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24th International Conference on Algorithms and architectures for Parallel Processing, ICA3PP 2024

作者： Yang, Tingting Wang, Yiqian Zhu, Jie Chang, Shuyu Huang, Haiping Nanjing University of Posts and Telecommunications Nanjing210003 China State Key Laboratory Chinese of Computer Architecture Institute of Computing Technology Academy of Sciences Beijing100864 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing210003 China

ISBN: (纸本)9789819615278

Unmanned Aerial Vehicles (UAVs) have emerged as integral components in logistics systems, where their potential for efficient delivery services is being explored. However, the limited battery capacity of UAVs poses a significant challenge for long-distance delivery applications. In this paper, we investigate a hybrid problem involving UAV trajectory planning and charging scheduling for long-distance logistics systems with a charging network. In the problem under study, multiple UAVs are assigned long-distance delivery tasks. A UAV can stop at any charging station in the charging network to charge if it is in a low-energy state. An Ant Colony Optimization-based UAV Trajectory Planning and Charging Scheduling (ACO-TPCS) algorithm is proposed to minimize task completion time by optimizing UAV trajectory and charging plans. The main framework of the ACO-TPCS algorithm consists of several key components, including reachable graph construction, candidate flight path generation, pheromone matrix construction, ant generation, feasible solution generation, and pheromone update method. All these components are delicately designed. Through extensive experimentation and comparison with baseline algorithms, we demonstrate the effectiveness of the ACO-TPCS algorithm in addressing the problem under study. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ant colony optimization

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Optimizing Self-training Sample Selection for Euphemism Detection in Special Scenarios 24th

Optimizing Self-training Sample Selection for Euphemism Dete...

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24th International Conference on Algorithms and architectures for Parallel Processing, ICA3PP 2024

作者： Zhang, Zhiwei Chang, Shuyu Huang, Haiping Wang, Rui Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing210023 China Nanjing University of Posts and Telecommunications Nanjing210023 China State Key Laboratory Chinese of Computer Architecture Institute of Computing Technology Academy of Sciences Beijing100864 China

ISBN: (纸本)9789819615476

Euphemism, which is often used to disguise true intentions or soften the tone of speech, has garnered significant attention for its detection in recent years. Current approaches to euphemism detection struggle with uncommon data, where new and rare vocabularies frequently emerge in the test set, leading to decreased model performance. To address these challenges, we propose a novel framework that combines data augmentation, self-training, and a special sample selection method. We expand the original dataset using lexical and sentence-level data augmentation techniques, enhancing the representation of rare vocabulary and allowing the model to familiarize itself with their contexts and usage characteristics. Next, we employ self-training as a semi-supervised learning approach, utilizing the augmented datasets to iteratively generate and refine pseudo-labels. During each iteration, a KNN framework is used to generate pseudo-labels by searching for the nearest neighbor texts, thus enhancing the quality of these labels. Finally, to further increase the presence of rare vocabulary in the training data, we implement a sample selection strategy based on euphemism frequency and predictive uncertainty, integrating it with the earlier steps. Experimental results demonstrate that our framework outperforms previous research on most metrics and achieves a 10% increase over the baseline model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Self-supervised learning

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Enhancing the Uplink of Cell-Free Massive MIMO Through Prioritized Sampling and Personalized Federated Deep Reinforcement Learning

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Mendoza, Charmae Franchesca Kaneko, Megumi Rupp, Markus Schwarz, Stefan Technische Universität Wien Institute of Telecommunications Sustainable Radio Access Networks Christian Doppler Laboratory Digital Twin Assisted AI Vienna1040 Austria National Institute of Informatics Information Systems Architecture Science Research Division Tokyo101-8430 Japan Department of Computer Science University of Tokyo Tokyo Japan Technische Universität Wien Institute of Telecommunications Vienna1040 Austria

Effective power control is key to solving the inter-user interference problem that degrades performance in cell-free massive multiple-input multiple-output (MIMO) systems. Motivated by its ability to operate online and model-free, without relying on training datasets, we leverage deep reinforcement learning (DRL) for uplink power control, aiming to maximize the guaranteed rate. We propose a fully centralized single-agent framework and two distributed schemes that employ several agents for improved scalability, leveraging prioritized experience replay to enable fast adaptation to the dynamic changes of the wireless environment. We investigate the performance of two multi-agent system architectures: (1) centralized training, decentralized execution (CTDE), where each agent forwards its RL experience to a central trainer, and (2) personalized federated learning (FedPer), where the training is performed locally at each agent, and only the base layer of the local deep neural network (DNN) model is forwarded periodically for aggregation at a server. We focus on the realistic scenario of dynamic device (de-)activation, combined with user mobility. Numerical evaluations demonstrate that the proposed FedPer with prioritized sampling achieves near-optimal rate and power performance while incurring the least amount of communication overhead. © 2015 IEEE.

