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2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC 2017)

作者： Jian Xiao Pangao Kou HuN an Electric Research Institute of State Grid Corporation

ISBN: (纸本)9781509064151;9781509064144

In this paper, a new hierarchical distributed fault diagnosis system for hydropower plant equipment was presented This system was employed fog computing which use the Stormbased computing unit as edge computing node and a cloud The type heterogeneous needed by fault diagnosis system and the data processing workflow of hydropower plant equipment were discussed. The system also defines a Case-based Reasoning model to classify the fault type. Finally a real application case is given in this paper.

关键词： Fault Diagnosis fog-computing Hydropower Plant Stream computing Cloud Services

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fog-Based Hierarchical Coordination of Residential Aggregators and Household Demand Response With Power Distribution Grids-Part II: Data Transmission Architecture and Case Studies

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IEEE TRANSACTIONS ON POWER SYSTEMS 2025年第1期40卷 99-112页

作者： Massrur, Hamid Reza Fotuhi-Firuzabad, Mahmud Dehghanian, Payman Blaabjerg, Frede Sharif Univ Technol Elect Engn Dept Tehran 111554363 Iran George Washington Univ Dept Elect & Comp Engn Washington DC 20052 USA Aalborg Univ Dept Energy AAU Energy DK-9220 Aalborg Denmark

Part I of this two-part paper series designed a solution for hierarchical coordination among Household Demand Response (HDR), Residential Aggregators (RAs) and DSO. This companion paper presents a novel three-layer fog-based architecture to establish an efficient data transmission network for the proposed coordination framework. The envisioned communication architecture includes the end-device, edge fog nodes, and cloud-server layers, providing a reliable solution for data collection of large-scale IoT-based Demand Responsive (DR) customers. The time delay and required bandwidth for the proposed data transmission architecture are modeled. To trace the effectiveness and economic impacts of the proposed fog-based hierarchical HDR-RAs-DSO distributed coordination framework, we perform extensive numerical studies on an enhanced IEEE 33-Bus test system. Several simulations are performed to investigate the time delay and required bandwidth of the proposed data transmission architecture in various scenarios, where it is found that the proposed coordination framework increases the RAs' benefits and flexibility, while in compliance with the network operating constraints. Additionally, the proposed HDR-RAs-DSO coordination framework provides a less costly solution for customers with HDR capability and results in greater profits for residential prosumers.

关键词： AMI bandwidth cloud-computing demand response (DR) data transmission fog-computing IoT latency time delay transactive energy

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Studying the end-to-end performance, energy consumption and carbon footprint of fog applications 29

Studying the end-to-end performance, energy consumption and ...

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29th IEEE Symposium on Computers and Communications (IEEE ISCC)

作者： Courageux-Sudan, Clement Orgerie, Anne-Cecile Quinson, Martin Univ Rennes IRISA CNRS INRIA Rennes France

ISBN: (纸本)9798350354249;9798350354232

The deployment of applications closer to end-users through fog computing has shown promise in improving network communication times and reducing contention. However, the use of fog applications such as microservices necessitates intricate network interactions among heterogeneous devices. Consequently, understanding the impact of different application and infrastructure parameters on performance becomes crucial. Current literature either offers end-to-end models that lack granularity and validation or fine-grained models that only consider a portion of the infrastructure. Our research first compares experimentally the accuracy of the existing integrated frameworks. We then combine one of these tools with a collection of validated models to obtain comprehensive metrics regarding microservice applications operating in the fog. Through a use-case, we demonstrate the effectiveness of our approach in investigating fog environments, from examining application latencies to greenhouse gas emissions.

关键词： Modeling and simulation fog-computing Microservice Performance evaluation Energy consumption

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fog-cloud scheduling simulator for reinforcement learning algorithms

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International Journal of Information Technology (Singapore) 2023年 1-17页

作者： Al-Hashimi, Mustafa Ahmed Adnan Rahiman, Amir Rizaan Muhammed, Abdullah Hamid, Nor Asilah Wati Department of Communication Technology and Networks Universiti Putra Malaysia (UPM) Serdang 43400 Malaysia

fog computing is a popular choice for Internet of Things (IoT) applications, such as electricity, health, transportation, smart cities, security, and more. Due to its decentralized architecture, fog computing offers low latency processing and ensures the preservation of information between the source and the cloud resources. Additionally, it can be integrated with the cloud to provide satisfactory and efficient service simultaneously. However, the main challenge with fog computing is that the edge nodes, called fog devices, have limited processing capabilities and storage for dynamic high-level operations. Therefore, supplying optimized scheduling algorithms to provide satisfactory quality service for the node’s task execution and processing becomes demanding. Most existing simulators are built based on simplified situations, which causes degradation in performance when realistic scenarios are considered. This study presents a developed simulator that captures all mentioned realistic scenarios by providing the feature of integrability with the reinforcement learning (RL) algorithm. Furthermore, three validation steps have been used to measure the simulator’s effectiveness: real-time visualization, intense task arrival, and preservation test have been used, and the results proved the simulator suitable for dealing with realistic situations. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： fog-computing Load balancing Reinforcement learning Scheduling Simulator

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Federated Scheduling of fog-native Applications over Multi-Domain Edge-to-Cloud Ecosystem 19

Federated Scheduling of Fog-native Applications over Multi-D...

