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Virtual node based adaptive routing in wireless ad hoc networks

中国高等学校学术文摘·计算机科学 2009年第4期3卷 535-542页

作者： Gang LI Hongmei SUN Key Lab of Network Science and Technology Institute of Computing TechnologyChinese Academy of SciencesBeijing 100080China Communications Technology Lab Intel China Research CenterBeijing 100080China

It is a challenge to make the routes quickly adapt to the changed network topology when nodes fail in a wireless ad hoc *** this paper,we propose an adaptive routing protocol,which groups the network nodes into virtual nodes according to their data transfer capabilities and creates virtual-node-based *** protocol can accommodate the routes to node failures by adaptively updating the virtual nodes and just-in-time using available nodes during data *** simulations indicate that the proposed protocol can keep the routes failed-node-free when the available virtual node members cover the failed nodes scattering area.

关键词： wireless ad hoc networks mobile ad hoc networks route protocols adaptability route repair

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A prior embedding-driven architecture for long distance blind iris recognition

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Biomedical Signal Processing and Control 2025年 109卷

作者： Xiong, Qi Zhang, Xinman Shen, Jun International College Hunan University of Arts and Sciences Changde415000 China School of Automation Science and Engineering Faculty of Electronic and Information Engineering MOE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Shaanxi Xi'an710049 China School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia

Blind iris images, caused by unknown degradation during the process of iris recognition at long distances, often lead to decreased iris recognition rates. Currently, limited literature addresses this issue. To tackle this challenge, we propose a prior embedding-driven architecture for long-distance blind iris recognition. Our approach introduces a blind iris image restoration network named Iris-PPRGAN. To effectively restore the texture of blind iris images, Iris-PPRGAN incorporates a Generative Adversarial network (GAN) as a Prior Decoder and a Deep Neural network (DNN) as the encoder. To enhance iris feature extraction, we also developed a robust iris classifier by modifying the bottleneck module of InsightFace, referred to as Insight-Iris. Initially, a low-quality blind iris image is restored using Iris-PPRGAN, and the restored image is subsequently recognized through Insight-Iris. Experimental results on the public CASIA-Iris-distance dataset demonstrate that our method outperforms state-of-the-art blind iris restoration techniques. Specifically, the recognition rate for long-distance blind iris images improves from 80.77 % (without restoration) to 90.38 % after applying our method, reflecting an approximate ten-percentage-point improvement. These results, validated both quantitatively and qualitatively, underscore the effectiveness of our approach in addressing the challenges of long-distance blind iris recognition. © 2025 Elsevier Ltd

关键词： Deep neural networks

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Unleashing the Power of LLMs in Dense Retrieval with Query Likelihood Modeling

arXiv

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arXiv 2025年

作者： Zhang, Hengran Bi, Keping Guo, Jiafeng Sun, Xiaojie Liu, Shihao Shi, Daiting Yin, Dawei Cheng, Xueqi CAS Key Lab of Network Data Science and Technology ICT CAS University of Chinese Academy of Sciences Beijing China Baidu Inc Beijing China

Dense retrieval is a crucial task in Information Retrieval (IR) and is the foundation for downstream tasks such as re-ranking. Recently, large language models (LLMs) have shown compelling semantic understanding capabilities and are appealing to researchers studying dense retrieval. LLMs, as decoder-style generative models, are competent at language generation while falling short on modeling global information due to the lack of attention to tokens afterward. Inspired by the classical word-based language modeling approach for IR, i.e., the query likelihood (QL) model, we seek to sufficiently utilize LLMs’ generative ability by QL maximization. However, instead of ranking documents with QL estimation, we introduce an auxiliary task of QL maximization to yield a better backbone for contrastively learning a discriminative retriever. We name our model as LLM-QL. To condense global document semantics to a single vector during QL modeling, LLM-QL has two major components, Attention Stop (AS) and Input Corruption (IC). AS stops the attention of predictive tokens to previous tokens until the ending token of the document. IC masks a portion of tokens in the input documents during prediction. Experiments on MSMARCO show that LLM-QL can achieve significantly better performance than other LLM-based retrievers and using QL estimated by LLM-QL for ranking outperforms word-based QL by a large margin. Our code can be found at https://***/Trustworthy-Information-Access/llm-ql. Copyright © 2025, The Authors. All rights reserved.

