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17th IEEE International Conference on Industrial and Information Systems, ICIIS 2023

作者： Wimal, Kesara Liyanage, Geethapriya School of Computer Science and Engineering University of Westminster LondonW1B 2HW United Kingdom Department of Computer Science and Engineering University of Moratuwa Moratuwa10400 Sri Lanka

ISBN: (纸本)9798350323634

A consensus protocol plays a vital role in any blockchain platform by ensuring all components agree on common data values and follow the same course of action, even in the presence of defective components. This research project has discovered a problem associated with contemporary blockchain consensus protocols, which has an impact on both users of blockchain technology and investors in cryptocurrencies. The question of whether current blockchain platforms are truly decentralized has been raised by the blockchain community over a period of time. The most popular blockchains use Proof of Work (PoW), Proof of Stake (PoS), or a combination of both, but both systems have limitations in terms of decentralization. Several alternative consensus protocols have emerged recently, but none have achieved total decentralization or welcomed any level user to be the next miner or forger. Therefore, true decentralization of a blockchain system is more challenging as most of the popular consensus protocols were invented to accommodate decentralization but eventually, driven by the centralization of power. This paper proposes a truly decentralized consensus protocol that is capable of avoiding the centralization of power even in the future regardless of the number of peers. The protocol also makes sure it avoids the use of specialized hardware resources, decreases the level of energy consumption, and encourages network activities. Additionally, the novel consensus protocol offers a more democratic and fair approach to blockchain consensus. © 2023 IEEE.

关键词： Blockchain

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A Knowledge Graph-Based Deep Learning Framework for Efficient Content Similarity Search of Sustainable Development Goals Data

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Data Intelligence 2023年第3期5卷 663-684页

作者： Irene Kilanioti George A.Papadopoulos School of Electrical and Computer Engineering National Technical University of Athens9 Heroon Polytechneiou St.Zografou Campus Athens15780Greece Department of Computer Science University of Cyprus1 University AvenueAglantziaCY-2109NicosiaCyprus

Sustainable development denotes the enhancement ofliving standards in the present without compromising future generations'*** Development Goals(SDGs)quantify the accomplishment of sustainable development and pave the way for a world worth living in for future *** can contribute to the achievement of the SDGs by guiding the actions of practitioners based on the analysis of SDG data,as intended by this *** propose a framework of algorithms based on dimensionality reduction methods with the use of Hilbert Space Filling Curves(HSFCs)in order to semantically cluster new uncategorised SDG data and novel indicators,and efficiently place them in the environment of a distributed knowledge graph ***,a framework of algorithms for insertion of new indicators and projection on the HSFC curve based on their transformer-based similarity assessment,for retrieval of indicators and loadbalancing along with an approach for data classification of entrant-indicators is ***,a thorough case study in a distributed knowledge graph environment experimentally evaluates our *** results are presented and discussed in light of theory along with the actual impact that can have for practitioners analysing SDG data,including intergovernmental organizations,government agencies and social welfare *** approach empowers SDG knowledge graphs for causal analysis,inference,and manifold interpretations of the societal implications of SDG-related actions,as data are accessed in reduced retrieval *** facilitates quicker measurement of influence of users and communities on specific goals and serves for faster distributed knowledge matching,as semantic cohesion of data is preserved.

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Spatio-Temporal Service Analysis in Multi-Layer Non-Terrestrial Networks

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Journal of Communications and Information Networks 2024年第1期9卷 43-55页

作者： Qian Chen Weixiao Meng Shuai Han Cheng Li School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China School of Engineering Science Simon Fraser UniversityBurnabyBC V5A 1S6Canada Department of Electrical and Computer Engineering Memorial UniversitySt.John’sNL A1B 3X5Canada

In the advent of the 6G era, non-terrestrial networks (NTN) with expansive coverage are being increasingly recognized as a vital supplement to cellular networks for facilitating seamless communication. The intricate interplay between network performance and service quality necessitates a thorough investigation into the modeling and analysis of services for efficient construction of *** studies on service analysis, predominantly focused on terrestrial networks,fall short in addressing the unique challenges posed by NTN,particularly those related to platform distribution and antenna gain modeling. This deficiency in research,coupled with the varying preferences of users for different network types, forms the basis of this study. This paper explores the spatio-temporal characteristics of services within a multi-layered NTN *** this context,the spatial distribution of the platforms is modeled using a binomial point process, and the antennas are characterized by a sectorized beam pattern. We derive the closed-form expressions for the association probability,the number of accessed users, and the arrival rate of services with certain delay requirements towards different types of NTN. Simulation results are provided to evaluate the influence of various parameters on the association probability, the number of accessed users, and the total arrival rate of services. The number of satellites can be determined to achieve the optimal system utility,balancing the accessed services, offloading effects, and launching costs. This initial investigation lays the groundwork for further theoretical progress in the service analysis and platform deployment of NTN.

