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Cost-Efficient Deep Neural Network Placement in Edge intelligence-Enabled Internet of Things

ACM Transactions on Sensor Networks 1000年

作者： Hao Tian Xiaolong Xu Hongyue Wu Qingzhan Zhao Jianguo Dai Maqbool Khan State Key Laboratory for Novel Software Technology Nanjing University Nanjing Jiangsu China Nanjing China School of Software Nanjing University of Information Science and Technology Nanjing Jiangsu China Nanjing China College of Intelligence and Computing Tianjin University Tianjin China Tianjin China Geospatial Information Engineering Research Center College of Information Science and Technology Shihezi University Shihezi Xinjiang China Shihezi China Department of IT and Computer Science Pak-Austria Fachhochschule Institute of Applied Sciences and Technology Haripur Pakistan Haripur Pakistan

Edge intelligence (EI) integrates edge computing and artificial intelligence empowering service providers to deploy deep neural networks (DNNs) on edge servers in proximity to users to provision intelligent applications (e.g., autonomous driving) for ubiquitous Internet of Things (IoT) in smart cities, which facilitates the quality of experience (QoE) of users and improves the processing and energy efficiency. However, considering DNN is typically computational-intensive and resource-hungry, conventional placement approaches ignore the influence of multi-dimensional resource requirements (processor, memory, etc.), which may degrade the real-time performance. Moreover, with the increasing scale of geo-distributed edge servers, centralized decision-making is still challenging to find the optimal strategies effectively. To overcome these shortcomings, in this paper we propose a game theoretic DNN placement approach in EI-enabled IoT. First, a DNN placement optimization problem is formulated to maximize system benefits, which is proven to be \(\mathcal {N}\mathcal {P}\)-hard and model the original problem as an exact potential game (EPG). Moreover, an EPG-based DNN model placement algorithm, named EPOL, is designed for edge servers to make sub-optimal strategies independently and theoretical analysis is possessed to guarantee the performance of EPOL. Finally, real-world dataset based experimental results corroborate the superiority and effectiveness of EPOL.

关键词： Edge intelligence DNN placement Game theory Internet of Things

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SRF: SpectrumRecombineFormer for Hyperspectral Image Classification

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ACM Transactions on Multimedia Computing, Communications, and Applications 1000年

作者： Weipeng Jing Peilun Kang Donglin Di Juntao Gu Linhui Li Mahmoud Emam Linda Mohaisen Xun Yang Chao Li College of Computer and Control Engineering Northeast Forestry University China Li Auto China Heilongjiang Cyberspace Research Center China Faculty of Artificial Intelligence Menoufia University Egypt Information Technology Faculty of Computing and Information Technology King Abdulaziz University Saudi Arabia University of Science and Technology of China School of Information Science and Technology China

Hyperspectral (HS) imaging is a valuable technique for accurately classifying materials because of the abundance of spectral information and high resolution it provides. However, the characteristics of Hyperspectral images (HSI), such as high-dimensional features and information redundancy, pose significant challenges to data processing. Traditional dimensionality reduction methods often have information loss, high computational complexity, and easy to ignore the strong correlation between HSI spectral bands when dealing with HSI data. Although other methods can achieve satisfactory classification performance, they do not consider the dimensionality reduction of HSI, and they focus on the model performance, which limits further improvement in classification performance. This paper proposes a transformer-based framework called “SpectrumRecombineFormer” (SRF), which is composed of two key modules, namely “Spatial Spectral ReCombination” (SSRC) and “Cross-layer Fusion” (CF). The SSRC is capable of utilizing both adjacent and non-adjacent spectrums to generate the spatial-sequential perceptive representations, which alleviates the effect of the strong correlation between HSI spectral bands. The CF can avoid the loss of information during the feed-forward procedure among layers. Extensive experiments on five existing datasets (widely-adopted Indian Pines, Houston2013, Pavia University, Salinas and KSC) demonstrate the capability of our proposed method to address the above mentioned challenges. Both quantitative and qualitative experimental ablation studies, including visualization results, reveal that the proposed SRF method can successfully and efficiently classify hyperspectral images and surpass the other state-of-the-art methods. For access to the source code, please visit https://***/kangpeilun/SRF-HSI-Classification-master.

