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A Trusted and Decentralized Federated Learning Framework for IoT devices in Smart City

A Trusted and Decentralized Federated Learning Framework for...

IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom)

作者： Sheng Wang Chun Chen Bing Han Jun Zhu Nanjing Construction Market Supervision Station Nanjing China Jiangsu Public Works Co.Ltd Nanjing China Department of College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Department of Architecture and Civil Engineering City University of Hong Kong China

ISBN: (数字)9798350351637

ISBN: (纸本)9798350351644

Smart cities, through investment in human and social capital as well as traditional and modern communications infrastructure, drive sustainable economic growth and high quality of life. IoT devices, as crucial components of smart cities, leverage the Federated Learning (FL) paradigm to contribute significantly to the advancement of smart cities by providing the value of data while safeguarding local data. However, existing federated learning frameworks for smart cities face several issues, including excessive centralization of decision-making and data, unbalanced resource allocation, and security and privacy concerns. To address these challenges, This paper aims to propose a blockchain-based federated learning framework for IoT devices in smart cities. We combine multiple security and privacy-preserving techniques such as differential privacy and Trusted Execution Environments (TEE) with federated learning to establish a framework that facilitates secure and trustworthy data exchange and FL requirements for IoT devices in smart cities. Moreover, we offload the local training computation from the limited IoT devices to the edge server and execute trust aggregation on the blockchain smart contracts. We build a prototype of our designed system and conduct experiments on diverse federated learning datasets. Experimental results demonstrate that our scheme achieves high efficiency while ensuring security and privacy. Through this work, we provide a viable solution for federated learning in smart cities, thereby advancing the sustainable development and intelligence of smart cities.

关键词： Training Social computing Smart cities Federated learning Smart contracts Internet of Things Security Servers Resource management Sustainable development

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Optimized Model Predictive Control for Unmanned Aerial Vehicles with Sensor Uncertainties

Optimized Model Predictive Control for Unmanned Aerial Vehic...

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2022 International Conference on Control, Automation and Diagnosis, ICCAD 2022

作者： Taher Azar, Ahmad Serrano, Fernando E. Ahmad Kamal, Nashwa Qureshi, Basit Al Mhdawi, Ammar K. Humaidi, Amjad J. Kasim Ibraheem, Ibraheem Ben Njima, Chakib Prince Sultan University College of Computer and Information Sciences Riyadh Saudi Arabia Benha University Faculty of Computers and Artificial Intelligence Benha Egypt Faculty of Engineering and Architecture Tegucigalpa Honduras Cairo University Faculty of Engineering Egypt Hill University United Kingdom University of Technology Control and Systems Engineering Department Baghdad Iraq Dijlah University College Department of Computer Techniques Engineering Baghdad10001 Iraq University of Sousse Tunisia

ISBN: (数字)9781665497947

ISBN: (纸本)9781665497947

In this paper, a novel control strategy based on model predictive control is proposed for tracking the trajectory of unmanned aerial vehicles (UAV). First, the dynamic model of an unmanned aerial vehicle UAV is established by considering the linear velocities in terms of the analyzed system's attitude angles. The UAV's dynamic model is suitable for kinematic control by using two attitude angles as control inputs. The controller design is made up of an output feedback controller formed by the error variables, which are the difference between the measured output and the reference variables. Then, a model predictive control is established by considering an optimization problem with a performance index and the corresponding constraints. Furthermore, the stochastic properties of the UAV dynamic model are taken into account in this research study. The measured outputs provided by the sensors are constrained by the topological characteristics of the unmanned aerial vehicle to be analyzed. Finally, a numerical experiment and its conclusions are presented, demonstrating that the proposed control strategy provides optimal trajectory tracking. © 2022 IEEE.

关键词： Model predictive control

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A Critical Analysis on the Application of Next-Generation Internet of Things (Iot) for Building Efficient Energy Systems for Improved Temperature Control and Better Energy Consumption 2nd

A Critical Analysis on the Application of Next-Generation In...

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2nd International Conference on Mechanical and Energy Technologies , ICMET 2021

作者： Veeraiah, Vivek Shaikh, Naim Narasima Venkatesh, A. Thailand, Korakod Kousalyadevi, G. Shanmugasundaram, V. Department of R&D Computer Science Adichunchanagiri University Karnataka Mandya India Global Business School and Research Centre Dr. D.Y. Patil Vidyapeeth Pune Tathawade India MBA-Department of Human Resource Management RV Institute of Management Karnataka Bangalore India Faculty of Law Thaksin University Muang Songkhla District Thailand Department of Architecture Mohamed Sathak Engineering College Kilakarai India Department of Electrical and Electronics Engineering Sona College of Technology Tamil Nadu Salem636005 India