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19th International Conference on Network and Service Management (CNSM) - Network and Service Management in the Era of Generative AI and Digital Twins

作者： AL-Naday, Mays Karagiannis, Vasileios De Block, Tom Volckaert, Bruno Univ Essex Colchester Essex England Austrian Inst Technol Vienna Austria AIOTI Brussels Belgium Univ Ghent imec Ghent Belgium

ISBN: (纸本)9783903176591

fog computing is emerging as geo-distributed and connected edge-to-cloud ecosystems, spanning multiple domains operated by different entities. Consequently, fog-compatible applications need to support distributed operations and decentralized management. This promoted the adoption of the microservices architecture, to facilitate application modularity and autonomy. Transitioning to fog-native applications, i.e., running distributed microservice workflows over multiple domains, is a challenging endeavor. On one hand, distributing workflows require awareness of the intents and dependencies of microservices, as this may impact the supply of data and the perceived Quality of Service (QoS). On the other hand, the variant capacities and energy supply, coupled with limited information-sharing across fog autonomies, hinders the prospect of end-to-end optimization. To tackle such problems, we propose a novel federate optimisation algorithm for multi-domain scheduling of fog-native microservice workflows. The algorithm incorporates workflow intents in decision-making by combining Bender's decomposition with Alternating Direction Method of Multipliers (ADMM) to provide optimized workflow placement, mapping, routing and admission. The performance of the algorithm is evaluated analytically and compared to state-of-the-art intent-based ADMM (iADMM). The results show performance trade-offs with the proposed iBADMM (direct), with the latter improving the fraction of workflow greenness by approximate to 15%.

关键词： fog-computing fog-native microservices workflow placement optimisation

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Non-Repudiation Storage and Access Control Scheme of Insurance Data Based on Blockchain in IPFS

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IEEE ACCESS 2020年 8卷 155145-155155页

作者： Sun, Jin Yao, Xiaomin Wang, Shangping Wu, Ying Xian Univ Technol Sch Sci Xian 710054 Peoples R China

The insurance business plays a quite significant role in people's lives, but in the process of claim settlement, there are still various frauds such that the insurance companies' refusal to compensate or customers' malicious fraud to obtain compensation. Therefore, it is very important to ensure fair and just claims. In this paper, by combining the blockchain technology and the ciphertext-policy attribute-based encryption system, we build a scheme for secure storage and update for insurance records under the InterPlanetary File System (IPFS) storage environment in the insurance system. In this scheme, we use the fog node to outsource encryption of insurance records to improve the efficiency of the staff;In addition, we store encrypted insurance records on IPFS to ensure the security of the storage platform and avoid the single point failure of the centralized mechanism. In addition, we use the immutability of the blockchain to achieve the non-repudiation of both insurance companies and the client. The security proof shows that the proposed scheme can achieve selective security against selected keyword attacks. Our scheme is efficient and feasible under performance analysis and real data set experiments.

关键词： Insurance Encryption Outsourcing Companies Access control Attribute-based encryption blockchain ciphertext update fog-computing interplanetary file system

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The Rainbow through the Lens of Dew 43

The Rainbow through the Lens of Dew

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43rd International Convention on Information, Communication and Electronic Technology (MIPRO)

作者： Sojat, Zorislav Skala, Karolj Rudjer Boskovic Inst Ctr Informat & Comp Zagreb Croatia

ISBN: (纸本)9789532330991

Ecological Responsibility of Computer Science is essential in further development of the science and application of computer technology. The rapid development of all kinds of computer controlled things and mobile devices, without and with Internet connectivity, represents presently the most prominent information technology application area. On the lowest level, below the Edge of Internet, we have a huge amount of individual devices ("things") which do actually the most significant amount of information processing. Those are computer controlled utensils of all kinds - cars, boilers, production machines, traffic lights, plant carers etc., directly intertwined with our natural and human physical environment and our immediate surroundings. These devices, which are neither at the Cloud or fog edge, nor even at the mobile edge, are the basis of the Dew computing Paradigm. Further exploration and usage of the realm of possibilities of Dew computing will solve the basic problems of integration of the "dew" level with the higher service level(s) in the Dew-fog-Cloud hierarchy. When the distributed Cloud-Dew service architecture is developed and adopted, a Cloud server and many Dew servers will be able to cooperate as a distributed application to provide controls or services. In view of that it is absolutely necessary to see the present (and specifically future) development through the eyes of Philosophy of computing and Ethics, and further the development through application of Ethical and Ecological principles. The Rainbow Ecosystem is a pragmatical hierarchical abstract cybernetic representation of an ecologically viable system, consisting of 9 essential areas, and applicable recursively throughout the integrated hierarchy. The ecological viability of the abstract system will enable proper ecologically responsible development of Rainbow computing Services, integrating our living Nature-Human-Machine ecosystem.

