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Auction Theory and Game Theory Based Pricing of Edge Computing Resources: A Survey

IEEE Internet of Things Journal 2025年

作者： Yu, Jiguo Liu, Shun Zou, Yifei Wang, Guijuan Hu, Chunqiang University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu610054 China Qilu University of Technology Big Data Institute Jinan250353 China Qufu Normal University School of Computer Science Shandong Rizhao China Shandong University School of Computer Science and Technology Shandong Qingdao266237 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan250353 China Chongqing University School of Big Data and Software Engineering Chongqing400044 China

The proliferation of Internet of Things (IoT) devices and edge computing applications has heightened the demand for efficient resource allocation and pricing mechanisms. Effective pricing strategies play a crucial role in optimizing resource utilization, reducing latency, and ensuring fair resource distribution among users. Both auction theory and game theory have emerged as fundamental economic frameworks for designing pricing mechanisms in edge computing. This paper presents a comprehensive survey of pricing strategies that leverage both auction and game theory, systematically categorizing existing research based on auction mechanisms and game-theoretic models. Unlike previous surveys that focus solely on auction-based pricing, this work integrates game-theoretic perspectives, providing a holistic analysis of strategic interactions in edge computing resource allocation. Furthermore, we discuss key challenges, emerging trends, and future research directions aimed at enhancing efficiency, fairness, and privacy protection in cloud-edge collaborative computing environments. © 2014 IEEE.

关键词： Mobile edge computing

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Research on Lightweight Sensing technology Based on Single-Antenna Multicarrier

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IEEE Internet of Things Journal 2025年

作者： Jiang, Yu Zhu, Di Wang, Jiadong Hu, Aiqun Southeast University School of Cyber Scienc and Engineering Purple Mountain Laboratories Nanjing210096 China Key Laboratory of Computer Network Technology of Jiangsu Province Nanjing210096 China Southeast University Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Southeast University School of Cyber Science and Engineering Nanjing210096 China Southeast University School of Cyber Science and Engineering School of Information Science and Engineering Nanjing210096 China Southeast University State Key Laboratory of Mobile Communication Nanjing210096 China

Channel State Information (CSI) serves as a critical indicator of wireless signal conditions and is widely regarded by researchers for its sensitivity in detecting changes within the channel. However, traditional sensing technologies often require substantial data and intricate learning algorithms, highlighting an urgent need for advancements in lightweight sensing technologies. These technologies should leverage simpler terminal devices, reduced data volumes, and more straightforward classification algorithms to achieve sensing capability that are comparable to those offered by more complex and established methods. This paper concentrates on the lightweight application of wireless sensing and encompasses the following key contributions: 1) The development of a lightweight sensing model utilizing a single-antenna multicarrier system, which introduces a CSI ratio model that adapts multi-antenna techniques for single-antenna settings;2) The enhancement of feature stability through the introduction of a complex-plane fitting method using artificial vector, alongside a dual receiver based method for cross-scene feature generation aimed at producing stable and high-quality auxiliary features. Experimental results show that the feature extraction capability of the single-antenna multicarrier CSI ratio model is close to that of traditional multi-antenna scheme. On the gait dataset, when the enhanced CSI ratio is used as a feature, the accuracy is nearly 100%, surpassing the 93% accuracy of the original amplitude feature. On the gesture dataset, the combination of the enhanced CSI ratio and PEI features achieves an accuracy of 96%, which is superior to using the original CSI amplitude feature alone. An analysis of resource consumption shows that the lightweight SVM model incurs very low computational overhead during decision-making, validating the potential of this scheme in terms of efficiency and practical application. © 2014 IEEE.

