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COMPRESSO: Latency-Aware Transmission of Compressed IoT Measurement Data Over SDN

IEEE Internet of Things Journal 2025年

作者： Feng, Wendi Dou, Xintan Taherkordi, Amirhosein Cheng, Bo Zhang, Wei State Key Laboratory of Networking and Switching Technology China University of Oslo College of Computer Science Dept. of Informatics Norway State Key Laboratory of Networking and Switching Technology China

Measurement data obtained from "things"in the Internet of Things (IoT) faces challenges in efficient transmission due to the low-bandwidth data transmission *** observe that measurement data are fixed in size and format, and low-entropy in the time domain, indicating that compression can be benefited. Rather than employing a single compression algorithm as advocated in existing literature, we argue that optimal transmission can be achieved by jointly considering compression overheads and network status, where software-defined networking (SDN) is employed to enforce network statistics and packet forwarding. This paper presents a new paradigm that achieves optimal transmission of SDN-empowered compressed measurement data. We formulate the problem as an optimization problem and prove its non-polynomial hardness time complexity. Due to this complexity, we introduce COMPRESSO, a heuristic algorithm that efficiently solves the problem. We conduct rigorous simulations, and the results demonstrate the efficiency of the new paradigm and COMPRESSO, i.e., attaining comparable performance to the optimal solution with 50% time usage reduction. © 2014 IEEE.

关键词： Data transfer

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A Framework for Digital Twin Collaboration 24

A Framework for Digital Twin Collaboration

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Proceedings of the Winter Simulation Conference

作者： Zhengchang Hua Karim Djemame Nikos Tziritas Georgios Theodoropoulos Dept. of Computer Science and Eng. Southern University of Science and Technology (SUSTech) Shenzhen CHINA and School of Computing University of Leeds Leeds UK School of Computing University of Leeds Leeds UK Dept. of Informatics and Telecommunications University of Thessaly Lamia GREECE Research Institute of Trustworthy Autonomous Systems (RITAS) SUSTech Shenzhen CHINA and Dept. of Computer Science and Eng. Southern University of Science and Technology (SUSTech) Shenzhen CHINA

ISBN: (纸本)9798331534202

Digital Twins (DTs) have emerged as a powerful tool for modeling Large Complex Systems (LCSs). Their strength lies in the detailed virtual models that enable accurate predictions, presenting challenges in traditionally centralized approaches due to the immense scale and decentralized ownership of LCSs. This paper proposes a framework that leverages the prevalence of individual DTs within LCSs. By facilitating the exchange of decisions and predictions, this framework fosters collaboration among autonomous DTs, enhancing performance. Additionally, a trust-based mechanism is introduced to improve system robustness against poor decision-making within the collaborative network. The framework's effectiveness is demonstrated in a virtual power plant (VPP) scenario. The evaluation results confirm the system's objectives across various test cases and show scalability for large deployments.

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Hierarchical Context Transformer for Multi-level Semantic Scene Understanding

arXiv

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arXiv 2025年

作者： Hao, Luoying Hu, Yan Yue, Yang Wu, Li Fu, Huazhu Duan, Jinming Liu, Jiang Research Institute of Trustworthy Autonomous Systems Dept. of Computer Science and Engineering Southern University of Science and Technology China School of Computer Science University of Birmingham United Kingdom Division of Informatics Imaging and Data Sciences School of Health Sciences University of Manchester United Kingdom MGI Tech Co. Ltd. China Singapore

A comprehensive and explicit understanding of surgical scenes plays a vital role in developing context-aware computer-assisted systems in the operating theatre. However, few works provide systematical analysis to enable hierarchical surgical scene understanding. In this work, we propose to represent the tasks set [phase recognition → step recognition → action and instrument detection] as multi-level semantic scene understanding (MSSU). For this target, we propose a novel hierarchical context transformer (HCT) network and thoroughly explore the relations across the different level tasks. Specifically, a hierarchical relation aggregation module (HRAM) is designed to concurrently relate entries inside multi-level interaction information and then augment task-specific features. To further boost the representation learning of the different tasks, inter-task contrastive learning (ICL) is presented to guide the model to learn task-wise features via absorbing complementary information from other tasks. Furthermore, considering the computational costs of the transformer, we propose HCT+ to integrate the spatial and temporal adapter to access competitive performance on substantially fewer tunable parameters. Extensive experiments on our cataract dataset and a publicly available endoscopic PSI-AVA dataset demonstrate the outstanding performance of our method, consistently exceeding the state-of-the-art methods by a large margin. The code is available at https://***/Aurorahao/HCT. Copyright © 2025, The Authors. All rights reserved.