ISBN: (纸本)9789811901072

This research article is focused on analyzing the application of next-generation Internet of Things (IoT) in creating energy-efficient systems so as to improvise the temperature and manage the energy consumption effectively. The term IoT is a new concept that has been growing imminently due to growing needs and requirements of government, individuals, corporations, etc. The IoT is mainly stated as a critical system of computing machines that possess better and enhanced connection so as to automate various aspects of the routine needs of the individuals, it also assists in creating better information approach for evaluation and implementation of different approaches for sustainable living. The IoT system connects the different smart devices and senses through cloud-based controllers, the sensors in the building can enable in collecting and transmitting the real-time data on the environment, this information is then used by the controller’s team to offer quick responses on the temperature control ana management. The systems enable in applying predictive and adaptive algorithms which will enable in executing the real-time operational responses, like turning on or switching off the lights based on the signals from in-room occupancy and turning on the air conditioning based on the level of occupancy in the building, this enables in optimizing the heating, ventilation and air-conditioning system so as to enhance better energy consumption. This article presents a critical analysis of the usage of IoT in enhancing the energy-efficient system in the building for improved temperature control and enhanced energy consumption. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Energy efficiency

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Coupled Swmm-Moea/D for Multi-Objective Optimization of Low Impact Development in Urban Stormwater Systems

SSRN

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SSRN 2024年

作者： Javan, Kazem Nazari, Amirhossein Roozbahani, Abbas Darestani, Mariam Hossieni, Hanieh Banihashemi, Saeed The Department of Civil and Environmental Engineering Western Sydney University Australia Faculty of Agricultural Technology College of Agriculture and Natural Resources University of Tehran Tehran Iran Ås Norway The Department of Computer and Electrical Engineering Sistan and Baluchestan University Iran School of Built Environment Faculty of Design Architecture and Building University of Technology Sydney Australia Tehran University Iran

The escalating challenge of unsustainable urban development worldwide has precipitated changes in land usage, contributing to increased impermeability of the urban landscape. This phenomenon exacerbates urban runoff, a critical environmental concern. In response, Low Impact Development (LID) techniques, recognized for their environmental efficacy, have emerged as pivotal in mitigating urban runoff. However, transforming the hydrological dynamics of urban watersheds into a more sustainable state necessitates substantial financial commitments from relevant authorities. Consequently, strategic LID planning becomes essential to maximize effectiveness while minimizing costs. This research introduces a novel, hybrid modeling strategy that integrates the Storm Water Management Model (SWMM) with the MOEA/D optimization algorithm. This approach aims to concurrently minimize runoff volume, peak flow rate, and implementation expenses. Focusing on a segment of Tehran Municipality's urban stormwater system in District 11, the study evaluates four distinct LID scenarios. These scenarios encompass various configurations of rain barrels (RB), bioretention cells (BC), green roofs (GR), and porous pavements (PP). Utilizing the TOPSIS method for comparative analysis, the study results identify the most efficacious scenario, S2_1, including RB and BC, which achieves a 19.34% reduction in runoff volume and a 46.53% decrease in peak flow rate, all at the implementation cost of 123,169 US$. A close second, scenario S3_1 incorporating RB and PP, demonstrates a 17% and 46.55% reduction in runoff volume and peak flow at an expenditure of 107,017 US$, respectively. The proposed SWMM-MOEA/D model, in conjunction with TOPSIS, presents a valuable tool for LID planning and optimization, offering decision-makers and relevant entities a pragmatic approach to address the challenges of urban runoff management. © 2024, The Authors. All rights reserved.

关键词： Multiobjective optimization

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A New Belief-Based Incomplete Pattern Unsupervised Classification Method : Extended Abstract

A New Belief-Based Incomplete Pattern Unsupervised Classific...

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International Conference on Data Engineering

作者： Zuowei Zhang Zhe Liu Zongfang Ma Yiru Zhang Hao Wang Institut de Recherche en Informatique et Systèmes Aléatoires University of Rennes 1 France School of Information and Control Engineering Xi’an University of Architecture and Technology China Department of Computer Science Norwegian University of Science and Technology Norway

Imputing the incomplete patterns in clustering tasks is a common but risky procedure, because the estimated values may affect the real distribution of the data and deteriorate the results. To address this problem, a new belief-based incomplete pattern unsupervised classification method (BPC) with uncertainty and imprecision reasoning is proposed in this paper. First, the complete patterns are grouped into a few clusters to obtain the corresponding reliable centers, and thereby are divided into reliable patterns and unreliable ones by an optimization method. Second, a basic classifier trained by reliable patterns is employed to classify unreliable patterns and incomplete patterns edited by the neighbors. Finally, some imprecise patterns are carefully reassigned again by a new distance-based rule depending on the obtained reliable centers and belief functions theory. The simulation results show that the BPC has the potential to deal with real datasets.

