD, which facilitate transboundary service designers to precisely and efficiently design the quality and capability characteristics of innovative services in the manner of semiautomatisation, which promotes the innovative design of transboundary services.

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Section: Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Liu

et al. 2020

Mathematical Problems in Engineering

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“…Software -as -a -service has been around for years. Especially with the rise of big data [11], data center [12] and data science [13], we are more concerned about how to better combine the following two aspects of intelligent system [14]. On the other hand, the majority of users (who are in urgent need of simplified smart systems including language, knowledge and software) can make up for the deficiency of a few experts(this paper focuses more on the new exploration of special smart system urgently needed by ordinary users and the direct application of the results).…”

Section: Introductionmentioning

confidence: 99%

Green Tourism Courses Customized with Digital Maps

Yang¹,

Jian²,

Zou³

2020

Proceedings of the International Academic Conference on Frontiers in Social Sciences and Management Innovation (IAFSM 2019)

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This paper aims to introduce map knowledge management combined with personalization and standardization by taking the green tourism course as an example. The method is as follows: Firstly, the digital map knowledge management methods of the map of green tourism course are divided into several categories, namely: the first type is pure natural landscape, the second type is artificial landscape, and the third type is mixed landscape. Then, on the digital map customized by the green tourism course, these three types of landscapes are treated differently. Finally, the application of knowledge graphs and mind maps and other visualization techniques to enrich the personalized digital maps customized by the green tourism curriculum, and then find a series of events that can be standardized batch processing, and establish a smart query system. Its characteristics are: distinguish learning mode between large and small probability and very special exception. The result: not only the three types of landscapes are clearly visible in the digital map smart system customized by the green tourism course, but also the digital map knowledge management combined with personalized and standardized in the case of green tourism courses. The significance is that such a purpose, method and result not only help the teachers and students to better experience the innovative ideas of the green tourism curriculum, but more importantly, reserve enough opportunities for teachers and students to participate, for example, The selection and scoring of the three types of landscapes is a simple participation, and the effect will produce big data; for another example, not only can the standardized query be used, but also the personalized query can be conveniently established with examples in our paper.

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“…Due to the rapid growth in BS from various domains such as Internet of Things, cloud computing, and social networks, selecting and composing these possible candidate services become challenging as they involve huge computational time and cost. This becomes a multi‐objective optimization problem (characterized as a NP‐hard problem) similar to web service composition …”

Section: Introductionmentioning

confidence: 99%

“…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.…”

mentioning

confidence: 99%

A MapReduce‐based modified Grey Wolf optimizer for QoS‐aware big service composition

Bhaskar

Jatoth

Gangadharan

et al. 2019

Concurrency and Computation

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Summary Big services are the collection of interrelated web services across virtual and physical domains, integrating service oriented computing and big data. The rapid growth of Big services that offer similar functionality with varying QoS attributes makes the process of selection and composition of these big services as highly challenging and complex. In this paper, we develop an efficient QoS‐aware Big service composition approach by applying a MapReduce based Modified Grey Wolf Optimizer (MR‐MGWO) that explores more search space, especially in a multidimensional environment. Our approach ensures an optimal balance of exploration and exploitation that enhances the convergence rate and minimizes the computational time. The empirical analysis illustrates that the performance of MR‐MGWO is superior to other similar approaches for solving Big service composition.

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

Cited by 29 publications

References 15 publications

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

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

Green Tourism Courses Customized with Digital Maps

A MapReduce‐based modified Grey Wolf optimizer for QoS‐aware big service composition

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