Includes bibliographical references.

The Concept of Modularity in the Context of IS/IT Project Outsourcing: An Empirical Case Study of a Belgian Technology Services Company -- An Analysis on Task Migration Strategy of Big Data Streaming Storm Computing Framework for Distributed Processing -- Mapping Student Performance With Employment Using Fuzzy C-Means.

[Article Title: The Concept of Modularity in the Context of IS/IT Project Outsourcing: An Empirical Case Study of a Belgian Technology Services Company/ Shahzada Benazeer, Jan Verelst, and Philip Huysmans, p. 1-17]

Abstract: Information systems and information technology (IS/IT) services are often outsourced to external partners for multiple reasons. The outsourcing literature is persistently reporting high failure rates in IS/IT project outsourcing. Literature suggests that the IS/IT project outsourcing is a complex maneuver, but unfortunately, none of the proposed remedies (mitigating actions) have considered addressing the complexity related issue in IS/IT project outsourcing. This paper explores the concept of modularity, as it has been applied in many other fields in order to manage complexity and enhance agility/flexibility. This paper presents a case study conducted at a Belgian organization involved in technology services and is part of a research project consisting of four cases. This study illustrates a systematic approach, how the concept of modularity can be applied in identifying ‘couplings' which may be responsible for increasing complexity to IS/IT project outsourcing. This study is a first attempt to gain insight into this phenomenon.

DOI: 10.4018/IJISMD.2020100101

[Article Title: An Analysis on Task Migration Strategy of Big Data Streaming Storm Computing Framework for Distributed Processing/ Xiling Hu, p. 18-35]

Abstract: In this modern era, a large volume of data is generated regularly, which needs to be processed for gaining profits of latent information. The processing of big data is composed of a challenge termed as communication overhead. In order to minimize communication overhead on the premise of various resource constraints, a task migration strategy under heterogeneous storm environment is proposed. The proposed strategy is based on the establishment and demonstration of storm resource constraint model, optimal communication overhead model, and task migration model. Where the source node selection algorithm adds the nodes beyond the threshold to the source node set according to the load of CPU, memory, and network bandwidth of each working node in the cluster and the priority order of various resources. The experiment shows that compared with the existing research, computing storm can effectively reduce the delay and communication overhead between nodes, and the execution overhead is small.

DOI: 10.4018/IJISMD.2020100102

[Article Title: Mapping Student Performance With Employment Using Fuzzy C-Means/ Ishwank Singh, Sai Sabitha, Tanupriya Choudhury, Archit Aggarwal, and Bhupesh Kumar Dewangan, p. 36-52]

Abstract: Technical organisations are ranked based on performance indicators like resources, students' intake, global reputation, and research activities. Student performance and placement are important factors in deciding the ranking of a university. Student performance analysis is a recent and widely researched domain aimed at reforming the education system. The analysis assists institutions to understand and improve their performance and educational outcomes. Admissions, academics, and placement are the three most significant processes during which the large amount of data is gathered within a university and there is a requirement of analysis. The data mining techniques are used for data analysis processes and it encompasses data understanding, pre-processing, modelling, and implementation. In this research work, fuzzy c-means clustering technique is used to understand fuzziness of student performance, classify and map the student performance to employability. To understand this objective, the dataset has been collected from universities, pre-processed, and analysed.

DOI: 10.4018/IJISMD.2020100103