关键词： hyperspectral image classification dimensionality reduction skip fusion swin-transformer remote sensing

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Web 3.0-Enabled Microservice Re-Scheduling for Heterogenous Resources Co-Optimization in Metaverse-Integrated Edge Networks

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ACM Transactions on Autonomous and Adaptive Systems 1000年

作者： Yihong Yang Zhangbing Zhou Lei Shu Feng Zhou Walid Gaaloul Arif Ali Khan School of Information Engineering China University of Geosciences (Beijing) China School of Information Engineering Frontiers Science Center for Deep-time Digital Earth China University of Geosciences (Beijing) China Technology Innovation Center of Geoscience Knowledge and Intelligent Service China Geological Survey China and Computer Science Department TELECOM SudParis France College of Artificial Intelligence Nanjing Agricultural University China National Geological Library of China China Computer Science Department TELECOM SudParis France M3S Empirical Software Engineering Research Unit University of Oulu Finland

The Web 3.0 and metaverse can empower intelligent application of Connected Autonomous Vehicles (CAVs). The adoption of edge computing can contribute to the low latency interaction between CAVs and the metaverse. Microservices are widely deployed on edge networks and the cloud nowadays. User's requests from CAVs are typically fulfilled through the composition of microservices, which may be hosted by contiguous edge nodes. Requests may differ on their required resources at runtime. Consequently, when requests are continuously injected into edge networks, the usage of heterogenous resources, including CPU, memory, and network bandwidth, may not be the same, or differ significantly, on certain edge nodes. This happens especially when burst requests are injected into the network to be satisfied concurrently. Therefore, the usage of heterogenous resources provided by edge nodes should be co-optimized through re-scheduling microservices. To address this challenge, this paper proposes a Web 3.0-enabled Microservice Re-Scheduling approach (called MRS), which is a migration-based mechanism integrating a placement strategy. Specifically, we formulate the microservice re-scheduling task as a multi-objective and multi-constraint optimization problem, which can be solved through a penalty signal-integrated framework and an improved pointer network. Extensive experiments are conducted on two real-world datasets. Evaluation results show that our MRS performs better than the counterparts with improvements of at least 7.7%, 2.4% and 2.2% in terms of network throughput, latency and energy consumption.

关键词： Web 3.0 Microservice Re-Scheduling Heterogenous Resources Co-Optimization Metaverse Connected Autonomous Vehicles (CAVs)

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Intelligent Computing and Optimization 1

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丛书名： Lecture Notes in Networks and Systems

1000年

作者： Pandian Vasant Mohammad Shamsul Arefin Vladimir Panchenko J. Joshua Thomas Elias Munapo Gerhard-Wilhelm Weber Roman Rodriguez-Aguilar

ISBN: (数字)9783031501517

ISBN: (纸本)9783031501500

The 6th edition of International Conference on Intelligent Computing and Optimization took place at G Hua Hin Resort & Mall on April 27–28, 2023, with tremendous support from the global research scholars across the planet. Objective is to celebrate “Research Novelty with Compassion and Wisdom” with researchers, scholars, experts, and investigators in Intelligent Computing and Optimization across the globe, to share knowledge, experience, and innovation—a marvelous opportunity for discourse and mutuality by novel research, invention, and creativity. This proceedings book of the 6th ICO’2023 is published by Springer Nature—Quality Label of Enlightenment.

关键词： Computational intelligence Artificial intelligence

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Advances in Web Mining and Web Usage Analysis 1

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丛书名： Lecture Notes in computer science

1000年

作者： Bamshad Mobasher Olfa Nasraoui Bing Liu Brij Masand

ISBN: (数字)9783540471288

ISBN: (纸本)9783540471271

TheWebisaliveenvironmentthatmanagesanddrivesawidespectrumofapp- cations in which a user may interact with a company, a governmental authority, a non-governmental organization or other non-pro?t institution or other users. User preferences and expectations, together with usage patterns, form the basis for personalized, user-friendly and business-optimal services. Key Web business metrics enabled by proper data capture and processing are essential to run an e?ective business or service. Enabling technologies include data mining, sc- able warehousing and preprocessing, sequence discovery, real time processing, document classi?cation, user modeling and quality evaluation models for them. Recipient technologies required for user pro?ling and usage patterns include recommendation systems, Web analytics applications, and application servers, coupled with content management systems and fraud detectors. Furthermore, the inherent and increasing heterogeneity of the Web has - quired Web-based applications to more e?ectively integrate a variety of types of data across multiple channels and from di?erent sources. The development and application of Web mining techniques in the context of Web content, Web usage, and Web structure data has already resulted in dramatic improvements in a variety of Web applications, from search engines, Web agents, and content management systems, to Web analytics and personalization services. A focus on techniques and architectures for more e?ective integration and mining of c- tent, usage,and structure data from di?erent sourcesis likely to leadto the next generation of more useful and more intelligent applications.