关键词： Communication channels (information theory)

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Fiber to the Room: key Technologies, Challenges, and Future Prospects

arXiv

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arXiv 2025年

作者： Cai, Jinhan Zhang, Xiaolong Wang, Xiang Chang, Tianhai Shen, Gangxiang Jiangsu Provincial Laboratory for Advanced Optical Transmission and Switching Networks Jiangsu New Optical Fiber Technology and Communication Network Engineering Research Center Suzhou Key Laboratory of Advanced Optical Communication Network Technology School of Electronic and Information Engineering Soochow University Jiangsu Province 215006 China Huawei Technology China

Fiber to the Room (FTTR) is a next-generation access network designed to deliver high bandwidth, low latency, and room-level optical coverage. This paper presents a comprehensive analysis of the FTTR system architecture and protocol stack, focusing on three key technical aspects: centralized scheduling and control, integrated management and maintenance, and green energy-saving mechanisms. A simplified FTTR architecture based on the convergence of the medium access control (MAC) and physical (PHY) layers is introduced to enhance coordination and scheduling efficiency. An extended remote management scheme, based on the optical network unit management and control interface (OMCI), is described to enable unified control across main fiber units (MFUs) and sub-fiber units (SFUs). Furthermore, a service-aware energy-saving framework is discussed for dynamic power optimization. The paper also explores the integration of artificial intelligence (AI) and passive sensing into FTTR systems to support intelligent scheduling, energy management, and environment-aware optimization. These insights provide technical guidance for the scalable deployment and future evolution of FTTR networks. Copyright © 2025, The Authors. All rights reserved.

关键词： Fiber to the x

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A low voltage low power up-conversion mixer for WSN application

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Journal of Semiconductors 2014年第4期35卷 123-127页

作者：吴晨健李智群孙戈 Institute of RF-& OE-ICs Southeast University Jiangsu Provincial Key Laboratory of Sensor Network Technology Soochow University

This paper presents an up-conversion mixer for 2.4-2.4835 GHz wireless sensor networks （WSN） in 0.18 μm RF CMOS technology. It was based on a double-balanced Gilbert cell type, with two Gilbert cells having quadrature modulation applied. Current-reuse and cross positive feedback techniques were applied in the mixer to boost conversion gain; the current source stage was removed from the mixer to improve linearity. Measured results exhibited that under a 1 V power supply, the conversion gain was 5 dB, the input referred 1 dB compression point was -11 dBm and the IIP3 was -0.75 dBm, while it only consumed 1.4 mW.

关键词： low voltage low power current-reuse positive feedback mixer

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A New and Efficient IT Knowledge Exchange Platform 2nd

A New and Efficient IT Knowledge Exchange Platform

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2nd International Conference on Applied Intelligence, ICAI 2024

作者： Sha, Jinting Yu, Wendong Wei, Hongwei Yuan, Lin Li, Zhujun Shandong Jinan250353 China Shandong Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Shandong Jinan250353 China Shandong Tianyi Information Technology Co. Ltd. Shandong Jinan250101 China Jinan Springs Patent and Trademark Office Shandong Jinan250014 China

ISBN: (纸本)9789819619061

As information technology continues to advance, an increasing number of technicians are joining the IT field. However, the technology in this field is changing very rapidly, requiring many technicians to constantly learn new knowledge to keep pace with developments. Therefore, in this context, the creation of a user-friendly IT technology exchange platform is highly valuable, so that technicians can easily learn and interact with each other. This platform adopts Vue 2 as the front-end framework, utilizes Spring Boot for the back-end development, Elasticsearch for full-text search capabilities, MySQL for data storage, Spring Security for authentication and security, and MyBatis for data persistence. Users can register accounts, create and publish articles and resources, and also like or bookmark articles and resources. In addition, the platform also supports features such as full-text search, article categorization, resource classification and so on. Testing has demonstrated that this IT knowledge exchange platform meets the basic needs of its users. At the same time, the platform offers robust security measures to protect user privacy and ensure data security. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： IT knowledge exchange platform Spring Boot Vue 2

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Measuring web page complexity by analyzing TCP flows and HTTP headers

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The Journal of China Universities of Posts and Telecommunications 2017年第6期24卷 1-13页

作者： Cheng Weiqing Hu Yangyang Yin Qiaofeng Chen Jiajia School of Computer Science Nanjing University of Posts and Telecommunications Key Laboratory of Computer Network and Information Integration Southeast University Jiangsu Education Information Center Jiangsu Provincial Department of Education

