A Framework for Evaluating Model-Driven Self-adaptive Software Systems

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition, self-adaptive application, context oriented software developmen

A Framework for Evaluating Model-Driven Self-adaptive Software Systems

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers

Model-Driven Productivity Evaluation for Self-Adaptive Context-Oriented Software Development

Anticipating context changes using a model-based approach requires a formal procedure for analysing and mod- elling their context-dependent functionality, and a stable descrip- tion of the architecture which supports dynamic decision-making and architecture evolution. This article demonstrates the capabil- ities of the context-oriented component-based application-model- driven architecture (COCA-MDA) to support the development of self-adaptive applications; we describe a state-of-the-art case study and evaluate the development effort involved in adopting the COCA-MDA in constructing the application. An intensive analysis of the application requirements simplified the process of modelling the application’s behavioural model; therefore, instead of modelling several variation models, the developers modelled an extra-functionality model. COCA-MDA reduces the development effort because it maintains a clear separation of concerns and em- ploys a decomposition mechanism to produce a context-oriented component model which decouples the applications’ core func- tionality from the context-dependent functionality. Estimating the MDA approach’s productivity can help the software developers to select the best MDA-based methodology from the available solutions proposed in the literature. Thus, counting the source line of code is not adequate for evaluating the development effort of the MDA-based methodology. Quantifying the maintenance adjustment factor of the new, adapted, and reused code is a better estimate of the development effort of the MDA approaches

Remote service discovery and control for ubiquitous service environments in next-generation networks

Doktorgradsavhandling i informasjons- og kommunikasjonsteknologi, Universitetet i Agder, Grimstad, 201

Remote service discovery and control for ubiquitous service environments in next-generation networks

Doktorgradsavhandling i informasjons- og kommunikasjonsteknologi, Universitetet i Agder, Grimstad, 201

New methods of partial transmit sequence for reducing the high peak-to-average-power ratio with low complexity in the ofdm and f-ofdm systems

The orthogonal frequency division multiplexing system (OFDM) is one of the most important components for the multicarrier waveform design in the wireless communication standards. Consequently, the OFDM system has been adopted by many high-speed wireless standards. However, the high peak-to-average- power ratio (PAPR) is the main obstacle of the OFDM system in the real applications because of the non-linearity nature in the transmitter. Partial transmit sequence (PTS) is one of the effective PAPR reduction techniques that has been employed for reducing the PAPR value 3 dB; however, the high computational complexity is the main drawback of this technique. This thesis proposes novel methods and algorithms for reducing the high PAPR value with low computational complexity depending on the PTS technique. First, three novel subblocks partitioning schemes, Sine Shape partitioning scheme (SS-PTS), Subsets partitioning scheme (Sb-PTS), and Hybrid partitioning scheme (H-PTS) have been introduced for improving the PAPR reduction performance with low computational complexity in the frequency-domain of the PTS structure. Secondly, two novel algorithms, Grouping Complex iterations algorithm (G-C-PTS), and Gray Code Phase Factor algorithm (Gray-PF-PTS) have been developed to reduce the computational complexity for finding the optimum phase rotation factors in the time domain part of the PTS structure. Third, a new hybrid method that combines the Selective mapping and Cyclically Shifts Sequences (SLM-CSS-PTS) techniques in parallel has been proposed for improving the PAPR reduction performance and the computational complexity level. Based on the proposed methods, an improved PTS method that merges the best subblock partitioning scheme in the frequency domain and the best low-complexity algorithm in the time domain has been introduced to enhance the PAPR reduction performance better than the conventional PTS method with extremely low computational complexity level. The efficiency of the proposed methods is verified by comparing the predicted results with the existing modified PTS methods in the literature using Matlab software simulation and numerical calculation. The results that obtained using the proposed methods achieve a superior gain in the PAPR reduction performance compared with the conventional PTS technique. In addition, the number of complex addition and multiplication operations has been reduced compared with the conventional PTS method by about 54%, and 32% for the frequency domain schemes, 51% and 65% for the time domain algorithms, 18% and 42% for the combining method. Moreover, the improved PTS method which combines the best scheme in the frequency domain and the best algorithm in the time domain outperforms the conventional PTS method in terms of the PAPR reduction performance and the computational complexity level, where the number of complex addition and multiplication operation has been reduced by about 51% and 63%, respectively. Finally, the proposed methods and algorithms have been applied to the OFDM and Filtered-OFDM (F-OFDM) systems through Matlab software simulation, where F-OFDM refers to the waveform design candidate in the next generation technology (5G)

Video Quality Prediction for Video over Wireless Access Networks (UMTS and WLAN)

Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.Partially sponsored by EU FP7 ADAMANTIUM Project (EU Contract 214751

Challenges of rapid migration to fully virtual education in the age of the Corona virus pandemic: experiences from across the world

