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Incentive-Driven Computation Task Allocation for Integrated Edge Computing and Energy Feeding

IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Zhang, Biling Liu, Jiahua Jiao, Zhengyang Wang, Yunpeng Guo, Caili Han, Zhu Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing100876 China China Merchants Securities co. Ltd Shenzhen518026 China State Grid Corporation of China Beijing Electric Power Company Beijing100192 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

This paper considers a novel scenario where the service provider encounters an insufficiency of computation and energy resources simultaneously. To complete the task on time, the service provider has to perform partial computation offloading and energy fetching, exploiting the idle resources of nearby edge nodes. However, computation offloading and energy fetching incur costs which are interdependent. On the other hand, the edge nodes are selfish and need an incentive, but the information between the service provider and the edge nodes is asymmetric. Therefore, how to offload the task and fetch energy while stimulating the edge nodes is a challenge. To minimize the expenditure of service provider, we investigate the task allocation problem where the incentive problem is evolved and formulated with contract theory. Noticing that the task allocation problem and the incentive problem are interdependent and cannot be solved through traditional optimization approaches, we decouple the problems and first theoretically derive the expression of feasible contracts for the given allocation scheme. Then we propose a low complexity sparrow algorithm to find the suboptimal solution to the task allocation problem, with which the desired contracts are obtained. Simulations show that the proposed scheme achieves superior performance in terms of total expenditure, potential computing resource and grid power reduction. © 2015 IEEE.

关键词： Computation offloading

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A Survey on Small Sample Imbalance Problem: Metrics, Feature Analysis, and Solutions

arXiv

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arXiv 2025年

作者： Zhao, Shuxian Gui, Jie Dong, Minjing Yu, Baosheng Gui, Zhipeng Dong, Lu Tang, Yuan Yan Kwok, James Tin-Yau School of Cyber Science d Engineering Southeast University Nanjing210000 China School of Cyber Science and Engineering Southeast University Nanjing211189 China Engineering Research Center of Blockchain Application Supervision and Management Southeast University Nanjing211189 China Purple Mountain Laboratories Nanjing210000 China Department of Computer Science City University of Hong Kong Hong Kong Lee Kong Chian School of Medicine Nanyang Technological University Singapore School of Remote Sensing and Information Engineering Wuhan University Wuhan430079 China Collaborative Innovation Center of Geospatial Technology Wuhan University Wuhan430079 China Department of Computer and Information Science University of Macau China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong

—The small sample imbalance (S&I) problem is a major challenge in machine learning and data analysis. It is characterized by a small number of samples and an imbalanced class distribution, which leads to poor model performance. In addition, indistinct inter-class feature distributions further complicate classification tasks. Existing methods often rely on algorithmic heuristics without sufficiently analyzing the underlying data characteristics. We argue that a detailed analysis from the data perspective is essential before developing an appropriate solution. Therefore, this paper proposes a systematic analytical framework for the S&I problem. We first summarize imbalance metrics and complexity analysis methods, highlighting the need for interpretable benchmarks to characterize S&I problems. Second, we review recent solutions for conventional, complexity-based, and extreme S&I problems, revealing methodological differences in handling various data distributions. Our summary finds that resampling remains a widely adopted solution. However, we conduct experiments on binary and multiclass datasets, revealing that classifier performance differences significantly exceed the improvements achieved through resampling. Finally, this paper highlights open questions and discusses future trends. Copyright © 2025, The Authors. All rights reserved.