关键词： Transplantation (surgical)

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Exploring the Potential of DeepSeek-R1 Model in Transforming Healthcare Solutions: An Overview

Exploring the Potential of DeepSeek-R1 Model in Transforming...

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International Symposium on Digital Forensic and Security (ISDFS)

作者： Muhammad Raheel Raza Shahbaz Ahmed Fahad Ahmed Khokhar Asaf Varol Peter Faber Business School Australian Catholic University North Sydney Australia Department of Computer Science Universitat Koblenz Koblenz Germany Department of Informatics & Mathematics University of Florence Firenze FI Italy Department of Engineering Management & Technology College of Eng. & Comp. Science Uni. of Tennessee at Chattanooga Chattanooga TN US Dept. of Computer Engineering College of Eng. & Nat. Sciences Maltepe University Istanbul Turkiye

ISBN: (数字)9798331509934

ISBN: (纸本)9798331509941

Over the past few decades, artificial intelligence (AI) has become more integrated into healthcare, with Large Language Models (LLMs) being a key component in improving healthcare decision-making. These LLMs' capacity to produce and interpret human-like texts has the potential to revolutionize healthcare procedures, where efficient data processing and communication are crucial. DeepSeek-Rl, created by DeepSeek AI, has drawn notice globally for its reasoning-based design that uses reinforcement learning (RL) to enhance problem-solving skills. Keeping this in view, the paper emphasizes the significance of the DeepSeek- Rl model and its application in the healthcare industry. Highlighting some hypothetical potential scenarios, we believe that DeepSeek models can playa crucial role in transforming existing medical approaches and revolutionizing the future of AI in health care.

关键词： Industries Biological system modeling Large language models Digital forensics Decision making Medical services Reinforcement learning Data processing Security Problem-solving

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Virtual laboratories in education - A cheap way for schools to obtain laboratories for all courses, by using the computer Laboratory

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technology Enhanced Learning Workshop held at the18th IFIP World computer Congress

作者： Alexiou, A Bouras, C Giannaka, E Research Academic Computer Technology Institute Greece and Computer Engineering and Informatics Dept. Univ. of Patras Greece

ISBN: (纸本)0387240462

Practical experience is an important component of the educational process. However, the time and economical resources often required for the setting up and construction of scientific laboratories is outside the scope of many institutions. A solution to this problem could be found in the adaptation of the Virtual Reality technology, which could allow the creation of Virtual Laboratories, which will simulate the processes and actions that could take place in real laboratories. In particular, this paper, based on the expertise and motivation gained by the VirRAD-IST project, proposes and describes such an educational virtual laboratory, which aims to meet the requirements of a teal laboratory and furthermore to support communication and collaboration services. We propose a web-based system, which allows users to perform experiments on educational fields, such as Physics or Chemistry in 3D multi-user worlds where users are represented by avatars and they are offered a wide range of communication and collaboration services in. order to simulate efficiently a real learning experimental process.

关键词： distance learning virtual reality multi-user virtual environments Virtual Laboratories Educational Virtual Environments

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A hypercube algorithm for sliding window compression

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Parallel Processing Letters 2000年第4期10卷 315-326页

作者： Kaklamanis, C. Konstantopoulos, C. Svolos, A. Computer Technology Institute Dept. of Comp. Eng. and Informatics University of Patras 26500 Rio Greece

Dictionary compression belongs to the class of lossless compression methods and is mainly used for compressing text files. The most known examples of this technique are the algorithms of the LZ coding family whose common feature is the use of an adaptive dictionary which is dynamically adjusting during the algorithm execution. In this paper, we present a parallel algorithm for one of these coding algorithms, namely the LZ77 coding algorithm also known as a sliding-window coding algorithm. We also present a parallel algorithm for the corresponding LZ77 decoding algorithm. Although there exist PRAM algorithms for various dictionary compression methods, their rather irregular structure has discouraged their implementation on practical interconnection networks such as the mesh and hypercube. However in the case of LZ77 coding/decoding, we show how to exploit the specific properties of the algorithm in order to achieve an efficient implementation on the hypercube. Specifically, we show how to encode a N-character string on a N-node hypercube in only O(log2N) time. In contrast, a naive simulation of a PRAM algorithm of the LZ77 coding on the hypercube would have O(log3N) complexity. In addition, we further enhance the performance of our parallel algorithms by using some known heuristics from the field of text compression.

关键词： Parallel algorithms

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Video Transmission over TFRC using cross-layer power management

Video Transmission over TFRC using cross-layer power managem...

