Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration

Future AI applications require performance, reliability and privacy that the existing, cloud-dependant system architectures cannot provide. In this article, we study orchestration in the device-edge-cloud continuum, and focus on AI for edge, that is, the AI methods used in resource orchestration. We claim that to support the constantly growing requirements of intelligent applications in the device-edge-cloud computing continuum, resource orchestration needs to embrace edge AI and emphasize local autonomy and intelligence. To justify the claim, we provide a general definition for continuum orchestration, and look at how current and emerging orchestration paradigms are suitable for the computing continuum. We describe certain major emerging research themes that may affect future orchestration, and provide an early vision of an orchestration paradigm that embraces those research themes. Finally, we survey current key edge AI methods and look at how they may contribute into fulfilling the vision of future continuum orchestration.Comment: 50 pages, 8 figures (Revised content in all sections, added figures and new section

Hidden depths: the effects of extrinsic data collection on consumer insurance contracts

Commentators have predicted that the insurance industry will soon benefit from technological advancements, such as developments in Artificial Intelligence (‘AI’) and Big Data. The application of AI- and Big Data-powered tools promises cost reduction, the creation of innovative products, and the potential to offer more efficient and tailored services to consumers. However, these new opportunities are mirrored by new legal and regulatory challenges. This article discusses challenges facing Australian data protection law, focusing on (potential) collection of consumers' data by insurers from non-traditional sources. In particular, we examine situations in which consumers may not be aware that the data collected could end up being used to price insurance. In our analysis, we discuss two useful examples of such non-traditional data sources: customer loyalty schemes and social media. These may give rise to several concerning data practices, including a significant increase in the collection of consumers' data by insurers. We argue that datafication of insurer processes may fuel excessive data collection in the context of insurance contracts, generating a substantial risk of harm to consumers, especially in terms of discrimination, exclusion, and unaffordability of insurance. We complement our analysis with the discussion of Australian insurance-specific provisions, asking if, and how, the harms examined could be adequately addressed

The Cloud-to-Thing Continuum

The Internet of Things offers massive societal and economic opportunities while at the same time significant challenges, not least the delivery and management of the technical infrastructure underpinning it, the deluge of data generated from it, ensuring privacy and security, and capturing value from it. This Open Access Pivot explores these challenges, presenting the state of the art and future directions for research but also frameworks for making sense of this complex area. This book provides a variety of perspectives on how technology innovations such as fog, edge and dew computing, 5G networks, and distributed intelligence are making us rethink conventional cloud computing to support the Internet of Things. Much of this book focuses on technical aspects of the Internet of Things, however, clear methodologies for mapping the business value of the Internet of Things are still missing. We provide a value mapping framework for the Internet of Things to address this gap. While there is much hype about the Internet of Things, we have yet to reach the tipping point. As such, this book provides a timely entrée for higher education educators, researchers and students, industry and policy makers on the technologies that promise to reshape how society interacts and operates

Designing Data Spaces

This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II “Data Space Technologies” subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various “Use Cases and Data Ecosystems” from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several “Solutions and Applications”, eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty

Rhythmic Haptic Cueing for Gait Rehabilitation of Hemiparetic Stroke and Brain Injury Survivors

This thesis explores the gait rehabilitation of hemiparetic stroke and brain injury survivors by a process of haptic entrainment to rhythmic cues. Entrainment to auditory metronomes is known to improve gait; this thesis presents the first systematic study of entrainment for gait rehabilitation via the haptic modality. To investigate this approach, a multi-limb metronome capable of delivering a steady, isochronous haptic rhythm to alternating legs was developed, purpose-built for gait rehabilitation, together with appropriate software for monitoring and assessing gait. A formative observational study, carried out at a specialised neurological centre, supplemented by discussions with physiotherapists and neuropsychologists, was used to focus the scope on hemiparetic stroke and brain injury. A second formative study used a technology probe approach to explore the behaviour of hemiparetic participants under haptic cueing using a pre-existing prototype. Qualitative data was collected by observation of, and discussion with, participants and health professionals. In preparation for a quantitative gait study, a formal experiment was carried out to identify a workable range for haptic entrainment. This led to the creation of a procedure to screen out those with cognitive difficulties entraining to a rhythm, regardless of their walking ability. The final study was a quantitative gait study combining temporal and spatial data on haptically cued participants with hemiparetic stroke and brain injury. Gait characteristics were measured before, during and after cueing. All successfully screened participants were able to synchronise their steps to a haptically presented rhythm. For a substantial proportion of participants, an immediate (though not necessarily lasting) improvement of temporal gait characteristics was found during cueing. Some improvements over baseline occurred immediately afterwards, rather than during, haptic cueing. Design issues and trade-offs are identified, and interactions between perception, sensory deficit, attention, memory, cognitive load and haptic entrainment are noted

ENABLING FIRMS IN THE MARCHE REGION TO UNDERSTAND BLOCKCHAIN FOR SUPPLY CHAIN TRACEABILITY THROUGH A TRIPLE HELIX APPROACH.

