A systematic literature review on mobile learning in Saudi Arabia

the aim of this paper is to collects, document, examine and critically analyze the current research literature on mobile learning (m-learning) in higher education institutes HEIs in the Kingdom of Saudi Arabia (KSA) published between 2010 and 2017. It explores the acceptance of using the m-learning, the factors that influence the deployment of m-learning. Investigate the trends in m-learning by systematically analyzing the previous studies. explores new emerging practices relating to the use of mobile technologies in nursing education; identify gaps in the research literature of the m-learning. The result shows there is reasonable evidence that the HEIs in Saudi Arabia face considerable factors in implementing m-learning. Also shows that significant studies assessing the effectiveness of m-learning within Saudi Arabia HEIs are lacking and existing studies lacked a theoretical framework. The absence of studies reporting on existing m-learning study reflects the limited penetration of this technology and associated pedagogies and a need to strengthen research in the field of m-learning in the KSA. © 2017 IEEE

Perspectives on resilience in cloud computing: Review and trends

The development of resilient distributed systems is seen as essential to maintaining stable business and state-run processes due to information systems now underpinning most aspects of society. Cloud computing is now one of the most pervasive usage paradigms and due its novelty, research surrounding its resilience is largely lacking and often varied in terms of developed solutions. Therefore this paper provides an up-to-date review of resilience work in cloud computing. This includes methods of measuring and evaluating resilience, solutions for enabling resilience and alternative architectures developed with a focus upon ensuring resilience from the ground up. Firstly, resilience is defined within the context of cloud computing in order to categorise the work appropriately. © 2017 IEEE

Survivability analogy for cloud computing

As cloud computing has become the most popular computing platform, and cloud-based applications a commonplace, the methods and mechanisms used to ensure their survivability is increasingly becoming paramount. One of the prevalent trends in recent times is a turn to nature for inspiration in developing and supporting highly survivable environments. This paper aims to address the problems of survivability in cloud environments through inspiration from nature. In particular, the community metaphor in nature's predator-prey systems where autonomous individuals' local decisions focus on ensuring the global survival of the community. Thus, we develop analogies for survivability in cloud computing based on a range of mechanisms which we view as key determinants of prey's survival against predation. For this purpose we investigate some predator-prey systems that will form the basis for our analogical designs. Furthermore, due to a lack of a standardized definition of survivability, we propose a unified definition for survivability, which emphasizes as imperative, a high level of proactiveness to thwart black swan events, as well as high capacity to respond to insecurity in a timely and appropriate manner, inspired by prey's avoidance and anti-predation approaches. © 2017 IEEE

Evolvable Embryonics: 2-in-1 Approach to Self-healing Systems

This paper covers the authors’ recent research in the area of evolutionary design optimisation in electronic application domain (Evolvable Hardware). This will be also presented in the context of biologically inspired systems where Evolvable Hardware is concerned with evolutionary synthesis of self-healing systems and potentially hardware capable of online adaptation to dynamically changing environment. We will also illustrate how EAs can produce novel and unintuitive design solutions, and possibly new design principles. The novelty of this research project addresses this compelling change in the traditional landscape of the associated research disciplines by seeking to provide a novel biologically inspired mechanism to support the design optimisation of self-healing architectures, that is Evolvable-Embryonics

Intelligent assisted living framework for monitoring elders

Recently, Ambient Intelligence Systems (AmI) in particular Ambient Assisted Living (AAL) are attracting intensive research due to a large variety of application scenarios and an urgent need for elderly in-home assistance. AAL is an emerging multi-disciplinary paradigm aiming at exploiting information and communication technologies in personal healthcare and telehealth systems for countering the effects of growing elderly population. AAL systems are developed to help elderly people living independently by monitoring their health status and providing caregivers with useful information. However, strong contributions are yet to be made on context binding of newly discovered sensors for providing dynamic or/and adaptive UI for caregivers, as the existing solutions (including framework, systems and platforms) are mainly focused on checking user operation history, browser history and applications that are most used by a user for prediction and display of the applications to an individual user. The aim of this paper is to propose a framework for making the adaptive UI from context information (real-time and historical data) that is collected from caregivers (primary user) and elderly people (secondary user). The collected data is processed to produce the contextual information in order to provide assistive services to each individual caregiver. To achieve this, the proposed framework collects the data and it uses a set of techniques (including system learning, decision making) and approaches (including ontology, user profiling) to integrate assistive services at runtime and enable their bindings to specific caregivers, in so doing improving the adaptability parameter of UI for the AAL. © 2017 IEEE

Cloud based collaborative software development: A review, gap analysis and future directions

