Smart Cloud Engine and Solution Based on Knowledge Base

AbstractComplexity of cloud infrastructures needs models and tools for process management, configuration, scaling, elastic computing and healthiness control. This paper presents a Smart Cloud solution based on a Knowledge Base, KB, with the aim of modeling cloud resources, Service Level Agreements and their evolution, and enabling the reasoning on structures by implementing strategies of efficient smart cloud management and intelligence. The solution proposed provides formal verification tools and intelligence for cloud control. It can be easily integrated with any cloud configuration manager, cloud orchestrator, and monitoring tool, since the connections with these tools are performed by using REST calls and XML files. It has been validated in the large ICARO Cloud project with a national cloud service provider

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

Towards Extreme and Sustainable Graph Processing for Urgent Societal Challenges in Europe

The Graph-Massivizer project, funded by the Horizon Europe research and innovation program, researches and develops a high-performance, scalable, and sustainable platform for information processing and reasoning based on the massive graph (MG) representation of extreme data. It delivers a toolkit of five open-source software tools and FAIR graph datasets covering the sustainable lifecycle of processing extreme data as MGs. The tools focus on holistic usability (from extreme data ingestion and MG creation), automated intelligence (through analytics and reasoning), performance modelling, and environmental sustainability tradeoffs, supported by credible data-driven evidence across the computing continuum. The automated operation uses the emerging serverless computing paradigm for efficiency and event responsiveness. Thus, it supports experienced and novice stakeholders from a broad group of large and small organisations to capitalise on extreme data through MG programming and processing. Graph-Massivizer validates its innovation on four complementary use cases considering their extreme data properties and coverage of the three sustainability pillars (economy, society, and environment): sustainable green finance, global environment protection foresight, green AI for the sustainable automotive industry, and data centre digital twin for exascale computing. Graph-Massivizer promises 70% more efficient analytics than AliGraph, and 30 % improved energy awareness for extract, transform and load storage operations than Amazon Redshift. Furthermore, it aims to demonstrate a possible two-fold improvement in data centre energy efficiency and over 25 % lower greenhouse gas emissions for basic graph operations.</p

Comparison of Information Representation Formalisms for Scalable File Agnostic Information Infrastructures

In the early days of computing, files where just a natural way of storing information -- which reflected the way one would file their punch cards in a cabinet drawer. Unfortunately, the requirement to fragment information into such chunks, is a huge bottleneck for the evolution of global information space that the Internet has become. The concept of file causes several problems including unnatural clustering of information, unnecessary replication of data and very expensive information discovery in distributed computing environments. The overall goal of this work is to design an architecture enabling new era in computing and networking -- a computing infrastructure without the concept of file. Files are seen by many specialists as one of the main bottlenecks of modern IT systems evolution. This is mostly due to a very unnatural fragmentation of information into chunks which are easier to manage by operating systems but much more difficult for information processing tools and eventually by humans themselves

Mechanisms Driving Digital New Venture Creation & Performance: An Insider Action Research Study of Pure Digital Entrepreneurship in EdTech

Digitisation has ushered in a new era of value creation where cross border data flows generate more economic value than traditional flows of goods. The powerful new combination of digital and traditional forms of innovation has seen several new industries branded with a ‘tech’ suffix. In the education technology sector (EdTech), which is the industry context of this research, digitisation is driving double-digit growth into a projected $240 billion industry by 2021. Yet, despite its contemporary significance, the field of entrepreneurship has paid little attention to the phenomenon of digital entrepreneurship. As several scholars observe, digitisation challenges core organising axioms of entrepreneurship, with significant implications for the new venture creation process in new sectors such as EdTech. New venture creation no longer appears to follow discrete and linear models of innovation, as spatial and temporal boundaries get compressed. Given the paradigmatic shift, this study investigates three interrelated themes. Firstly, it seeks to determine how a Pure Digital Entrepreneurship (PDE) process develops over time; and more importantly, how the journey challenges extant assumptions of the entrepreneurial process. Secondly, it strives to identify and theorise the deep structures which underlie the PDE process through mechanism-based explanations. Consequently, the study also seeks to determine the causal pathways and enablers which overtly or covertly interrelate to power new venture emergence and performance. Thirdly, it aims to offer practical guidelines for nurturing the growth of PDE ventures, and for the development of supportive ecosystems. To meet the stated objectives, this study utilises an Insider Action Research (IAR) approach to inquiry, which incorporates reflective practice, collaborative inquiry and design research for third-person knowledge production. This three-pronged approach to inquiry allows for the enactment of a PDE journey in real-time, while acquiring a holistic narrative in the ‘swampy lowlands’ of new venture creation. The findings indicate that the PDE process is differentiated by the centrality of digital artifacts in new venture ideas, which in turn result in less-bounded processes that deliver temporal efficiencies – hence, the shorter new venture creation processes than in traditional forms of entrepreneurship. Further, PDE action is defined by two interrelated events – digital product development and digital growth marketing. These events are characterised by the constant forking, merging and termination of diverse activities. Secondly, concurrent enactment and piecemeal co-creation were found to be consequential mechanisms driving temporal efficiencies in digital product development. Meanwhile, data-driven operation and flexibility combine in digital growth marketing, to form higher order mechanisms which considerably reduce the levels of task-specific and outcome uncertainties. Finally, the study finds that digital growth marketing is differentiated from traditional marketing by the critical role of algorithmic agencies in their capacity as gatekeepers. Thus, unlike traditional marketing, which emphasises customer sovereignty, digital growth marketing involves a dual focus on the needs of human and algorithmic stakeholders. Based on the findings, this research develops a pragmatic model of pure digital new venture creation and suggests critical policy guidelines for nurturing the growth of PDE ventures and ecosystems

