Big data architecture evolution : 2014 and beyond

This paper aims at developing the Big Data Architecture, and its relation with Analytics, Cloud Services as well as Business Intelligence. The chief aim from all mentioned is to enable the Enterprise Architecture and the Vision of an Organizational target to utilize all the data they are ingesting and regressing data for their short-term or long-terms analytical needs, while making sure that they are addressing during the design phase of such data architecture for both directly and indirectly related stakeholder. Since all stakeholders have their relative interests to utilize the transformed data-sets. This paper also identifies most of the Big Data Architecture, threat analysis within a Big Data System and Big Data Analytic Roadmaps, in terms of smaller components by conducting a gap-analysis that has significant importance as Baseline Big Data Architecture, targeting the end resultant Architectures, once the distillation process of main Big Data Architecture is completed by the Data architects

Accessible Conversational User Interfaces: Considerations for design

Conversational user interfaces (CUIs), such as chatbots and voice assistants, are increasingly common in areas of day-to-day life, and can be expected to become ever more pervasive in the future. These interfaces are being designed for ever more complex interactions, and they appear to have potential to be beneficial to people with disabilities to interact through the web and with technologies embedded in the environment. However, to fulfil this promise they need to be designed to be accessible. This paper reviews a range of current guidance, reports, research and literature on accessible design for different disability groups, including users with mental health issues, autism, health conditions, cognitive disabilities, dyslexia or learning difficulties, and sensory, mobility or dexterity impairments. We collate the elements from this body of guidance that appear relevant to the design of accessible CUIs, and instances where guidance presents issues which are less conclusive, and require further exploration. Using this, we develop a set of questions which could be useful in the further research and development of accessible CUIs. We conclude by considering why CUIs could present opportunities for furthering accessibility, by introducing an example of this potential – a project to design an assistant to support students to disclose their disabilities and organise support, without the need to fill in forms

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Impact and Challenges of Software in 2025: Collected Papers

Today (2014), software is the key ingredient of most products and services. Software generates innovation and progress in many modern industries. Software is an indispensable element of evolution, of quality of life, and of our future. Software development is (slowly) evolving from a craft to an industrial discipline. Software – and the ability to efficiently produce and evolve high-quality software – is the single most important success factor for many highly competitive industries. Software technology, development methods and tools, and applications in more and more areas are rapidly evolving. The impact of software in 2025 in nearly all areas of life, work, relationships, culture, and society is expected to be massive. The question of the future of software is therefore important. However – like all predictions – quite difficult. Some market forces, industrial developments, social needs, and technology trends are visible today. How will they develop and influence the software we will have in 2025?:Impact of Heterogeneous Processor Architectures and Adaptation Technologies on the Software of 2025 (Kay Bierzynski) 9 Facing Future Software Engineering Challenges by Means of Software Product Lines (David Gollasch) 19 Capabilities of Digital Search and Impact on Work and Life in 2025 (Christina Korger) 27 Transparent Components for Software Systems (Paul Peschel) 37 Functionality, Threats and Influence of Ubiquitous Personal Assistants with Regard to the Society (Jonas Rausch) 47 Evolution-driven Changes of Non-Functional Requirements and Their Architecture (Hendrik Schön) 5

A Pervasive Computational Intelligence based Cognitive Security Co-design Framework for Hype-connected Embedded Industrial IoT

The amplified connectivity of routine IoT entities can expose various security trajectories for cybercriminals to execute malevolent attacks. These dangers are even amplified by the source limitations and heterogeneity of low-budget IoT/IIoT nodes, which create existing multitude-centered and fixed perimeter-oriented security tools inappropriate for vibrant IoT settings. The offered emulation assessment exemplifies the remunerations of implementing context aware co-design oriented cognitive security method in assimilated IIoT settings and delivers exciting understandings in the strategy execution to drive forthcoming study. The innovative features of our system is in its capability to get by with irregular system connectivity as well as node limitations in terms of scares computational ability, limited buffer (at edge node), and finite energy. Based on real-time analytical data, projected scheme select the paramount probable end-to-end security system possibility that ties with an agreed set of node constraints. The paper achieves its goals by recognizing some gaps in the security explicit to node subclass that is vital to our system’s operations

A Framework for the Automatic Physical Configuration and Tuning of a Mysql Community Server

Manual physical configuration and tuning of database servers, is a complicated task requiring a high level of expertise. Database administrators must consider numerous possibilities, to determine a candidate configuration for implementation. In recent times database vendors have responded to this problem, providing solutions which can automatically configure and tune their products. Poor configuration choices, resulting in performance degradation commonplace in manual configurations, have been significantly reduced in these solutions. However, no such solution exists for MySQL Community Server. This thesis, proposes a novel framework for automatically tuning a MySQL Community Server. A first iteration of the framework has been built and is presented in this paper together with its performance measurements

A Unified Quality Control Model for E-Learning Systems

Defining, measuring, and achieving quality of e-learning systems are not an easy task. Accordingly, one of the most essential goals for the higher educational institutes is how to reach a high and satisfied level of quality in their learning systems. Achieving such level needs adequate and continuous improvements for the whole e-learning environment elements. Therefore, we aim in our work to construct a unified framework for total quality management system (TQMS) that attempt to satisfy the quality requirements, needs, and standards. The objective of this paper is to present a quality control model for e-learning system that adopts the e-learning platform according to the on-line determination of both user's requirements and global standards. This paper proposed software architecture of quality Management framework for e-learning that could be adopted by different higher education institutes to control the quality of the e-learning process, and assure the quality of the e-learning process outcome. The proposed framework is based on a tri-dimensions quality model. The three dimensions are set of quality requirements for e-learning environment represented in Quality Assurance (QA) policies that will be formalized by using policy based approach, the specifications of e-learning platform that provide learning and teaching activities, and quality control process loop. The architecture for monitor and ensure quality control of the QA policies for e-learning system will deliver the whole learning services in an optimal way. It is also flexible and can be implemented over any e-learning system