Organizations who have transitioned their development environments to the Cloud have started realizing benefits such as: cost reduction in hardware; relatively accelerated development process via reduction of time and effort to set up development and testing environments; unified management; service and functionality expansion; on-demand provisioning and access to resources and development environments. These benefits represent only a fraction of the full potential that could be achieved via leveraging Cloud Computing for the collaborative software development process. Related efforts in this area have been mainly in the areas of: asynchronous collaboration; collaboration in isolated aspects of the Software Development process, such as coding activities; use of open-source tools for contributing, improving, and managing code, etcetera. Although these efforts represent valid contributions and important enablers, they are still missing important aspects which enable a more holistic process, with solid theoretical foundation. This paper reviews this research area, in order to better assess factors and gaps creating the need to enhance the collaborative software development process in the Cloud, to better meet the pressure to collaboratively create better cloud-agnostic applications. © 2017 IEEE

A Critical Review of Practices and Challenges in Intrusion Detection Systems for IoT: Towards Universal and Resilient Systems

The Internet-of-Things (IoT) is rapidly becoming ubiquitous. However the heterogeneous nature of devices and protocols in use, the sensitivity of the data contained within, as well as the legal and privacy issues, make security for the IoT a growing research priority and industry concern. With many security practices being unsuitable due to their resource intensive nature, it is deemed important to include second line defences into IoT networks. These systems will also need to be assessed for their efficacy in a variety of different network types and protocols. To shed light on these issues, this paper is concerned with advancements in intrusion detection practices in IoT. It provides a comprehensive review of current Intrusion Detection Systems (IDS) for IoT technologies, focusing on architecture types. A proposal for future directions in IoT based IDS are then presented and evaluated. We show how traditional practices are unsuitable due to their inherent features providing poor coverage of the IoT domain. In order to develop a secure, robust and optimised solution for these networks, the current research for intrusion detection in IoT will need to move in a different direction. An example of which is proposed in order to illustrate how malicious nodes might be passively detected

Towards cloud driven semantic annotation

Semantic Web Technologies have been an active research area for some time and they are concerned with the development of technological concepts and artefacts that can drive the much elusive semantic web. The idea of a semantic web is a web which comprises of data with well-defined meaning. It is also a web that is context-aware in nature, whereby web documents are easily understandable and able to be processed by machines based on the underlying meaning provided for the documents by making use of annotation data (i.e. metadata). While several concepts have been proposed to drive the semantic web, none has so far demonstrated potentials to transform the current Web 2.0 to a truly semantic Web 3.0. With the advent of diverse technological innovations such as internet of things, cloud computing, big data analytics, etc. it is pertinent to review the state-of-the-art for semantic annotation and how it can be impacted by any of these technologies. This paper provides a review of semantic annotation state-of-the-art and how cloud computing as a paradigm can impact on it. © 2017 IEEE

A Cloud Computing Capability Model for Large-Scale Semantic Annotation

Semantic technologies are designed to facilitate context-awareness for web content, enabling machines to understand and process them. However, this has been faced with several challenges, such as disparate nature of existing solutions and lack of scalability in proportion to web scale. With a holistic perspective to web content semantic annotation, this paper focuses on leveraging cloud computing for these challenges. To achieve this, a set of requirements towards holistic semantic annotation on the web is defined and mapped with cloud computing mechanisms to facilitate them. Technical specification for the requirements is critically reviewed and examined against each of the cloud computing mechanisms, in relation to their technical functionalities. Hence, a mapping is established if the cloud computing mechanism's functionalities proffer a solution for implementation of a requirement's technical specification. The result is a cloud computing capability model for holistic semantic annotation which presents an approach towards delivering large scale semantic annotation on the web via a cloud platform

A Cloud Computing Capability Model for Large-Scale Semantic Annotation

Semantic technologies are designed to facilitate context-awareness for web content, enabling machines to understand and process them. However, this has been faced with several challenges, such as disparate nature of existing solutions and lack of scalability in proportion to web scale. With a holistic perspective to web content semantic annotation, this paper focuses on leveraging cloud computing for these challenges. To achieve this, a set of requirements towards holistic semantic annotation on the web is defined and mapped with cloud computing mechanisms to facilitate them. Technical specification for the requirements is critically reviewed and examined against each of the cloud computing mechanisms, in relation to their technical functionalities. Hence, a mapping is established if the cloud computing mechanism’s functionalities proffer a solution for implementation of a requirement’s technical specification. The result is a cloud computing capability model for holistic semantic annotation which presents an approach towards delivering large-scale semantic annotation on the web via a cloud platform