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A Spatio-Temporal Switchable Data Prefetcher for Convolutional Neural Networks

A Spatio-Temporal Switchable Data Prefetcher for Convolution...

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International SoC Design Conference, ISOCC

作者： Jihoon Jang Hyun Kim Hyokeun Lee Department of Electrical and Information Engineering Research Center for Electrical and Information Technology Seoul National University of Science and Technology Seoul Korea Secure and Advanced Computer Architecture (SACA) Research Group North Carolina State University (NCSU) Raleigh NC USA

In this paper, we propose a spatio-temporal switchable data prefetcher that can adapt to the locality characteristics of CNN models. The proposed prefetcher records the recent delta history by leveraging two tables. The first table predicts spatial address patterns by comparing the delta score with the last delta, while the second table predicts temporal address patterns by recording and reordering the delta sequence from the delta history. Consequently, the proposed prefetcher is capable of appropriately switching between these two prediction methodologies based on spatial and temporal localities. The experimental results on CNN inference workloads show that we achieved high average accuracy of 83.8% and coverage of 81.6%, and hence the proposed prefetcher improves system performance by 33.8% over a baseline with no data prefetcher and 21% over the best-performing prior spatio-temporal prefetcher.

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Event Graphs: Syntax, Semantics, and Implementation

Event Graphs: Syntax, Semantics, and Implementation

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2023 Winter Simulation Conference, WSC 2023

作者： Gunal, Murat M. Ismail Osais, Yahya Wagner, Gerd Fenerbahce University Faculty of Engineering and Architecture Atatürk Mah. Ataşehir Bulvari Istanbul Ataşehir34758 Turkey Center for Intelligent Secure Systems King Fahd University of Petroleum and Minerals Computer Engineering Department P.O. Box 2244 Dhahran31261 Saudi Arabia Brandenburg University of Technology Konrad-Wachsmann-Allee 5 Cottbus03046 Germany

ISBN: (纸本)9798350369663

This tutorial aims to introduce Event Graphs (EGs), invented 40 years ago by Lee Schruben to allow eventbased modeling of discrete dynamic systems. Their simplicity and naturalness in causality modelling and simulation modelling made EGs popular in research and practice. In a simulation, an event causes state changes in a system as well as other events to happen in the future. EGs provide a parsimonious diagram representation for the Event Scheduling paradigm of Discrete Event Simulation. We first introduce their visual syntax and informal semantics, and then present a recent extension by adding objects to EGs. Our tutorial also includes an introduction to the formal semantics of EGs and a Python implementation for executing EGs. © 2023 IEEE.

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Modified ARQ-based cooperative relaying scheme for a delay tolerant network

Modified ARQ-based cooperative relaying scheme for a delay t...

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2021 IEEE International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2021

作者： Otaru, Musa Adinoyi, Abdulkareem Ajiya, Mohammed Aljlayl, Mohammed Yanikomeroglu, Halim Bayero University Kano Department of Electrical Engineering Nigeria Technology Strategy Architecture Saudi Telecommunications Company Saudi Arabia Carleton University Dept. of Systems and Computer Engineering Ottawa Canada

ISBN: (纸本)9781665412629

We use fixed relays deployed by network operators to reduce re-transmission (thereby reducing network power requirements) in addition to providing excellent end-to-end error performance in a revisit to automatic repeat request-based cooperative relaying. The new relaying scheme facilitates the creation of a connectivity suitable for delay tolerant internet-of-things (IoT)-type services. For IoT devices, link reliability and power efficiency are a major system design consideration. The proposed scheme operates in the following fashion. The source (e.g., a sensor) transmits for a certain time window. During this period, the source and the relays do not require per transmission acknowledgment (ACK) from the destination. At the end of a transmission window, the destination sends a 'group' ACK. If negative, relays are invited to help. Depending on the cooperation strategy, each relay transmits in either one transmission time slot or a few time slots, using a suitably chosen higher-order modulation constellation. If no error occurs, the source continues its transmission. Furthermore, we devise a novel strategy for selecting the best relay for this new way of exploiting the benefits of multiple relays in a network. In the process, we reclaim the bandwidth expansion that comes with multi-relay system but still maintaining E2E bit error rate that is superior to that of a single relay cooperation. Numerical results that reveal the benefits of the new and modified ARQ cooperative relaying scheme are presented. © 2021 IEEE.