To understand website complexity deeply, a web page complexity measurement system is developed. The system measures the complexity of a web page at two levels： transport-level and content-level, using a packet trace-based approach rather than server or client logs. Packet traces surpass others in the amount of information contained. Quantitative analyses show that different categories of web pages have different complexity characteristics. Experimental results show that a news web page usually loads much more elements at more accessing levels from much more web servers within diverse administrative domains over much more concurrent transmission control protocol （TCP） flows. About more than half of education pages each only involve a few logical servers, where most of elements of a web page are fetched only from one or two logical servers. The number of content types for web game traffic after login is usually least. The system can help web page designers to design more efficient web pages, and help researchers or Internet users to know communication details.

关键词： hyper text transfer protocol concurrent TCP flows world wide web web page complexity

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Design and Implementation of Takeaway Ordering Recommendation System Based on Python and Flask 2nd

Design and Implementation of Takeaway Ordering Recommendatio...

引用

2nd International Conference on Applied Intelligence, ICAI 2024

作者： Cao, Junjie Yu, Wendong Wei, Hongwei Yuan, Lin Li, Zhujun Shandong Jinan250353 China Shandong Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Shandong Jinan250353 China Shandong Tianyi Information Technology Co. Ltd. Shandong Jinan250101 China Jinan Springs Patent and Trademark Office Shandong Jinan250014 China

ISBN: (纸本)9789819619030

With the rapid development of the economy, people are getting busier and busier, and it is difficult to find time to cook, so ordering takeout or dining at restaurants has become the norm. In the 2020 work report, the government proposed to fully implement the "Internet +" process, which also indicates the arrival of the advantages of the digital economy. Therefore, it has become an inevitable trend to use Internet technology to change our daily life and production methods. Driven by this trend, the catering industry has begun to move towards informatization. In order to make it more convenient for merchants and customers to meet their respective needs and save time and energy, a takeaway ordering recommendation system has emerged. This paper uses a collaborative filtering recommendation algorithm to recommend personalized foods that users may like, so as to provide more convenient services for catering services. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Bottles

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Few-Shot Photovoltaic Film Defect Detection with Contextual Ensemble Language-Image Multimodal network

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IEEE Transactions on Industrial Informatics 2025年

作者： Wang, Huiyan Peng, Ruihao Zhu, Yiheng Li, Jiachen Zhou, Mengchu Ying, Ming Wang, Shouguang Zhejiang Gongshang University School of Computer Science and Technology Hangzhou 310018 China Qilu University of Technology (Shandong Academy of Sciences) Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Jinan 250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Jinan 250353 China New Jersey Institute of Technology Helen and John C. Hartmann Department of Electrical and Computer Engineering Newark 07102 NJ United States Zhejiang Gongshang University School of Information and Electronic Engineering Hangzhou 310018 China

The automatic detection of defects in industrial photovoltaic film is crucial for ensuring the reliability of photovoltaic modules. key challenges include limited defect samples, interclass feature similarities, and interference from complex backgrounds. Existing deep learning-based methods require large-scale datasets and focus solely on visual data, which limits their effectiveness in few-shot defect detection (FSDD). To address these challenges, we propose Contextual Ensemble Language-Image multimodal network (CELIN), which enhances FSDD in photovoltaic films by incorporating textual information through prompt tuning. Unlike traditional language-image models that rely on single fixed text prompts, CELIN employs a position-aware context ensemble strategy to integrate position-specific prompt vectors, enabling the model to capture global contextual information and reduce background interference. In addition, a cross class mask method is introduced to differentiate between similar defect categories by blocking interclass interactions during attention computation, thereby minimizing misclassification. Extensive experiments on our own few-shot photovoltaic film defect dataset and various public benchmarks demonstrates that CELIN significantly outperforms existing methods. © 2005-2012 IEEE.