关键词： Deep reinforcement learning

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Lightweight Task-Oriented Semantic Communication Empowered by Large-Scale AI Models

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chuanhong Guo, Caili Yang, Yang Chen, Mingzhe Quek, Tony Q. S. Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL United States Singapore University of Technology and Design Dept. of Information Systems Technology and Design 487372 Singapore

Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial computational demands of LAI models pose significant challenges for real-time communication scenarios. To address this, this paper proposes utilizing knowledge distillation (KD) techniques to extract and condense knowledge from LAI models, effectively reducing model complexity and computation latency. Nevertheless, the inherent complexity of LAI models leads to prolonged inference times during distillation, while their lack of channel awareness compromises the distillation performance. These limitations make standard KD methods unsuitable for task-oriented semantic communication scenarios. To address these issues, we propose a fast distillation method featuring a pre-stored compression mechanism that eliminates the need for repetitive inference, significantly improving efficiency. Furthermore, a channel adaptive module is incorporated to dynamically adjust the transmitted semantic information based on varying channel conditions, enhancing communication reliability and adaptability. In addition, an information bottleneck-based loss function is derived to guide the fast distillation process. Simulation results verify that the proposed scheme outperform baselines in term of task accuracy, model size, computation latency, and training data requirements. © 1967-2012 IEEE.

关键词： NP-hard

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Fusing Bluetooth with Pedestrian Dead Reckoning: A Floor Plan-Assisted Positioning Approach

arXiv

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arXiv 2025年

作者： Pan, Wenxuan Yang, Yang Chen, Mingzhe Wei, Dong Guo, Caili Mao, Shiwen Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering the Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Wireless Engineering Research and Education Center Auburn University AuburnAL36849 United States

Floor plans can provide valuable prior information that helps enhance the accuracy of indoor positioning systems. However, existing research typically faces challenges in efficiently leveraging floor plan information and applying it to complex indoor layouts. To fully exploit information from floor plans for positioning, we propose a floor plan-assisted fusion positioning algorithm (FP-BP) using Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). In the considered system, a user holding a smartphone walks through a positioning area with BLE beacons installed on the ceiling, and can locate himself in real time. In particular, FP-BP consists of two phases. In the offline phase, FP-BP programmatically extracts map features from a stylized floor plan based on their binary masks, and constructs a mapping function to identify the corresponding map feature of any given position on the map. In the online phase, FP-BP continuously computes BLE positions and PDR results from BLE signals and smartphone sensors, where a novel grid-based maximum likelihood estimation (GML) algorithm is introduced to enhance BLE positioning. Then, a particle filter is used to fuse them and obtain an initial estimate. Finally, FP-BP performs post-position correction to obtain the final position based on its specific map feature. Experimental results show that FP-BP can achieve a real-time mean positioning accuracy of 1.19 m, representing an improvement of over 28% compared to existing floor plan-fused baseline algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Photomapping

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Protection and restoration scheme for light-trail WDM ring networks

Protection and restoration scheme for light-trail WDM ring n...

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2005 Conference onOptical Network Design and Modelling: Towards the broadband-for-all era, ONDM 2005

作者： Gumaste, Ashwin Zheng, Si Qing Advanced Computer Networks and Architecture Laboratory University of Texas Dallas TX 75083

In this paper we propose a protection strategy for light-trail [1-4] networks for ring topologies. A light-trail is a multi-point lightpath, such that multiple users can take part in communication along the trail, through time (differentiated) non-overlapping connections. Dynamic connections between source-destination pairs can be set up and torn down without the need for optical switch reconfiguration. A light-trail hence represents an opportunistic medium that reduces the uncertainty of provisioning resources for dynamic connections. However, this multi-point flow model leads to a new set of problems in the area of protecting and restoring light-trail based networks. Conventional link protection or path protection techniques are not sufficient for light-trails because of the potential of having multiple possible source-destination pairs in the same trail over time. In this paper we propose a hardware scheme to protect light-trails and further prove its correctness. Further, the scheme is implemented through a failed-traffic assignment algorithm. Subsequently we consider alternative heuristic schemes for implementing the protection scheme proposed. We simulate and compare the simulation results to an analytical model developed. © 2005 IEEE.