The social disruption caused by the sudden eruption of the Corona Virus pandemic has shaken the whole world, influencing all levels of education immensely. Notwithstanding there was a lack of preparedness for this global public health emergency which continues to affect all aspects of work and life. The problem is, naturally, multifaceted, fast evolving and complex, affecting everyone, threatening our well-being, the global economy, the environment and all societal and cultural norms and our everyday activities. In a recent UNESCO report it is noted that nearly a billion and a quarter (which is 67,7 % of the total number) of learners have been affected by the Corona Virus pandemic worldwide. The education sector at all levels has been one of the hardest hit sectors particularly as the academic/school year was in full swing. The impact of the pandemic is widespread, representing a health hazard worldwide. Being such, it profoundly affects society as a whole, and its members that are, in particular, i) individuals (the learners, their parents, educators, support staff), ii) schools, training organisations, pedagogical institutions and education systems, iii) quickly transformed policies, methods and pedagogies to serve the newly appeared needs of the latter. Lengthy developments of such scale usually take years of consultation, strategic planning and implementation. In addition to raising awareness across the population of the dangers of the virus transmission and instigating total lockdown, it has been necessary to develop mechanisms for continuing the delivery of education as well as demanding mechanisms for assuring the quality of the educational experience and educational results. There is often scepticism about securing quality standards in such a fast moving situation. Often in the recent past, the perception was that courses and degrees leading to an award are inferior if the course modules (and sometimes its assessment components) were wholly online. Over the last three decades most Higher Education institutions developed both considerable infrastructure and knowhow enabling distance mode delivery schools (Primary and Secondary) had hardly any necessary infrastructure nor adequate knowhow for enabling virtual education. In addition, community education and various training providers were mainly delivered face-to-face and that had to either stop altogether or rapidly convert materials, exercises and tests for online delivery and testing. A high degree of flexibility and commitment was demanded of all involved and particularly from the educators, who undertook to produce new educational materials in order to provide online support to pupils and students. Apart from the delivery mode of education, which is serving for certificated programmes, it is essential to ensure that learners’ needs are thoroughly and continuously addressed and are efficiently supported throughout the Coronavirus or any other future lockdown. The latter can be originated by various causes and reasons that vary in nature, such as natural or socioeconomical. Readiness, thus, in addition to preparedness, is the primary key question and solution when it comes to quality education for any lockdown. In most countries, the compulsory primary and secondary education sectors have been facing a more difficult challenge than that faced by Higher Education. The poor or in many cases non-existent technological infrastructure and low technological expertise of the teachers, instructors and parents, make the delivery of virtual education difficult or even impossible. The latter, coupled with phenomena such as social exclusion and digital divide where thousands of households do not have adequate access to broadband Internet, Wi-Fi infrastructure and personal computers hamper the promising and strenuous virtual solutions. The shockwaves of the sudden demands on all sectors of society and on individuals required rapid decisions and actions. We will not attempt to answer the question “Why was the world unprepared for the onslaught of the Coronavirus pandemic” but need to ascertain the level of preparedness and readiness particularly of the education sector, to effect the required rapid transition. We aimed to identify the challenges, and problems faced by the educators and their institutions. Through first-hand experiences we also identify best practices and solutions reached. Thus we constructed a questionnaire to gather our own responses but also experiences from colleagues and members of our environment, family, friends, and colleagues. This paper reports the first-hand experiences and knowledge of 33 co-authors from 27 institutions and from 13 different countries from Europe, Asia, and Africa. The communication technologies and development platforms used are identified; the challenges faced as well as solutions and best practices are reported. The findings are consolidated into the four areas explored i.e. Development Platforms, Communications Technologies, Challenges/Problems and Solutions/Best Practices. The conclusion summarises the findings into emerging themes and similarities. Reflections on the lasting impact of the effect of Coronavirus on education, limitations of study, and indications of future work complete the paper

A human factors perspective on volunteered geographic information

This thesis takes a multidisciplinary approach to understanding the unique abilities of Volunteered Geographic Information (VGI) to enhance the utility of online mashups in ways not achievable with Professional Geographic Information (PGI). The key issues currently limiting the use of successful of VGI are the concern for quality, accuracy and value of the information, as well as the polarisation and bias of views within the user community. This thesis reviews different theoretical approaches in Human Factors, Geography, Information Science and Computer Science to help understand the notion of user judgements relative to VGI within an online environment (Chapter 2). Research methods relevant to a human factors investigation are also discussed (Chapter 3). (Chapter 5) The scoping study established the fundamental insights into the terminology and nature of VGI and PGI, a range of users were engaged through a series of qualitative interviews. This led the development of a framework on VGI (Chapter 4), and comparative description of users in relation to one another through a value framework (Chapter 5). Study Two produced qualitative multi-methods investigation into how users perceive VGI and PGI in use (Chapter 6), demonstrating similarities and the unique ability for VGI to provide utility to consumers. Chapter Seven and Study Three brought insight into the specific abilities for VGI to enhance the user judgement of online information within an information relevance context (Chapter 7 and 8). In understanding the outcomes of these studies, this thesis discusses how users perceive VGI as different from PGI in terms of its benefit to consumers from a user centred design perspective (Chapter 9). In particular, the degree to which user concerns are valid, the limitation of VGI in application and its potential strengths in enriching the user experiences of consumers engaged within an information search. In conclusion, specific contributions and avenues for further work are highlighted (Chapter 10)