关键词： Artificial intelligence computer Communication Networks Database Management Information Storage and Retrieval Information Systems Applications (incl. Internet) computers and Society

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Applications of Evolutionary Computing 1

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丛书名： Lecture Notes in computer science

1000年

作者： Mario Giacobini Anthony Brabazon Stefano Cagnoni Gianni A. Caro Anikó Ekárt Anna Isabel Esparcia-Alcázar Muddassar Farooq Andreas Fink Penousal Machado

ISBN: (数字)9783642011290

ISBN: (纸本)9783642011283

The year 2009 celebrates the bicentenary of Darwin’s birth and the 150th - niversary of the publication of his seminal work, On the Origin of *** this makes 2009 a special year for the research community working in biology and evolution, the ?eld of evolutionary computation (EC) also shares the same excitement. EC techniques are e?cient, nature-inspired planning and optimi- tion methods based on the principles of natural evolution and genetics. Due to their e?ciency and simple underlying principles, these methods can be used in the context of problem solving, optimization, and machine learning. A large and ever-increasing number of researchers and professionals make use of EC te- niques in various application domains. ThisvolumepresentsacarefulselectionofrelevantECapplicationscombined with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and can help and inspire researchers and professionals to develop e?cient EC methods for design and problem solving.

关键词： Programming Techniques computer Communication Networks Theory of Computation Computation by Abstract Devices computer Hardware Math Applications in computer science

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Modeling Infectious Disease Epidemics in Mass Religious Gatherings: A Systematic Review

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ACM Transactions on Modeling and computer Simulation 1000年

作者： Sultanah Alshammari Mohammed Ba-Aoum Nofe Alganmi Ahmad Showail Center of Research Excellence in Artificial Intelligence and Data Science King Abdulaziz University Jeddah Saudi Arabia Department of Computer Science King Abdulaziz University Jeddah Saudi Arabia Industrial and Systems Engineering Department King Fahd University of Petroleum and Minerals College of Sciences Dhahran Saudi Arabia Department of Computer Engineering Taibah University Madinah Saudi Arabia

Like other global mass gatherings, religious pilgrimages, such as Hajj, Arba’een, and the Hindu festival Kumbh Mela, attract millions of pilgrims to gather at specific holy sites on specific dates. During disease pandemics, mass gatherings can become super spreader events, causing exponential growth of infections in multiple regions. Epidemic modeling approaches can be valuable tools for studying the impact of mass gatherings on global health during disease outbreaks. To assess the use of epidemic models at religious pilgrimages, we compile published studies that proposed epidemic models at mass religious gatherings. A review of existing epidemic models at various religious gatherings highlights the role of epidemic modeling approaches in assessing the implications of religious pilgrimages on disease pandemics. All the articles surveyed showed a link between hosting religious gatherings and an increase in the number of cases of the simulated epidemic. In addition, we found that the SEIR mathematical model was the most common type developed with variations in some of the retrieved papers. The results reported in these studies motivate further investigation of the role of epidemic modeling and simulation in estimating the size and geographic scale of infections while hosting religious gatherings. Finally, we believe that this survey paper draws attention to the application of epidemic models in the advanced planning of recurrent religious pilgrimages, as it is not feasible to cancel, suspend, or reallocate these pilgrimages. These epidemic models can provide a baseline for policymakers to determine which control measures should be implemented and when.