关键词： Taxonomies

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Tumor Synthesis Conditioned on Radiomics

Tumor Synthesis Conditioned on Radiomics

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IEEE Workshop on Applications of computer Vision (WACV)

作者： Jonghun Kim Inye Na Eun Sook Ko Hyunjin Park Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Department of Radiology and Center for Imaging Science Samsung Medical Center Sungkyunkwan University School of Medicine Suwon Korea

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Due to privacy concerns, obtaining large datasets is challenging in medical image analysis, especially with 3D modalities like Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Existing generative models, developed to address this issue, often face limitations in output diversity and thus cannot accurately represent 3D medical images. We propose a tumor-generation model that utilizes radiomics features as generative conditions. Radiomics features are high-dimensional handcrafted semantic features that are biologically well-grounded and thus are good candidates for conditioning. Our model employs a GAN-based model to generate tumor masks and a diffusion-based approach to generate tumor texture conditioned on radiomics features. Our method allows the user to generate tumor images according to user-specified radiomics features such as size, shape, and texture at an arbitrary location. This enables the physicians to easily visualize tumor images to better understand tumors according to changing radiomics features. Our approach allows for the removal, manipulation, and repositioning of tumors, generating various tumor types in different scenarios. The model has been tested on tumors in four different organs (kidney, lung, breast, and brain) across CT and MRI. The synthesized images are shown to effectively aid in training for downstream tasks and their authenticity was also evaluated through expert evaluations. Our method has potential usage in treatment planning with diverse synthesized tumors. Our code is available at ***/jongdoryITS-Radiomics.

关键词： Training Three-dimensional displays Biological system modeling Magnetic resonance imaging Computed tomography Computational modeling Biological information theory Tumors Radiomics Biomedical imaging

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Efficient Chroma Intra Prediction via Exemplar Colorization Network for Versatile Video Coding

引用

IEEE Transactions on Multimedia 2025年

作者： Pan, Zhaoqing Chen, Jixing Peng, Bo Lei, Jianjun Wang, Fu Lee Ling, Nam Kwong, Sam Tianjin University School of Electrical and Information Engineering Tianjin300072 China Hong Kong Metropolitan University School of Science and Technology Hong Kong Hong Kong Santa Clara University Department of Computer Science and Engineering Santa ClaraCA95053 United States Lingnan University School of Data Science Hong Kong Hong Kong

Chroma intra prediction aims to reduce chroma redundancies within a frame, which plays an important role in improving the coding efficiency of intra coding. Existing chroma intra prediction methods typically utilize the spatial relationship between the current luma block and its neighboring reference luma blocks to predict its chroma samples. However, the spatial properties of luma components differ from those of chroma components, which limits the accuracy of chroma intra prediction. To tackle this issue, an efficient Exemplar Colorization Network (ECNet)-based chroma intra prediction method is proposed in this paper, in which the colorization relationship between reference luma and chroma components is exploited to predict the chroma components for the current luma component. Inspired by the principle that semantic information in an image exhibits short-range continuity, a Spatial-consistency-based Colorization Transfer Network (SCTNet) is proposed, which builds and transfers colorization representations of neighboring reference blocks for chroma prediction. To improve the chroma prediction capability of SCTNet, a colorization learning module is developed to learn the robust mapping relationship from the luma component to the chroma component in a region-to-pixel manner, and a weight-adaptive reconstruction module is designed to adaptively utilize reference information from neighboring blocks to generate an initial prediction result. In addition, to further improve the accuracy of chroma intra prediction, a multi-reference-based chroma refinement network is proposed, which simultaneously uses the spatial information of neighboring reference chroma blocks and the current luma block to eliminate blocking and color-bleeding artifacts in the initial prediction result. Experimental results demonstrate that our proposed ECNet outperforms the state-of-the-art chroma intra prediction methods in terms of coding performance. © 1999-2012 IEEE.

关键词： Video signal processing

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Data-Driven Nonconvex Reachability Analysis using Exact Multiplication

arXiv

引用

arXiv 2025年

作者： Zhang, Zhen Niazi, M. Umar B Chong, Michelle S. Johansson, Karl H. Alanwar, Amr School of Computation Information and Technology Technical University of Munich Germany Division of Decision and Control Systems Digital Futures School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Mechanical Engineering Eindhoven University of Technology Netherlands

This paper addresses a fundamental challenge in data-driven reachability analysis: accurately representing and propagating non-convex reachable sets. We propose a novel approach using constrained polynomial zonotopes to describe reachable sets for unknown LTI systems. Unlike constrained zonotopes commonly used in existing literature, constrained polynomial zonotopes are closed under multiplication with constrained matrix zonotopes. We leverage this property to develop an exact multiplication method that preserves the non-convex geometry of reachable sets without resorting to approximations. We demonstrate that our approach provides tighter over-approximations of reachable sets for LTI systems compared to conventional methods. © 2025, CC BY.