引用

International Conference on Software, Telecommunications and computer Networks

作者： Bouras, Christos Gkamas, Apostolos Kapoulas, Vaggelis Papapanagiotou, Vassilis Stamos, Kostas Zaoudis, Giannis Research Academic Computer Technology Institute Computer Engineering and Informatics Dept. University of Patras Greece

ISBN: (纸本)9781424449736

This paper presents the issues related to efficient transmission of encoded video (such as H.264) over wireless links using the TFRC protocol. It proposes a novel mechanism that utilizes cross-layer approaches for adaptation of the power transmission level of the sender and feedback information regarding the wireless connection status from the receiver for improved transmission statistics and therefore user experience without unnecessary power consumption. The mechanism is tested through simulations using ns2. Compared to the operation of the video transmission without the mechanism, we observe that it has benefits in terms of video quality.

关键词： Image communication systems

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Evaluation of the multicast mode of MBMS

Evaluation of the multicast mode of MBMS

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18th IEEE International Symposium on Personal, Indoor and Mobile Radio Communication

作者： Alexiou, Antonios Bouras, Christos Kokkinos, Vasileios Rekkas, Evangelos Research Academic Computer Technology Institute Computer Engineering and Informatics Dept. Univ. of Patras Greece

ISBN: (纸本)9781424411436

Multicasting is an efficient way for delivering rich multimedia applications to large user groups as it allows the transmission of packets to multiple destinations using fewer network resources. Content and service providers are increasingly interested in supporting multicast communications over wireless networks and in particular over Universal Mobile Telecommunications System (UMTS). To this direction, the third Generation Partnership Project (3GPP) is currently standardizing the Multimedia Broadcast/Multicast Service (MBMS) framework of UMTS. In this paper, we present an overview of the MBMS multicast mode of UMTS. We analytically present the multicast mode of the MBMS and analyze its performance in terms of packet delivery cost under various network topologies, cell environments and multicast users' distributions. Furthermore, for the evaluation of the scheme, we consider different transport channels for the transmission of the data over the UTRAN interfaces and propose a cost based scheme for the efficient radio bearer selection that minimizes the packet delivery cost.

关键词： Multicasting

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Motion control for humanoid robots based on the motion phase decision tree learning

Motion control for humanoid robots based on the motion phase...

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2004 International Symposium on Micro-NanoMecahtronics and Human Science, MHS2004;The Fourth Symposium 'Micro-NanoMechatronics for and Information-Based Society' The 21st Century COE Program, Nagoya University, Micro-Nano COE

作者： Kuwayama, Kiyotake Kato, Shohei Kunitachi, Tsutomu Itoh, Hidenori Dept. of Intelligence and Computer Science Nagoya Institute of Technology Dept. of Computer Science and Art School of Informatics Daido Institute of Technology

ISBN: (纸本)0780386078

Humanoid robots, due to their link structure with high degree of freedom and the substitutability for human work, require a sophisticated motion control technique regardless of the type of motions or the environments. This paper gives a concept learning-based approach to this problem. We propose a motion generation method based on decision tree learning with motion phase. The system can generate a stable and anti-tumble motion which transforms the robot into a target posture. In experiment, the target motion are to stand up from a chair. Some stable and anti-tumble motions to stand up from a chair were performed by humanoid robot HOAP-1. In this paper, we discuss the validity of motion control considering motion phase. © 2004 IEEE.

关键词： Robots

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Performance Evaluation of a Descent Algorithm for Bi-matrix Games

Performance Evaluation of a Descent Algorithm for Bi-matrix ...

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4th International Workshop on Internet and Network Economics

作者： Tsaknakis, Haralampos Spirakis, Paul G. Kanoulas, Dimitrios Research Academic Computer Technology Institute (RACTI) Greece Dept. of Computer Eng. and Informatics Patras University Patras Greece

ISBN: (纸本)9783540921844

In this paper we present an implementation and performance evaluation of a descent algorithm that was proposed in [1] for the computation of approximate Nash equilibria of non-cooperative bi-matrix games. This algorithm, which achieves the best polynomially computable epsilon-approximate equilibria till now, is applied here to several problem instances designed so as to avoid the existence of easy solutions. Its performance is analyzed in terms of quality of approximation and speed of convergence. The results demonstrate significantly better performance than the theoretical worst case bounds, both for the quality of approximation and for the speed of convergence. This motivates further investigation into the intrinsic characteristics of descent algorithms applied to bi-matrix games. We discuss these issues and provide some insights about possible variations and extensions of the algorithmic concept that could lead to further understanding of the complexity of computing equilibria. We also prove here a new significantly better bound on the number of loops required for convergence of the descent algorithm.

关键词： Parallel processing systems

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