关键词： infectious diseases epidemics pandemics mathematical models agent-based models mass gatherings religious gatherings

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Secure Collaborative Learning for Self-Adaptive Systems on Connected Autonomous Vehicles

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ACM Transactions on Autonomous and Adaptive Systems 1000年

作者： Xiaotong Wu Yuwen Liu Xiaoxiao Chi Rong Jiang Xiaokang Zhou Wajid Rafique Maqbool Khan Alibaba Business School Hangzhou Normal University China College of Computer Science and Technology China University of Petroleum (East China) China Department of Computing Macquarie University Australia Yunnan Key Laboratory of Service Computing Yunnan University of Finance and Economics China Faculty of Business Data Science Kansai University Japan and RIKEN Center for Advanced Intelligence Project Japan Department of Electrical and Software Engineering University of Calgary Canada Software Competence Center Hagenberg Austria

As an advanced carrier of on-board sensors, connected autonomous vehicle (CAV) can be viewed as an aggregation of self-adaptive systems with monitor-analyze-plan-execute (MAPE) for vehicle-related services. Meanwhile, machine learning (ML) has been applied to enhance analysis and plan functions of MAPE so that self-adaptive systems have optimal adaption to changing conditions. However, most of ML-based approaches don’t utilize CAVs’ connectivity to collaboratively generate an optimal learner for MAPE, because of sensor data threatened by gradient leakage attack (GLA). In this article, we first design an intelligent architecture for MAPE-based self-adaptive systems on Web 3.0-based CAVs, in which a collaborative machine learner supports the capabilities of managing systems. Then, we observe by practical experiments that importance sampling of sparse vector technique (SVT) approaches cannot defend GLA well. Next, we propose a fine-grained SVT approach to secure the learner in MAPE-based self-adaptive systems, that uses layer and gradient sampling to select uniform and important gradients. At last, extensive experiments show that our private learner spends a slight utility cost for MAPE (e.g., \(0.77\%\) decrease in accuracy) defending GLA and outperforms the typical SVT approaches in terms of defense (increased by \(10\%\sim 14\%\) attack success rate) and utility (decreased by \(1.29\%\) accuracy loss).

关键词： collaborative learning optimal adaption vehicle application data security self-adaptive system

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Intelligent Computing and Optimization 1

引用

丛书名： Lecture Notes in Networks and Systems

1000年

作者： Pandian Vasant Mohammad Shamsul Arefin Vladimir Panchenko J. Joshua Thomas Elias Munapo Gerhard-Wilhelm Weber Roman Rodriguez-Aguilar

ISBN: (数字)9783031503306

ISBN: (纸本)9783031503290

The 6th edition of International Conference on Intelligent Computing and Optimization took place at G Hua Hin Resort & Mall on April 27–28, 2023, with tremendous support from the global research scholars across the planet. Objective is to celebrate “Research Novelty with Compassion and Wisdom” with researchers, scholars, experts, and investigators in Intelligent Computing and Optimization across the globe, to share knowledge, experience, and innovation—a marvelous opportunity for discourse and mutuality by novel research, invention, and creativity.;This proceedings book of the 6th ICO’2023 is published by Springer Nature—Quality Label of Enlightenment.

关键词： Computational intelligence Artificial intelligence

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Applications of Evolutionary Computation 1

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丛书名： Lecture Notes in computer science

1000年

作者： Cecilia Chio Alexandros Agapitos Stefano Cagnoni Carlos Cotta Francisco Fernández Vega Gianni A. Caro Rolf Drechsler Anikó Ekárt Anna I. Esparcia-Alcázar Muddassar Farooq William B. Langdon Juan J. Merelo-Guervós Mike Preuss Hendrik Richter Sara Silva Anabela Simões Giovanni Squillero Ernesto Tarantino Andrea G. B. Tettamanzi Julian Togelius Neil Urquhart A. Şima Uyar Georgios N. Yannakakis

ISBN: (数字)9783642291784

ISBN: (纸本)9783642291777

This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* 2012 events EuroGP, EvoCOP, EvoBIO, and EvoMUSART. The 54 revised full papers presented were carefully reviewed and selected from 90 submissions. EvoApplications 2012 consisted of the following 11 tracks: EvoCOMNET (nature-inspired techniques for telecommunication networks and other parrallel and distributed systems), EvoCOMPLEX (algorithms and complex systems), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoHOT (bio-inspired heuristics for design automation), EvoIASP (evolutionary computation in image analysis and signal processing), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defense applications), EvoSTIM (nature-inspired techniques in scheduling, planning, and timetabling), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

关键词： Computation by Abstract Devices Programming Techniques computer Communication Networks Math Applications in computer science Image Processing and computer Vision Artificial intelligence

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