关键词： Geometry

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H Control for General Conformable Polynomial Fuzzy Models

引用

International Journal of Fuzzy Systems 2025年 1-10页

作者： Laajimi, Malek Gassara, Hamdi Rhaima, Mohamed Mchiri, Lassaad Makhlouf, Abdellatif Ben Laboratory of Sciences and Techniques of Automatic control & Computer Engineering National School of Engineering of Sfax Sfax Tunisia Department of Statistics and Operations Research College of Science King Saud University Riyadh Saudi Arabia Panthéon-Assas University Paris II Paris France Department of Mathematics Faculty of Sciences Sfax University Sfax Tunisia

This research focuses on exploring the exponential $$H_\infty $$ stability of general conformable nonlinear system. In order to address the nonlinearity inherent in the system, a polynomial fuzzy (PF) method is employed. Modeling a general conformable nonlinear system within the polynomial framework reduces the number of fuzzy rules compared to the classical Takagi–Sugeno fuzzy (TSF). Furthermore, controlling such a complex system, which accounts for perturbations, employs a PF model instead TSF model to describe its nonlinear dynamics, and incorporates a general conformable derivative instead of an integer-order one, is significantly more challenging, and remains unaddressed in previous studies. In this paper, a PF controller is designed in the form of sum of squares (SOS) to enhance the resilience against perturbations and ensure the exponential stability of the proposed model. The proposed SOS can be solved numerically, and partially symbolically, using the recently developed SOSTOOLS. In order to ensure the $$H_\infty $$ performance, a generalized criterion is defined for the general conformable nonlinear system. To demonstrate the effectiveness of the proposed method, a numerical example is provided.

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PTSC: an efficient random boolean consensus algorithm for distributed systems with the probabilistic propagation model

引用

Peer-to-Peer Networking and Applications 2025年第4期18卷 1-12页

作者： Cao, Yuke She, Kun Xiao, Yuxuan Wu, Yongyue Ren, Yuntao Chen, Ruidong School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Frontier Research Department Anheng Vision (Chengdu) Information Technology Co. LTD Chengdu China Frontier Research Department Chengdu Anheng Information Technology Co. LTD Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

As the foundation of distributed systems, consensus mechanisms play a crucial role in ensuring the proper operation of the system. In a distributed network composed of trusted peer nodes, nodes may need to perform operations on random Boolean values (0 or 1) during their execution. To address this, this paper, inspired by Paxos, Raft, and their derivative algorithms, proposes a random Boolean consensus algorithm based on the principle of the Probabilistic Propagation Model. In each consensus round, a Boolean value is selected with a smaller probability in the first round of communication, and the final decision is made with a larger probability in the second round, ensuring that the probabilities of the system obtaining 0 or 1 are approximately equal. The running time is further reduced by minimizing the participation of nodes. Experimental results show that this method enables nodes in the system to quickly reach a consensus on a random Boolean value, and as the number of nodes increases, the savings in system overhead become more apparent.

关键词： Parallel processing systems

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VLM-Enabled Network Experimentation: Case Study of Chanel Capacity in System Limited by η-μ Fading

VLM-Enabled Network Experimentation: Case Study of Chanel Ca...

