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Register a new userFog Computing Systems: State of the Art, Research Issues and Future Trends, with a Focus on Resilience
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Added by
Jose Moura
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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Many future innovative computing services will use Fog Computing Systems (FCS), integrated with Internet of Things (IoT) resources. These new services, built on the convergence of several distinct technologies, need to fulfil time-sensitive functions, provide variable levels of integration with their environment, and incorporate data storage, computation, communications, sensing, and control. There are, however, significant problems to be solved before such systems can be considered fit for purpose. The high heterogeneity, complexity, and dynamics of these resource-constrained systems bring new challenges to their robust and reliable operation, which implies the need for integral resilience management strategies. This paper surveys the state of the art in the relevant fields, and discusses the research issues and future trends that are emerging. We envisage future applications that have very stringent requirements, notably high-precision latency and synchronization between a large set of flows, where FCSs are key to supporting them. Thus, we hope to provide new insights into the design and management of resilient FCSs that are formed by IoT devices, edge computer servers and wireless sensor networks; these systems can be modelled using Game Theory, and flexibly programmed with the latest software and virtualization platforms.
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Industrial processes rely on sensory data for decision-making processes, risk assessment, and performance evaluation. Extracting actionable insights from the collected data calls for an infrastructure that can ensure the dissemination of trustworthy data. For the physical data to be trustworthy, it needs to be cross-validated through multiple sensor sources with overlapping fields of view. Cross-validated data can then be stored on the blockchain, to maintain its integrity and trustworthiness. Once trustworthy data is recorded on the blockchain, product lifecycle events can be fed into data-driven systems for process monitoring, diagnostics, and optimized control. In this regard, Digital Twins (DTs) can be leveraged to draw intelligent conclusions from data by identifying the faults and recommending precautionary measures ahead of critical events. Empowering DTs with blockchain in industrial use-cases targets key challenges of disparate data repositories, untrustworthy data dissemination, and the need for predictive maintenance. In this survey, while highlighting the key benefits of using blockchain-based DTs, we present a comprehensive review of the state-of-the-art research results for blockchain-based DTs. Based on the current research trends, we discuss a trustworthy blockchain-based DTs framework. We highlight the role of Artificial Intelligence (AI) in blockchain-based DTs. Furthermore, we discuss current and future research and deployment challenges of blockchain-supported DTs that require further investigation.
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Yasmine N. M. Saleh
, Claude C. Chibelushi
, Ayman A. Abdel-Hamid andn Abdel-Hamid Soliman
2020
The advent of miniature biosensors has generated numerous opportunities for deploying wireless sensor networks in healthcare. However, an important barrier is that acceptance by healthcare stakeholders is influenced by the effectiveness of privacy safeguards for personal and intimate information which is collected and transmitted over the air, within and beyond these networks. In particular, these networks are progressing beyond traditional sensors, towards also using multimedia sensors, which raise further privacy concerns. Paradoxically, less research has addressed privacy protection, compared to security. Nevertheless, privacy protection has gradually evolved from being assumed an implicit by-product of security measures, and it is maturing into a research concern in its own right. However, further technical and socio-technical advances are needed. As a contribution towards galvanising further research, the hallmarks of this paper include: (i) a literature survey explicitly anchored on privacy preservation, it is underpinned by untangling privacy goals from security goals, to avoid mixing privacy and security concerns, as is often the case in other papers; (ii) a critical survey of privacy preservation services for wireless sensor networks in healthcare, including threat analysis and assessment methodologies; it also offers classification trees for the multifaceted challenge of privacy protection in healthcare, and for privacy threats, attacks and countermeasures; (iii) a discussion of technical advances complemented by reflection over the implications of regulatory frameworks; (iv) a discussion of open research challenges, leading onto offers of directions for future research towards unlocking the door onto privacy protection which is appropriate for healthcare in the twenty-first century.
These days, the development of smart cities, specifically in location-aware, latency-sensitive, and security-crucial applications (such as emergency fire events, patient health monitoring, or real-time manufacturing) heavily depends on a more advance computing paradigms that can address these requirements. In this regard, fog computing, a robust cloud computing complement, plays a preponderant role by virtue of locating closer to the end-devices. Nonetheless, utilized approaches in smart cities are frequently cloud-based, which causes not only the security and time-sensitive services to suffer but also its flexibility and reliability to be restricted. So as to obviate the limitations of cloud and other related computing paradigms such as edge computing, this paper proposes a systematic literature review (SLR) for the state-of-the-art fog-based approaches in smart cities. Furthermore, according to the content of the reviewed researches, a taxonomy is proposed, falls into three classes, including service-based, resource-based, and application-based. This SLR also investigates the evaluation factors, used tools, evaluation methods, merits, and demerits of each class. Types of proposed algorithms in each class are mentioned as well. Above all else, by taking various perspectives into account, comprehensive and distinctive open issues and challenges are provided via classifying future trends and issues into practical sub-classes.
This article outlines our point of view regarding the applicability, state-of-the-art, and potential of quantum computing for problems in finance. We provide an introduction to quantum computing as well as a survey on problem classes in finance that are computationally challenging classically and for which quantum computing algorithms are promising. In the main part, we describe in detail quantum algorithms for specific applications arising in financial services, such as those involving simulation, optimization, and machine learning problems. In addition, we include demonstrations of quantum algorithms on IBM Quantum back-ends and discuss the potential benefits of quantum algorithms for problems in financial services. We conclude with a summary of technical challenges and future prospects.
Game Theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming Multi-Access Edge Computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as Quality of Experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game usefulness, namely: rational vs. evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse trade-offs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios.
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