关键词： Ecological Responsibility of Computer Science Philosophy of computing Ethics Ecology Viable System Requisite Variety Rainbow Ecosystem Rainbow-computing Services Dew-computing fog-computing Cloud-computing

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Multi-Class Management With Sub-Class Service for Autonomous Electric Mobility On-Demand Systems

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2019年第7期68卷 7155-7159页

作者： Belakaria, Syrine Ammous, Mustafa Smith, Lauren Sorour, Sameh Abdel-Rahim, Ahmed Univ Idaho Dept Elect & Comp Engn Moscow ID 83844 USA Univ Idaho Dept Civil & Environm Engn Moscow ID 83844 USA Univ Idaho Natl Inst Adv Transportat Technol Moscow ID 83844 USA

This paper aims to resolve a clear and unrealistic limitation found in recent works that have proposed solutions to the massive demand for the autonomous electric mobility-on-demand (AEMoD) services. Namely, this paper will focus on the matched charge-to-trip only service by enabling sub-class service;i.e., allowing vehicles to serve customer classes with trips needing less charge. The paper proposes a multi-class management system with a new queuing model for one city zone, and then derives the stability conditions of the system. Proportions of vehicles from each class that will immediately serve customers with sub-class service or full/partial charge are modeled, and the maximum expected response time of the system is then minimized by optimizing these vehicle service decisions. The advantages of the new model are then compared with previously proposed schemes and non-optimized models through simulations.

关键词： Autonomous Vehicles electric mobility AEMODs queuing systems fog-computing

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AI at the Edge for Sign Language Learning Support 1

AI at the Edge for Sign Language Learning Support

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1st IEEE International Conference on Humanized computing and Communication (HCC)

作者： Battistoni, Pietro Di Gregorio, Marianna Sebillo, Monica Vitiello, Giuliana Univ Salerno Dipartimento Informat Salerno Italy

ISBN: (纸本)9781728141251

In the field of multimodal communication, sign language is and continues to be, one of the most understudied areas. Thanks to the recent advances in the field of deep learning, there are far-reaching implications and applications that neural networks can have for sign language mastering. This paper describes a method for ASL alphabet recognition using Convolutional Neural Networks (CNN), which allows to monitor user's learning progress. American Sign Language (ASL) alphabet recognition by computer vision is a challenging task due to the complexity in ASL signs, high interclass similarities, large intraclass variations, and constant occlusions. We produced a robust model that classifies letters correctly in a majority of cases. The experimental results encouraged us to investigate the adoption of AI techniques to support learning of a sign language, as a natural language with its own syntax and lexicon. The challenge was to deliver a mobile sign language training solution that users may adopt during their everyday life. To satisfy the indispensable additional computational resources to the locally connected enduser devices, we propose the adoption of a fog-computing Architecture.

关键词： component fog-computing Neural Network Sequence Learning Sign Language

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Multi Criteria Decision Making (MCDM) based Spectrum Moderator for fog-Assisted Internet of Things 15

Multi Criteria Decision Making (MCDM) based Spectrum Moderat...

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15th International Conference on Mobile Systems and Pervasive computing (MobiSPC) / 13th International Conference on Future Networks and Communications (FNC)

作者： Eswaran, Subha P. Sripurushottama, Sridhar Jain, Manoj CRL Bharat Elect Ltd Bangalore 560013 Karnataka India ValueMomentum Inc Piscataway NJ 08854 USA

Internet of Things (IoT) comprises of large number of devices which are heterogeneous in their hardware potentials and types of data traffic. In addition, IoT network is not having a common QoS (Quality of Service) goal but exhibits heterogeneous QoS demands which are dynamically driven by different IoT services such as smart city, e-health, e-business, smart parking etc. These heterogeneous services result in sporadic spectrum usage and make it difficult to achieve spectrum efficiency in IoT. It will also lead to spectrum scarcity for emergency IoT services. In this paper, Multi Criteria Decision Making (MCDM) approach is proposed to coordinate IoT devices in spectrum sharing. This frame work evaluates and ranks the available spectrum bands based on their multiple spectral characteristics to match with the capacities and QoS needs of IoT devices. The complexity of the traditional multiple criteria ranking is reduced by one-fourth by introducing a Service-based Analytical Hierarchical Processing (S-AHP). Proposed framework is realized with fog computing-MapReduce infrastructure to meet the latency constraints of IoT devices. Hadoop based simulation results show that the proposed approach achieves improved spectrum utilization and reduced service drops in comparison with other MCDM approaches such as Simple Additive Weighting (SAW) and Preference Selection Index (PSI). (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： MCDM fog-computing IoT AHP Spectrum management

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