引用

International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Dejan Milić Nenad Petrović Milan Jović Radiša Stefanović Mejdin Saliji Elida Suljović Faculty of Electronic Engineering University of Niš Niš Serbia Applied Engineering Sciences Academy of Vocational Studies Polytechnic Belgrade Serbia Faculty of Mathematics and Natural Sciences Cyril and Methodius University Skopje Republic of North Macedonia Informatics and Computer Science Technical School in Novi Pazar Novi Pazar Serbia

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

In this paper, a micro-MRC receiver with L branches operating in a correlated gamma-shadowed η-μ fading channel is considered. For such a system, the channel capacity (CC) is determined based on the maximum signal-to-noise ratio (SNR) at the L branches at the input of the MRC receiver. The results are presented graphically to illustrate the impact of different system parameters on performance and the improvements that result from the advantages of combined diversity. Additionally, we introduce the application of Large Language Models (LLMs) to make network experimentation more practical, using the previously presented expression as a case study. Moreover, a Vision Language Model (VLM) aided method aiming to make model-driven network design and experimentation more convenient is introduced and evaluated for the previously considered case study

关键词： Fading channels Wireless communication Visualization Channel capacity System performance Scalability Large language models Receivers Signal to noise ratio

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Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review

引用

PeerJ computer Science 2025年 11卷 e2568-e2568页

作者： Mir, Rizwan Riaz Haq, Nazeef Ul Ishaq, Kashif Safie, Nurhizam Dogar, Abdul Basit Department of Computer Science and IT Virtual University of Pakistan Lahore Pakistan Department of Computer Science University of Engineering and Technology Lahore Lahore Pakistan School of Systems and Technology University of Management & Technology Lahore Pakistan Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Malaysia

Self-awareness and self-management in diabetes are critical as they enhance patient well-being, decrease financial burden, and alleviate strain on healthcare systems by mitigating complications and promoting healthier life expectancy. Incomplete understanding persists regarding the synergistic effects of diet and exercise on diabetes management, as existing research often isolates these factors, creating a knowledge gap in comprehending their combined influence. Current diabetes research overlooks the interplay between diet and exercise in self-management. A holistic study is crucial to mitigate complications and healthcare burdens effectively. Multi-dimensional research questions covering complete diabetic management such as publication channels for diabetic research, existing machine learning solutions, physical activity tacking existing methods, and diabetic-associated datasets are included in this research. In this study, using a proper research protocol primary research articles related to diet, exercise, datasets, and blood analysis are selected and their quality is assessed for diabetic management. This study interrelates two major dimensions of diabetes management together that are diet and exercise. Copyright 2025 Mir et al. Distributed under Creative Commons CC-BY 4.0

关键词： Self-supervised learning

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AI-Enhanced Multi-Dimensional Stochastic Process Modeling for QoS Analysis in 6G Networks Under Joint Fading and Dynamic Interference Constraints in $\alpha-\eta-\mu$ Environments

AI-Enhanced Multi-Dimensional Stochastic Process Modeling fo...

引用

Cognitive Computing in engineering, Communications, Sciences and Biomedical Health informatics (IC3ECSBHI), International Conference on

作者： Deepak Upadhyay Alankrita Aggarwal Pardeep Singh Deepak Suresh Asudani Nookala Venu Aakash Singh Ranswal Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Department of Computer Science and Engineering University Institute of Engineering Apex Institute of Technology UIE Chandigarh University Mohali India School of Computer Science and Engineering Galgotias University Noida India Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

In this paper, we investigate AI-enhanced multidimensional stochastic process modelling for QoS analysis in 6G networks subjected to $\alpha-\eta-\mu$ fading and dynamic interference constraints. Simulation results and heatmaps are utilized for the investigation of fading parameters such as shape factors and interference power, that impacts network performance. Our experimental findings show that AI-driven models provide markedly superior results in improving a number of QoS metrics, including throughput, latency, and packet loss compared to traditional methods. The research illustrates how AI improves connectivity, and operational stability of a network which adapts in times of fluctuating conditions. Our results demonstrate the ability of AI to preserve QoS while balancing performance and power, thereby providing a perspective for 6G network design and optimization.

关键词： Fading channels 6G mobile communication Adaptation models Analytical models Stochastic processes Packet loss Quality of service Throughput Stability analysis Optimization

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