关键词： association strategy non-terrestrial networks service analysis stochastic geometry system utility

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Open Source Sounding Rocket-based Free-Falling Platform to Conduct Reduced Gravity Research

Open Source Sounding Rocket-based Free-Falling Platform to C...

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2024 IAF Microgravity sciences and Processes Symposium at the 75th International Astronautical Congress, IAC 2024

作者： Dalla Pria, G.L. Brückner, V. Åkerlund, B. Almqvist, E. Arancibia Parra, L. Broström, A. Buck, C. Gels, J. Hollmark, A. Höglund, F. Jakobsson, A. Korotkijs, A. Malmqvist, A. Mårtensson, J. Kuhn, T. Department of Computer Science Electrical and Space Engineering Luleå University of Technology Bengt Hultqvists väg 1 Kiruna981 92 Sweden

ISBN: (纸本)9798331312077

Free fall Experiment uNit for Reduced gravity Investigations and Research (FENRIR) is a Rocket Experiment for University Students (REXUS) project, based at the Kiruna Space Campus of Lulea University of Technology (LTU), which will fly onboard a sounding rocket in March 2025. It offers an easy-to-use platform for future free-falling experiments that need to be ejected from sounding rockets. A Free Falling Unit (FFU) will be ejected from the rocket just before its apogee at approximately 70 km, ensuring around 70 seconds of reduced gravity. To increase the quality of reduced gravity conditions, an Attitude Stabilisation System consisting of three reaction wheels is included in the FFU. To prove its feasibility, the FFU hosts an experiment related to Phase Change Materials during its maiden flight. The behaviour of the substance is expected to vary due to the absence of buoyancy convection in reduced gravity conditions. This scientific experiment will serve as an example of the many possible scientific investigations that can be performed on the platform. After experiencing reduced gravity, the FFU recovery system will deploy a parachute and relay location data to the users to ensure safe recovery of the experiments inside. Finally, after FENRlR's maiden flight and post-flight activities, the entire project will be published as open source and the physical structure will be inherited by LTU to be potentially reused. Upper secondary and university students are foreseen as potential end-users: thanks to FENRlR's apparatus, they will have the opportunity to focus only on the mission's experiment and accompanying electronics, without having to design the entire structure from scratch. The platform is designed modularly to ensure ease of use and adjustability for different needs and use cases. This paper summarises the development of the FENRIR platform and how internal and external stakeholders and partners have driven the design and implementation process. Copyright © 20

关键词： Sounding rockets

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Intelligent Digital Twin Communication Framework for Addressing Accuracy and Timeliness Tradeoff in Resource-Constrained Networks

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IEEE Transactions on Cognitive Communications and Networking 2024年第3期11卷 1954-1965页

作者： Cakir, Lal Verda Thomson, Craig J. Ozdem, Mehmet Canberk, Berk Nguyen, Van-Linh Duong, Trung Q. Edinburgh Napier University School of Computing Engineering and Built Environment EdinburghEH10 5DT United Kingdom BTS Group Istanbul Turkey Turk Telekom Turkey Department of Computer Science and Information Engineering Taiwan Memorial University of Newfoundland Faculty of Engineering and Applied Science St. John'sNLA1C 5S7 Canada Queen's University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom

The accuracy and timeliness tradeoff prevents Digital Twins (DTs) from realizing their full potential. High accuracy is crucial for decision-making, and timeliness is equally essential for responsiveness. Therefore, this tradeoff in DT communication must be addressed to achieve DT synchronization. Previous studies identified the issue but considered the problem as maximizing data transfer, which is infeasible due to resource constraints. To facilitate this, we quantify accuracy and timeliness as E and φ and define the problem as joint minimisation. We then introduce the Intelligent DT Communication (IDTC) Framework to solve the problem, which includes machine learning-based Predictive Synchronization (PS) and DT synchronization management (DTSYNC) protocol. Here, PS uses imputation and forecasting to generate future values, which are utilized to update DT at the projected time points. This mechanism of PS enables lowering E and φ of the communication. Subsequently, we utilize the DTSYNC to control synchronization and optimise the twining frequency ft. We evaluate the proposed framework using a public dataset and compare its performance with several state-of-the-art studies in a real-world scenario. Evaluation results indicate that IDTC outperforms the existing methods by 80% for E and 84% for φ while enabling ft adjustment, resulting in 3.8 times goodput improvement. © 2015 IEEE.