Enterprise architecture driven design of an artefact to support strategic Information Technology decision-making of Small Enterprises in Nigeria and South Africa

Information Technology (IT) is inevitably influencing the way enterprises operate, compete, and grow. The contemporary disruption has not excluded small companies. Small enterprises play a significant role in the growth of every economy but are hindered by limited skills, time, and money. The attributes of small enterprises influence the strategic and day-to-day operations. Small enterprise owners are often the managers who make the strategic decisions in order to solve specific problems. The decision style of small enterprise owner-managers limits the leveraging of IT. To ensure the sustainability of small enterprises in a contemporary business ecosystem, it is pertinent to strategise IT investment decisions. Enterprise architecture is a well-known approach to business and IT alignment. This study aimsto discover and develop how the complex enterprise architecture principles can strategise the IT decisionmaking process in small enterprises with limited resources and informal structures. The pragmatic philosophic stance was the premise for understanding the decision challenges and the development of a roadmap to intervene the problems the researcher identified. The Vaishnavi and Kuechler design science research methodology guided this study. The qualitative research approach was employed to collect verbal data with eleven small enterprise ownermanagers to understand the processes and the challenges of making IT decision in small enterprises. A thematic analysis of the findings revealed that lack of formalisation, limited information, and lack of IT skill created a critical bottleneck of IT investment decisions in small enterprises. An enterprise architecture-driven framework was developed to overcome the bounded rationality approach to IT choices in small enterprises. The framework holistically assesses organisational business-IT capabilities, constraints, and criteria to guide the decisionmaker's choice. The characteristics of small enterprises limit the successful implementation of the enterprise architecture-driven framework as a theoretical guideline for making optimal IT decisions in small enterprises. This study further developed an online IT decision-assistive tool informed by the framework. The instantiation artefact was demonstrated with six small enterprise owners from Nigeria and South Africa. The findings affirmed the prospect, potential, and relevance of an enterprise architecture-driven artefact as a tool to optimise strategic IT decisions in small manufacturing, service, and retail enterprises. The artefact developed in this study provided a practical intervention to the challenges of IT investment decisions in small enterprises

Enterprise architecture driven design of an artefact to support strategic Information Technology decision-making of Small Enterprises in Nigeria and South Africa

Information Technology (IT) is inevitably influencing the way enterprises operate, compete, and grow. The contemporary disruption has not excluded small companies. Small enterprises play a significant role in the growth of every economy but are hindered by limited skills, time, and money. The attributes of small enterprises influence the strategic and day-to-day operations. Small enterprise owners are often the managers who make the strategic decisions in order to solve specific problems. The decision style of small enterprise owner-managers limits the leveraging of IT. To ensure the sustainability of small enterprises in a contemporary business ecosystem, it is pertinent to strategise IT investment decisions. Enterprise architecture is a well-known approach to business and IT alignment. This study aimsto discover and develop how the complex enterprise architecture principles can strategise the IT decisionmaking process in small enterprises with limited resources and informal structures. The pragmatic philosophic stance was the premise for understanding the decision challenges and the development of a roadmap to intervene the problems the researcher identified. The Vaishnavi and Kuechler design science research methodology guided this study. The qualitative research approach was employed to collect verbal data with eleven small enterprise ownermanagers to understand the processes and the challenges of making IT decision in small enterprises. A thematic analysis of the findings revealed that lack of formalisation, limited information, and lack of IT skill created a critical bottleneck of IT investment decisions in small enterprises. An enterprise architecture-driven framework was developed to overcome the bounded rationality approach to IT choices in small enterprises. The framework holistically assesses organisational business-IT capabilities, constraints, and criteria to guide the decisionmaker's choice. The characteristics of small enterprises limit the successful implementation of the enterprise architecture-driven framework as a theoretical guideline for making optimal IT decisions in small enterprises. This study further developed an online IT decision-assistive tool informed by the framework. The instantiation artefact was demonstrated with six small enterprise owners from Nigeria and South Africa. The findings affirmed the prospect, potential, and relevance of an enterprise architecture-driven artefact as a tool to optimise strategic IT decisions in small manufacturing, service, and retail enterprises. The artefact developed in this study provided a practical intervention to the challenges of IT investment decisions in small enterprises