La presente Tesi esplora come le imprese, particolarmente le PMI, situate nella regione Marche, possono sfruttare le potenzialità offerte dalla tecnologia blockchain per accrescere la propria competitività. Originariamente concepita per permettere transazioni di valore diretto tra pari senza intermediari, la blockchain è stata proposta per applicazioni oltre l'ambito delle criptovalute per la registrazione di dati in modo immutabile e trasparente. La promessa che sottende l'uso della blockchain è quella di superare la mancanza di fiducia che permea diversi settori, abolendo la necessità di fiducia interpersonale e di intermediari fidati. Particolarmente rilevante è il suo impiego nelle catene di fornitura, dove promette di garantire trasparenza nella tracciabilità dei prodotti, anche per quelli del Made in Italy. Considerando l'importanza che le imprese del Made in Italy rivestono per l'economia marchigiana, questa Tesi si focalizza sulle potenzialità della blockchain nella tracciabilità delle catene di fornitura di tali prodotti. Nonostante i molti benefici teorici discussi nella letteratura accademica, l'implementazione della blockchain per la tracciabilità si scontra con due sfide principali. Primo, l'accuratezza dei dati inseriti da fonti esterne, che può richiedere relazioni di fiducia preesistenti e il coinvolgimento di intermediari per la verifica dei dati, reintroducendo paradossalmente la necessità di fiducia e di intermediari che la blockchain mira a eliminare. Secondo, la scalabilità limitata ostacola la memorizzazione di grandi quantità di dati sulle blockchain. Le soluzioni proposte per affrontare la bassa scalabilità, come la memorizzazione off-chain e le blockchain di tipo permissioned, potenzialmente compromettono i principi di decentralizzazione e sicurezza che sono i fondamenti della blockchain. Una scarsità di studi empirici lascia spazio allo scetticismo riguardo la reale capacità della blockchain di eliminare la necessità di fiducia e intermediari nelle catene di fornitura. Vista la scarsità di studi empirici che attestino l'efficacia della blockchain per la tracciabilità, questa Tesi adotta un approccio esplorativo e qualitativo, basato su interviste e sondaggi, per raccogliere evidenze concrete sull'uso della blockchain da parte delle imprese Made in Italy e comprenderne le opportunità e le sfide. Dai risultati emerge che la blockchain per la tracciabilità è adottata dalle imprese del Made in Italy come strumento di marketing business-to-consumer, nonostante il rischio di perdita di dati con la memorizzazione off-chain e l’utilizzo di blockchain pubbliche di terza generazione che impiegano algoritmi di consenso che aumentano la scalabilità a spese di decentralizzazione e sicurezza. Inoltre, nel comprendere e adottare la blockchain per la tracciabilità, le imprese del Made in Italy si affidano quasi completamente a consulenti e fornitori di servizi blockchain, che potrebbero avere un conflitto di interessi nel promuovere la blockchain in una maniera che non tiene conto delle sue limitazioni. La mancanza di accesso diretto ai dati di performance della blockchain rende difficile per gli adottanti valutare la convenienza del servizio blockchain che utilizzano. Infine, l'assenza di quadri giuridici chiari pone ulteriori rischi per le imprese. Al fine di promuovere una comprensione più profonda, critica, e scevra da conflitti di interesse, delle implicazioni della blockchain per la tracciabilità, la Tesi avanza la proposta di un modello di Tripla Elica per la Regione Marche che incoraggi collaborazioni tra il mondo accademico, il settore industriale e le istituzioni governative, facilitate da intermediari dell'innovazione. Questo approccio enfatizza la necessità di decisioni informate, quadri giuridici chiari e collaborazioni strategiche per un'adozione consapevole della blockchain. Per quanto riguarda le implicazioni gestionali, le PMI della regione Marche dovrebbero adottare un approccio prudente verso la blockchain a causa dell'attuale assenza di prove conclusive sui benefici e sui costi di questa tecnologia. È inoltre consigliabile che queste aziende diano priorità alla digitalizzazione delle proprie catene di fornitura utilizzando tecnologie consolidate prima di prendere in considerazione l'adozione della blockchain. In aggiunta, si suggerisce di ricercare informazioni imparziali sulla blockchain, di valutare attentamente i compromessi insiti nel trilemma della blockchain, di assicurarsi di avere accesso diretto ai dati di performance del servizio blockchain utilizzato e di comprendere le implicazioni legali dell'uso di tale tecnologia. Le implicazioni a livello di politiche pubbliche evidenziano la necessità di ambienti normativi capaci di adattarsi per sostenere la sperimentazione con la blockchain e gli sforzi collaborativi, nonché l'importanza di iniziative educative volte a migliorare la comprensione della blockchain. Le direzioni per la ricerca futura includono la necessità di studi interdisciplinari che confrontino la blockchain con le soluzioni di tracciabilità esistenti, esplorino l'impatto degli aspetti giuridici e testino in modo rigoroso le preferenze dei consumatori per prodotti tracciati con blockchain assicurandosi che i partecipanti ai sondaggi ed esperimenti ricevano una descrizione equilibrata delle potenzialità e delle limitazioni di questa tecnologia