关键词： Adversarial machine learning

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Deep Q-Learning-Based Resource Management in IRS-Assisted VLC Systems

IEEE Transactions on Machine Learning in Communications and ...

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IEEE Transactions on Machine Learning in Communications and Networking 2024年 2卷 34-48页

作者： Hammadi, Ahmed Al Bariah, Lina Muhaidat, Sami Al-Qutayri, Mahmoud Sofotasios, Paschalis C. Debbah, Merouane Technology Innovation Institute Abu Dhabi United Arab Emirates Khalifa University Center for Cyber-Physical Systems Department of Electrical Engineering and Computer Science Abu Dhabi United Arab Emirates Carleton University Department of Systems and Computer Engineering OttawaK1S 5B6 Canada Khalifa University Department of Electrical Engineering and Computer Science Abu Dhabi United Arab Emirates Tampere University Department of Electrical Engineering Tampere33014 Finland Khalifa University KU 6G Center Abu Dhabi United Arab Emirates

Visible Light Communication (VLC) is a promising enabling technology for the next-generation wireless networks, as it complements radio-frequency (RF)-based communications by providing wider bandwidth, higher data rates, and immunity to interference from electromagnetic sources. However, due to its unique characteristics, VLC is highly sensitive to the line-of-sight (LoS) blockage. Recently, intelligent reflecting surface (IRS) has been proposed as an innovative solution that dynamically reconfigures the wireless environment. The present contribution proposes a two-stage resource management framework in an indoor VLC system: In the first stage, a maximum possible fairness (MPF) algorithm is presented in order to maximize the fairness amongst the users. In the second stage, deep Q-learning is exploited in order to maximize the overall spectral efficiency (SE). The corresponding numerical results have shown that the proposed DQL-MPF framework exhibits superior performance in terms of both the overall SE and Jain's Fair Index, achieved at a fast convergence rate. More specifically, when the noise power is high and the number of users is relatively large, the DQL-MPF algorithm achieves a more than tenfold overall SE compared to the Baseline scheme. Moreover, the synergy between the MPF and the DQL algorithms is investigated. To this end, we demonstrate that the MPF algorithm maximizes the fairness amongst the users while the DQL algorithm maximizes the overall SE and improves the robustness against the noise. Our results also highlight the effectiveness of the proposed algorithm in leveraging the increasing number of IRS elements for optimized performance. © 2023 The Authors.

关键词： Spectrum efficiency

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Recent Advances in In-Memory Computing:Exploring Memristor and Memtransistor Arrays with 2D Materials

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Nano-Micro Letters 2024年第7期16卷 1-30页

作者： Hangbo Zhou Sifan Li Kah-Wee Ang Yong-Wei Zhang Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A*STAR)1 Fusionopolis Way#16-16 ConnexisSingapore 138632Republic of Singapore Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Republic of Singapore Institute of Materials Research and Engineering Agency for ScienceTechnology and Research(A*STAR)2 Fusionopolis WaySingapore 138634Republic of Singapore

The conventional computing architecture faces substantial chal-lenges,including high latency and energy consumption between memory and processing *** response,in-memory computing has emerged as a promising alternative architecture,enabling computing operations within memory arrays to overcome these *** devices have gained significant attention as key components for in-memory computing due to their high-density arrays,rapid response times,and ability to emulate biological *** these devices,two-dimensional(2D)material-based memristor and memtransistor arrays have emerged as particularly promising candidates for next-generation in-memory computing,thanks to their exceptional performance driven by the unique properties of 2D materials,such as layered structures,mechanical flexibility,and the capability to form *** review delves into the state-of-the-art research on 2D material-based memristive arrays,encompassing critical aspects such as material selection,device perfor-mance metrics,array structures,and potential ***,it provides a comprehensive overview of the current challenges and limitations associated with these arrays,along with potential *** primary objective of this review is to serve as a significant milestone in realizing next-generation in-memory computing utilizing 2D materials and bridge the gap from single-device characterization to array-level and system-level implementations of neuromorphic computing,leveraging the potential of 2D material-based memristive devices.

