Khubaib Amjad Alam

Impact analysis and change propagation in service-oriented enterprises

ContextThe adoption of Service-oriented Architecture (SOA) and Business Process Management (BPM) is fairly recent. The major concern is now shifting towards the maintenance and evolution of service-based business information systems. Moreover, these systems are highly dynamic and frequent changes are anticipated across multiple levels of abstraction. Impact analysis and change propagation are identified as potential research areas in this regard. ObjectiveThe aim of this study is to systematically review extant research on impact analysis and propagation in the BPM and SOA domains. Identifying, categorizing and synthesizing relevant solutions are the main study objectives. MethodThrough careful review and screening, we identified 60 studies relevant to 4 research questions. Two classification schemes served to comprehend and analyze the anatomy of existing solutions. BPM is considered at the business level for business operations and processes, while SOA is considered at the service level as deployment architecture. We focused on both horizontal and vertical impacts of changes across multiple abstraction layers. ResultsImpact analysis solutions were mainly divided into dependency analysis, traceability analysis and history mining. Dependency analysis is the most frequently adopted technique followed by traceability analysis. Further categorization of dependency analysis indicates that graph-based techniques are extensively used, followed by formal dependency modeling. While considering hierarchical coverage, inter-process and inter-service change analyses have received considerable attention from the research community, whereas bottom-up analysis has been the most neglected research area. The majority of change propagation solutions are top-down and semi-automated. ConclusionsThis study concludes with new insight suggestions for future research. Although, the evolution of service-based systems is becoming of grave concern, existing solutions in this field are less mature. Studies on hierarchical change impact are scarce. Complex relationships of services with business processes and semantic dependencies are poorly understood and require more attention from the research community.

Enabling Far-Edge Analytics: Performance Profiling of Frequent Pattern Mining Algorithms

Far-edge analytics refers to the enablement of data mining algorithms in far-edge mobile devices that are part of mobile edge cloud computing (MECC) systems. Far-edge analytics enables data reduction in mobile environments, hence reducing the data transfer rate and bandwidth utilization cost for mobile-edge communication. In addition, far-edge analytics facilitates local knowledge availability to enable personalized mobile data stream mining applications. Existing literature mainly addresses classification and clustering problems in far-edge mobile devices, but the problem of frequent pattern mining (FPM) remains unexplored. This paper presents the results of an experimental study on the performance profiling of frequent pattern mining algorithms. We developed a real mobile application for performance analysis and profiling of 21 FPM algorithms with various real data sets in terms of execution time, storage complexity, sparsity, density, and data set size. According to the experimental results, large-sized data sets with high sparsity increase computational and storage cost in far-edge mobile devices. To address these issues, we propose a framework and discuss the relevant research challenges for seamless execution of FPM algorithms in MECC systems.

An Uncertainty-aware Integrated Fuzzy AHP-WASPAS Model to Evaluate Public Cloud Computing Services

Abstract Cloud service evaluation and selection has emerged as a significant challenge for consumers and organizational decision makers due to the proliferation and exponential growth of cloud services over the internet. The plethora of cloud service providers (CSPs) with a range of functionally similar public cloud services, makes it difficult for the service consumers to select the appropriate and optimal cloud services. Several evaluation models have been proposed in the past few years. However, existing literature lacks a systematic procedure aggregating the user feedback and real-world performance assessment data, while incorporating the uncertainty involved in the subjective human preferences. In addition, existing literature reports constrained evaluation criteria while neglecting several decisive factors. In this study, we formulate this problem as a Multi-Criteria Decision making (MCDM) problem and develop an integrated decision model based on Fuzzy Analytic Hierarchy Process (FAHP) and Weighted Aggregated Sum-Product Assessment (WASPAS) methods. A comprehensive and multi-dimensional hierarchical model is structured which comprises of 9 primary and 30 secondary evaluation factors. Relative weight assessment of the primary and secondary evaluation factors, is performed through FAHP with extent analysis and WASPAS is used to rank the candidate cloud services. A case study on six real-world Public cloud services is performed to demonstrate the efficacy of the proposed model. Finally, the robustness of the proposed model is validated through sensitivity analysis.

A systematic literature review on vision based gesture recognition techniques

Human Computer Interaction (HCI) technologies are rapidly evolving the way we interact with computing devices and adapting to the constantly increasing demands of modern paradigms. One of the most useful tools in this regard is the integration of Human-to-Human Interaction gestures to facilitate communication and expressing ideas. Gesture recognition requires the integration of postures, gestures, face expressions and movements for communicating or conveying certain messages. The aim of this study is to aggregate and synthesize experiences and accumulated knowledge about Vision-Based Recognition (VBR) techniques. The major objective of conducting this Systematic Literature Review (SLR) is to highlight the state-of-the-art in the context of vision-based gesture recognition with specific focus on hand gesture recognition (HGR) techniques and enabling technologies. After a careful systematic selection process, 100 studies relevant to the four research questions were selected. This process was followed by data collection, a detailed analysis, and a synthesis of the selected studies. The results reveal that among the VBR techniques, HGR is a predominant and highly focused area of research. Research focus is also found to be converging towards sign language recognition. Potential applications of HGR techniques include desktop applications, smart environments, entertainment, sign language interpretation, virtual reality and gamification. Although various experimental research efforts have been devoted to gestures recognition, there are still numerous open issues and research challenges in this field. Lastly, considering the results from this SLR, potential future research directions are suggested, including a much needed focus on grammatical interpretation, hybrid approaches, smartphone devices, normalization, and real-life systems.

Measuring the Impact of Changing Technology in Mobile Phones on User Device Interaction Based on a Qualitative Survey

Gesture based mobile interfaces provide the users a new way in which they use technology in public settings. In this paper, we qualitatively analyze the gestures in touch screen mobile devices in general and its social acceptability in particular. The study describes the social factors which impact on users adoptability of mobile gestures. Since mobile phones are becoming the part of our public appearance, designers must integrate gestures that users consider acceptable for public use. In this regard, a survey is conducted on acceptability of gestures. This survey shows useful information over acceptability of gestures in mobile phones. This study also shows which age group is being attracted more than other groups by new gestures as they increasingly adopt them. A questionnaire is also prepared which is based on accepting rate of new gestures.