Smart Grid Technologies and Implementations

Smart grid has been advocated in both developing and developed countries in many years to deal with large amount of energy deficit and air pollutions. However, many literatures talked about some specific technologies and implementations, few of them could give a clear picture on the smart grid implementations in a macro scale like what is the main consideration for the smart grid implementations, how to examine the power system operation with communication network deployment, how to determine the optimal technology scheme with consideration of economic and political constraints, and so on. Governments and related institutions are keen to evaluate the cost and benefit of new technologies or mechanisms in a scientific way rather than making decision blindly. Decision Support System, which is an information system based on interactive computers to support decision making in planning, management, operations for evaluating technologies, is an essential tool to provide decision makers with powerful scientific evidence. The objective of the thesis is to identify the data and information processing technologies and mechanisms which will enable the further development of decision support systems that can be used to evaluate the indices for smart grid technology investment in the future. First of all, the thesis introduces the smart grid and its features and technologies in order to clarify the benefits can be obtained from smart grid deployment in many aspects such as economics, environment, reliability, efficiency, security and safety. Besides, it is necessary to understand power system business and operation scenarios which may affect the communication network model. This thesis, for the first time, will give detailed requirements for smart grid simulation according to the power system business and operation. In addition, state of art monitoring system and communication system involved in smart grid for better demand side management will be reviewed in order to find out their impacts reflecting to the power systems. The methods and algorithms applied to the smart grid monitoring, communication technologies for smart grid are summarized and the monitoring systems are compared with each other to see the merits and drawbacks in each type of the monitoring system. In smart grid environment, large number of data are need to be processed and useful information are required to be abstracted for further operation in power systems. Machine learning is a useful tool for data mining and prediction. One of the typical machine learning artificial algorithms, artificial neural network (ANN) for load forecasting in large power system is proposed in this thesis and different learning methods of back-propagation, Quasi-Newton and Levenberg-Marquardt, are compared with each other to seek the best result in load forecasting. Bad load forecasting may leads to demand and generation mismatch, which could cause blackout in power systems. Load shedding schemes are powerful defender for power system from collapsing and keep the grid in integral to a maximum extent. A lesson learned from India blackout in July 2012 is analyzed and recommendations on preventing grid from blackout are given in this work. Also, a new load shedding schemes for an isolated system is proposed in this thesis to take full advantage from information sharing and communication network deployment in smart grid. Lastly, the new trend of decision support system (DSS) for smart grid implementation is summarized and reliability index and stability scenarios for cost benefit analysis are under DSS consideration. Many countries and organizations are setting renewable penetration goals when planning the contribution to reduce the greenhouse gas emission in the future 10 or 20 years. For instance, UK government is expecting to produce 27% of renewable energies EU-wide before 2030. Some simulations have been carried out to demonstrate the physical insight of a power system operation with renewable energy integration and to study the non-dispatchable energy source penetration level. Meanwhile, issues from power system reliability which may affect consumers are required to take into account. Reliability index of Centralized wind generations and that of distributed wind generations are compared with each other under an investment perspective