关键词： 2D materials Memristors Memtransistors Crossbar array In-memory computing

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Blockchain and Federated Reinforcement Learning for Vehicle-to-Everything Energy Trading in Smart Grids

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第2期5卷 839-853页

作者： Moniruzzaman, Md Yassine, Abdulsalam Benlamri, Rachid Department of Electrical and Computer Engineering Lakehead University Thunder BayONP7B 5E1 Canada Department of Software Engineering Lakehead University Thunder BayONP7B 5E1 Canada University of Doha for Science and Technology Doha24449 Qatar

The proliferation of electric vehicles (EVs) and the advancement of vehicle-to-everything energy trading systems are expected to play a crucial role in alleviating the stress on the electric grid during peak hours. However, the wide adoption of these paradigms requires intelligent mechanisms that protect the security and privacy of EV users. This article proposes a novel federated reinforcement learning system combined with blockchain technology to maximize EV users' utility while preserving the security and privacy of trading transactions. Furthermore, we develop the concept of proof of state of charge as a consensus mechanism to determine the winning EVs and reward them as block miners in the blockchain. The proposed system is validated through comprehensive simulation experiments utilizing a real-world dataset. The model is implemented on the Avalanche blockchain platform to demonstrate its real-world feasibility. The test results show that the proposed scheme improves EV users' utility significantly compared to the existing studies. The obtained simulation results indicate the effectiveness and robustness of the proposed system. © 2023 IEEE.

关键词： Reinforcement learning

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Multilayer Satellite Network Collaborative Mobile Edge Caching:A GCN-Based Multi-Agent Approach

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China Communications 2024年第11期21卷 56-74页

作者： Yang Jie He Jingchao Cheng Nan Yin Zhisheng Han Dairu Zhou Conghao Sun Ruijin School of Telecommunications Engineering Xidian UniversityXi’an 710071China School of Electronic and Optical Engineering Nanjing University of Science and TechnologyNanjing 210000China Department of Electrical and Computer Engineering University of WaterlooWaterloo ON N2L 3G1Canada

With the explosive growth of highdefinition video streaming data,a substantial increase in network traffic has *** emergency of mobile edge caching(MEC)can not only alleviate the burden on core network,but also significantly improve user *** with the MEC and satellite networks,the network is empowered popular content ubiquitously and *** the research gap between multilayer satellite networks and MEC,we study the caching placement problem in this ***,we introduce a three-layer distributed network caching management architecture designed for efficient and flexible handling of large-scale *** the constraint on satellite capacity and content propagation delay,the cache placement problem is then formulated and transformed into a markov decision process(MDP),where the content coded caching mechanism is utilized to promote the efficiency of content ***,a new generic metric,content delivery cost,is proposed to elaborate the performance of caching decision in large-scale ***,we introduce a graph convolutional network(GCN)-based multi-agent advantage actor-critic(A2C)algorithm to optimize the caching ***,extensive simulations are conducted to evaluate the proposed algorithm in terms of content delivery cost and transferability.

关键词： cache placement coded caching graph convolutional network(GCN) mobile edge caching(MEC) multilayer satellite network

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Eff ect of Annealing on the Temperature Dependence of Resistance in Polyethylene/Carbon Black Composites

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International Journal of the Society of Material engineering for Resources 2022年第1期25卷 51-55页

作者： Tomioka, Masahiro Kumagai, Seiji Department of Mathematical Science and Electrical-Electronic-Computer Engineering Akita University Tegatagakuen-machi 1-1 Akita010-8502 Japan

This study aimed at elucidating the effect of annealing on the positive temperature coefficient characteristics of polyethylene/carbon black (PE/CB) composites. The PE/CB composite was annealed at 140, 150 or 160°C, and the temperature-dependence of its resistance was measured. The internal morphologies of the PE/CB composites with different annealing temperatures were observed using a scanning electron microscope, to verify the optimum annealing conditions for obtaining highly reproducible temperature dependence of resistance. It was shown that the resistance in the PE/CB composite increased with the percentage of inside cracks, which was closely related to the reproducibility of the temperature dependence. Finally, the optimum annealing temperature for the targeted PE/CB composite was estimated to be 150°C. ©2022 Soc. Mater. Eng. Resour. Japan.

关键词： Polyethylenes

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