关键词： Packet networks

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Linear complexity of sequences produced by single cycle T-function

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The Journal of China Universities of Posts and Telecommunications 2011年第4期18卷 123-128页

作者： WANG Yan HU Yu-pu LI Shun-bo YANG Yang Key Laboratory of Computer Networks and Information Security Ministry of Education Xidian University Xi'an 710071 China Department of Mathematics Xi'an University of Architecture and Technology Xi'an 710055 China

Four kinds of sequences generated by single cycle triangular function （T-function） are investigated to check the possibility for a single cycle T-function to be a cryptographic component in stream ciphers. Based on the special properties of single cycle T-function and an algorithm due to Wei, linear complexities of these four kinds of sequence are all acquired. The results show that single cycle T-function sequences have high linear complexity. Therefore, T-function satisfies the essential requirements being a basic component of stream cipher.

关键词： stream cipher single cycle T-function linear complexity

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Revisiting the security of the ALRED design and two of its variants: Marvin and lettersoup

Revisiting the security of the ALRED design and two of its v...

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作者： Simplicio Jr., Marcos A. Barreto, Paulo S.L.M. Laboratory of Computer Architecture and Networks Escola Politécnica University of São Paulo 04023-900 Brazil

The Alred construction is a lightweight strategy for constructing message authentication algorithms from an underlying iterated block cipher. Even though this construction's original analyses show that it is secure against some attacks, the absence of formal security proofs in a strong security model still brings uncertainty on its robustness. In this paper, aiming to give a better understanding of the security level provided by different authentication algorithms based on this design strategy, we formally analyze two Alred variants - the Marvin message authentication code and the LetterSoup authenticated-encryption scheme, - bounding their security as a function of the attacker's resources and of the underlying cipher's characteristics. © 1963-2012 IEEE.

关键词： Authentication

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A business model for video transmission services using dynamic adaptation streaming over HTTP 9

A business model for video transmission services using dynam...

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9th Advanced International Conference on Telecommunications, AICT 2013

作者： Rodríguez, Demóstenes Zegarra Rosa, Renata Lopes Bressan, Graça Laboratory of Computer Architecture and Networks Computer and Digital System Engineering Department University of São Paulo São Paulo Brazil

ISBN: (纸本)9781612082790

A business model for video transmission services is proposed that uses the Dynamic Adaptation Streaming over HTTP (DASH) mechanism using different versions of the same video. These video versions are encoded using different parameters, such as spatial resolution or number of frames per second. The transmission of each video version depends on the capabilities of the network at the end user point. The business model proposed considers different costs for each version of video fragments transmitted. The costs of video resolution upgrade are predefined by the service provider and used during the video streaming. Also, in this model, the user can either accept or reject an upgrade. Subjective tests were performed using different spatial resolutions of the same video, in which the interest level of users to perform a video upgrade is evaluated. Furthermore, the network architecture of the proposed solution is presented and the technical feasibility to deploy the proposed solution in commercial networks is shown. As a consequence, the proposed solution can improve the earnings of the video service provider. Copyright © 2013 IARIA.

关键词： Video streaming

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Towards bandwidth optimization in fog computing using FACE framework 7

Towards bandwidth optimization in fog computing using FACE f...

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7th International Conference on Cloud Computing and Services Science, CLOSER 2017

作者： De Fátima Pereira Marquesone, Rosangela Da Silva, Érico Augusto Gonzalez, Nelson Mimura Langona, Karen Goya, Walter Akio Redígolo, Fernando Frota De Brito Carvalho, Tereza Cristina Melo Mangs, Jan-Erik Sefidcon, Azimeh Laboratory of Computer Networks and Architecture Escola Politecnica University of São Paulo Brazil Ericsson Research Sweden

ISBN: (纸本)9789897582431

The continuous growth of data created by Internet-connected devices has been posing a challenge for mobile operators. The increase in the network traffic has exceeded the network capacity to efficiently provide services, specially for applications that require low latency. Edge computing is a concept that allows lowering the network traffic by using cloud-computing resources closer to the devices that either consume or generate data. Based on this concept, we designed an architecture that offers a mechanism to reduce bandwidth consumption. The proposed solution is capable of intercepting the data, redirecting it to a processing node that is allocated between the end device and the server, in order to apply features that reduce the amount of data on the network. The architecture has been validated through a prototype using video surveillance. This area of application was selected due to the high bandwidth requirement to transfer video data. Results show that in the best scenario is possible to obtain about 97% of bandwidth gain, which can improve the quality of services by offering better response times. ©2017 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Fog computing

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