关键词： Contextual ensemble prompt tuning few-shot surface defect detection photovoltaic film defect detection vision-language multimodal model

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Homeomorphism Prior for False Positive and Negative Problem in Medical Image Dense Contrastive Representation Learning

arXiv

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arXiv 2025年

作者： He, Yuting Wang, Boyu Ge, Rongjun Chen, Yang Yang, Guanyu Li, Shuo Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Ministry of Education Nanjing China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Nanjing China School of Instrument Science and Engineering Southeast University Nanjing China Department of Computer Science Western University LondonONN6A 3K7 Canada Department of Biomedical Engineering Department of Computer and Data Science Case Western Reserve University ClevelandOH44106 United States

Dense contrastive representation learning (DCRL) has greatly improved the learning efficiency for image dense prediction tasks, showing its great potential to reduce the large costs of medical image collection and dense annotation. However, the properties of medical images make unreliable correspondence discovery, bringing an open problem of large-scale false positive and negative (FP&N) pairs in DCRL. In this paper, we propose GEoMetric vIsual deNse sImilarity (GEMINI) learning which embeds the homeomorphism prior to DCRL and enables a reliable correspondence discovery for effective dense contrast. We proposes a deformable homeomorphism learning (DHL) which models the homeomorphism of medical images and learns to estimate a deformable mapping to predict the pixels’ correspondence under the condition of topological preservation. It effectively reduces the searching space of pairing and drives an implicit and soft learning of negative pairs via gradient. We also proposes a geometric semantic similarity (GSS) which extracts semantic information in features to measure the alignment degree for the correspondence learning. It will promote the learning efficiency and performance of deformation, constructing positive pairs reliably. We implement two practical variants on two typical representation learning tasks in our experiments. Our promising results on seven datasets which outperform the existing methods show our great superiority. We will release our code at a companion website. Copyright © 2025, The Authors. All rights reserved.

关键词： Contrastive Learning

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Barrier Offset Varying-Parameter Dynamic Learning network for Solving Dual-Arms Human-Like Behavior Generation

引用

IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Zhang, Zhijun Zhang, Mingyang Guo, Jinjia He, Haotian School of Automation Science and Engineering South China University of Technology Guangzhou510640 China Key Library of Autonomous Systems and Network Control Ministry of Education China Jiangxi Thousand Talents Plan Nanchang University Nanchang330031 China Guangzhou510335 China Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Shanxi University of Technology Hanzhong723001 China School of Information Science and Engineering Changsha Normal University Changsha410100 China School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Guangdong University of Petrochemical Technology Maoming525000 China School of Computer Science and Engineering Jishou University Jishou416000 China

Enabling robots to imitate human actions and perform tasks with high precision while avoiding potential obstacles in the environment can effectively enhance the interaction between social robots and humans. In this paper, to achieve higher precision trajectory tracking and obstacle avoidance for dual-arm humanoid robots, the barrier offset varying-parameter dynamic learning neural (BOVDL) network method is proposed and applied to dual-arm humanoid behavior generation scheme. To do so, a dual-arms humanoid robot model is set up, and transformed into a constrained time-varying quadratic programming (TVQP) problem. Secondly, by using lagrangian multiplier method and Karush-Kuhn-Tuchker condition, the inequality constrained TVQP is converted as a time-varying equation with a barrier parameter. Thirdly, a varying-parameter dynamic learning network is presented to solve the time-varying equation with a barrier parameter. computer simulation experiments are conducted to verify the feasibility, accuracy, and safety of the proposed BOVDL network method. Experimental results show that all 14 joints of the humanoid robot's arms are within the motion range of each real human arm's physical constraints. The maximum position error and velocity error between the desired trajectory and the actual trajectory of the end effector are less than 10-6m magnitude and 10-7m magnitude, respectively, representing a reduction of 5 orders of magnitude compared to the traditional varying-parameter convergent-differential neural network. Furthermore, the proposed method also enables the dual-arm humanoid robot to avoid collisions with obstacles while performing tasks, demonstrating the superiority of the proposed BOVDL network scheme. © 2016 IEEE.

关键词： Anthropomorphic robots

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