Designs and Analyses in Structured Peer-To-Peer Systems

Peer-to-Peer (P2P) computing is a recent hot topic in the areas of networking and distributed systems. Work on P2P computing was triggered by a number of ad-hoc systems that made the concept popular. Later, academic research efforts started to investigate P2P computing issues based on scientific principles. Some of that research produced a number of structured P2P systems that were collectively referred to by the term "Distributed Hash Tables" (DHTs). However, the research occurred in a diversified way leading to the appearance of similar concepts yet lacking a common perspective and not heavily analyzed. In this thesis we present a number of papers representing our research results in the area of structured P2P systems grouped as two sets labeled respectively "Designs" and "Analyses". The contribution of the first set of papers is as follows. First, we present the princi- ple of distributed k-ary search and argue that it serves as a framework for most of the recent P2P systems known as DHTs. That is, given this framework, understanding existing DHT systems is done simply by seeing how they are instances of that frame- work. We argue that by perceiving systems as instances of that framework, one can optimize some of them. We illustrate that by applying the framework to the Chord system, one of the most established DHT systems. Second, we show how the frame- work helps in the design of P2P algorithms by two examples: (a) The DKS(n; k; f) system which is a system designed from the beginning on the principles of distributed k-ary search. (b) Two broadcast algorithms that take advantage of the distributed k-ary search tree. The contribution of the second set of papers is as follows. We account for two approaches that we used to evaluate the performance of a particular class of DHTs, namely the one adopting periodic stabilization for topology maintenance. The first approach was of an intrinsic empirical nature. In this approach, we tried to perceive a DHT as a physical system and account for its properties in a size-independent manner. The second approach was of a more analytical nature. In this approach, we applied the technique of Master Equations, which is a widely used technique in the analysis of natural systems. The application of the technique lead to a highly accurate description of the behavior of structured overlays. Additionally, the thesis contains a primer on structured P2P systems that tries to capture the main ideas prevailing in the field

Hybrid ToF and RSSI real-time semantic tracking with an adaptive industrial internet of things architecture

Real-time asset tracking in indoor mass production manufacturing environments can reduce losses associated with pausing a production line to locate an asset. Complemented by monitored contextual information, e.g. machine power usage, it can provide smart information, such as which components have been machined by a worn or damaged tool. Although sensor based Internet of Things (IoT) positioning has been developed, there are still key challenges when benchmarked approaches concentrate on precision, using computationally expensive filtering and iterative statistical or heuristic algorithms, as a trade-off for timeliness and scalability. Precise but high-cost hardware systems and invasive infrastructures of wired devices also pose implementation issues in the Industrial IoT (IIoT). Wireless, selfpowered sensors are integrated in this paper, using a novel, communication-economical RSSI/ToF ranging method in a proposed semantic IIoT architecture. Annotated data collection ensures accessibility, scalable knowledge discovery and flexibility to changes in consumer and business requirements. Deployed at a working indoor industrial facility the system demonstrated comparable RMS ranging accuracy (ToF 6m and RSSI 5.1m with 40m range) to existing systems tested in non-industrial environments and a 12.6-13.8m mean positioning accuracy

Access, accountability, and the proliferation of psychological therapy:On the introduction of the IAPT initiative and the transformation of mental healthcare

Psychological therapy today plays a key role in UK public mental health. In large part, this has been through the development of the (specifically English) Improving Access to Psychological Therapies (IAPT) programme. Through IAPT, millions of citizens have encountered interventions such as cognitive behaviour therapy, largely for the treatment of depression and anxiety. This article interrogates how this national response to problems of mental ill-health – and the problematization itself – was developed, accounted for, and sustained. By imbricating economic expertise with accounts of mental ill-health and mechanisms of treatment, IAPT has revivified psychological framings of pathology and therapy. However, it has done so in ways that are more familiar within biomedical contexts (e.g. through recourse to randomized controlled trial studies). Today, the initiative is a principal player in relation to which other services are increasingly developed. Indeed, in many respects IAPT has transformed from content to context within UK public mental health (in a process of what I term ‘contextification’). By documenting these developments, this paper contributes to re-centring questions about the place and role of psychology in contemporary healthcare. Doing so helps to complicate assumptions about the dominance of linear forms of (de)biomedicalization in health-systems