关键词： Energy efficiency

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Irreversibility analysis of magnetized flow of engine oil hybrid nanofluid (Ti6Al4V-ZnO/EO) over a stretching surface

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Alexandria Engineering Journal 2025年 127卷 214-227页

作者： Hussain, Syed M. Faridi, Aftab Ahmed Ahmad, Hijaz Ali, Kashif Iqbal, Muhammad Rashid Jamshed, Wasim Guedri, Kamel Almaliki, Abdulrazak H. Department of Mathematics Faculty of Science Islamic University of Madinah Madinah42351 Saudi Arabia Department of Mathematics The Islamia University of Bahawalpur Bahawalpur63100 Pakistan Near East University Operational Research Center in Healthcare TRNC Mersin 10 Nicosia99138 Turkey Department of Technical Sciences Western Caspian University Baku1001 Azerbaijan Department of Mathematics College of Science Korea University 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of Department of Basic Sciences and Humanities Muhammad Nawaz Sharif University of Engineering and Technology Multan60000 Pakistan Department of Mathematics and Statistics Institute of Southern Punjab Multan32100 Pakistan Islamabad44000 Pakistan College of Engineering Al-Ayen Iraqi University An Nasiriyah64001 Iraq Department of Computer Engineering Biruni University Topkapi Istanbul Turkey Mechanical Engineering Department College of Engineering and Architecture Umm Al-Qura University P. O. Box 5555 Makkah21955 Saudi Arabia Department of Civil Engineering college of Engineering Taif University Taif21944 Saudi Arabia

This article analyzes the irreversibility of hydro-magnetic dynamics of hybridized nanofluid comprising of titanium alloy (Ti6Al4V) and zinc-oxide (ZnO) submerged into engine oil (used as a fuel) through a porous stretching sheet with multipart effects of viscous dissipation and non-uniform heat source. An induced magnetic field exists in the flow field due to the conducting nature of the hybrid nanofluid. The equations of the flow model are transformed by the similarity transformations and then simulated through a numerical scheme constructed with a formulation of central differences that adopts successive over-relaxation methodology. In this thermodynamic system, entropy and Bejan number profiles corresponding to the prominent parameters are simultaneously analysed for both the nanofluid case and hybrid nanofluid case in the Cartesian coordinates. A comparison table is constructed to validate the numerical results with existing literature. The impacts of various parameters on Nusselt number and skin friction coefficient are graphed with reference to the magnetic field parameter. A significant reduction in irreversibility and a remarkable improvement in thermal characteristics of engine oil are observed due to induced magnetism effects. The engine oil hybrid nanofluid (Ti6Al4V-ZnO/EO) exhibits a 13.89 % higher heat transfer rate over a porous stretching surface compared to the engine oil nanofluid (Ti6Al4V/EO). © 2025 The Authors

关键词： Magnetic levitation

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Low-power emerging memristive designs towards secure hardware systems for applications in internet of things

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Nano Materials Science 2021年第2期3卷 186-204页

作者： Nan Du Heidemarie Schmidt Ilia Polian Department Nano Device Technology Fraunhofer Institute for Electronic Nano SystemsTechnologie-Campus 309126ChemnitzGermany Faculty of Electrical Engineering and Information Technology Chemnitz University of Technology(TU Chemnitz)Straße der Nationen 6209126ChemnitzGermany Department of Quantum Detection Leibniz Institute of Photonic Technology(IPHT)Albert-Einstein-Str.907745JenaGermany Institute for Solid State Physics Friedrich Schiller University JenaFürstengraben 107743JenaGermany Institute of Computer Engineering and Computer Architecture(ITI) University of StuttgartPfaffenwaldring 4770569StuttgartGermany

Emerging memristive devices offer enormous advantages for applications such as non-volatile memories and inmemory computing(IMC),but there is a rising interest in using memristive technologies for security applications in the era of internet of things(IoT).In this review article,for achieving secure hardware systems in IoT,lowpower design techniques based on emerging memristive technology for hardware security primitives/systems are *** reviewing the state-of-the-art in three highlighted memristive application areas,*** non-volatile memory,memristive reconfigurable logic computing and memristive artificial intelligent computing,their application-level impacts on the novel implementations of secret key generation,crypto functions and machine learning attacks are explored,*** the low-power security applications in IoT,it is essential to understand how to best realize cryptographic circuitry using memristive circuitries,and to assess the implications of memristive crypto implementations on security and to develop novel computing paradigms that will enhance their *** review article aims to help researchers to explore security solutions,to analyze new possible threats and to develop corresponding protections for the secure hardware systems based on low-cost memristive circuit designs.

关键词： Memristive technology Nanoelectronic device Low-power consumption Miniaturization Nonvolatility Reconfigurability In memory computing Artificial intelligence Hardware security primitives Machine learning-related attacks and defenses

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