关键词： Online searching

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Splicer+: Secure Hub Placement and Deadlock-Free Routing for Payment Channel network Scalability

arXiv

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arXiv 2025年

作者： Yang, Lingxiao Dong, Xuewen Wang, Wei Gao, Sheng Qu, Qiang Tian, Wensheng Shen, Yulong The School of Computer Science and Technology Xidian University Xi’an710071 China The Shaanxi Key Laboratory of Network and System Security Xi’an710071 China The Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing100044 China The School of Information Central University of Finance and Economics Beijing100081 China The Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China The Huawei Blockchain Lab Huawei Cloud Tech Co. Ltd. Shenzhen518055 China The Nanhu Lab Jiaxing314001 China The Cryptology and Computer Security Laboratory Shanghai Jiao Tong University Shanghai200240 China

Payment channel hub (PCH) is a promising approach for payment channel networks (PCNs) to improve efficiency by deploying robust hubs to steadily process off-chain transactions. However, existing PCHs, often preplaced without considering payment request distribution across PCNs, can lead to load imbalance. PCNs' reliance on source routing, which makes decisions based solely on individual sender requests, can degrade performance by overlooking other requests, thus further impairing scalability. In this paper, we introduce Splicer+, a highly scalable multi-PCH solution based on the trusted execution environment (TEE). We study tradeoffs in communication overhead between participants, transform the original NP-hard PCH placement problem by mixed-integer linear programming, and propose optimal/approximate solutions with load balancing for different PCN scales using supermodular techniques. Considering global PCN states and local directly connected sender requests, we design a deadlock-free routing protocol for PCHs. It dynamically adjusts the payment processing rate across multiple channels and, combined with TEE, ensures high-performance routing with confidential computation. We provide a formal security proof for the Splicer+ protocol in the UC-framework. Extensive evaluations demonstrate the effectiveness of Splicer+, with transaction success ratio (↑51.1%), throughput (↑181.5%), and latency outperforming state-of-the-art PCNs. Copyright © 2025, The Authors. All rights reserved.

关键词： Scalability

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PPO-Based Vehicle Control for Ramp Merging Scheme Assisted by Enhanced C-V2X

arXiv

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arXiv 2025年

作者： Wu, Qiong Ji, Maoxin Fan, Pingyi Wang, Kezhi Cheng, Nan Chen, Wen Letaief, Khaled B. The School of Internet of Things Engineering Jiangnan University Wuxi214122 China The Department of Electronic Engineering State Key laboratory of Space Network and Communications Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China The Department of Computer Science Brunel University Middlesex LondonUB8 3PH United Kingdom The State Key Lab. of ISN School of Telecommunications Engineering Xidian University Xi’an710071 China The Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China Hong Kong

On-ramp merging presents a critical challenge in autonomous driving, as vehicles from merging lanes need to dynamically adjust their positions and speeds while monitoring traffic on the main road to prevent collisions. To address this challenge, we propose a novel merging control scheme based on reinforcement learning, which integrates lateral control mechanisms. This approach ensures the smooth integration of vehicles from the merging lane onto the main road, optimizing both fuel efficiency and passenger comfort. Furthermore, we recognize the impact of vehicle-to-vehicle (V2V) communication on control strategies and introduce an enhanced protocol leveraging Cellular Vehicle-to-Everything (C-V2X) Mode 4. This protocol aims to reduce the Age of Information (AoI) and improve communication reliability. In our simulations, we employ two AoI-based metrics to rigorously assess the protocol's effectiveness in autonomous driving scenarios. By combining the NS3 network simulator with Python, we simulate V2V communication and vehicle control simultaneously. The results demonstrate that the enhanced C-V2X Mode 4 outperforms the standard version, while the proposed control scheme ensures safe and reliable vehicle operation during on-ramp merging. Copyright © 2025, The Authors. All rights reserved.

关键词： Problem oriented languages

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Uplink Control Information Based Clustered Access and Discontinuous Reception Management for mMTC

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IEEE Communications Letters 2025年

作者： Wang, Shao-Di Wang, Chang-Long Wang, Hui-Ming Zhou, Feng Leung, Victor C. M. Xidian University Key Laboratory of Electronic Information Countermeasure and Simulation Technology of Ministry of Education Xi’an710071 China Xi’an Jiaotong University School of Information and Communication Engineering Ministry of Education Key Lab for Intelligent Networks and Network Security Xi’an710049 China Shenzhen MSU BIT University Artificial Intelligence Research Institute Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

Uplink control information (UCI) and discontinuous reception (DRX) play important roles for massive machine type communication (mMTC). Despite their standalone significance, a conspicuous gap exists in comprehensively exploring the synergy between UCI and DRX concerning both energy conservation and latency reduction for mMTC. In this letter, we propose a UCI-based clustered access and DRX management (UCADM) scheme that strikes a balance between these two critical performance metrics, reducing energy usage while preserving low latency in uplink-downlink interaction for mMTC. Specifically, we present a strictly feasible solution for the proposed UCADM scheme by using the spectral radius and the constraint projection, which can effectively solve DRX switching operations as indicated by scheduling information from UCI. Simulation results confirm the effectiveness of our scheme. © 1997-2012 IEEE.

关键词： Information management

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A rejection sampling algorithm for off-centered discrete Gaussian distributions over the integers

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science China(Information sciences) 2019年第3期62卷 196-198页

作者： Yusong DU Baodian WEI Huang ZHANG School of Data and Computer Science Sun Yat-sen University Guangdong Key Laboratory of Information Security Technology Chongqing Key Lab of Computer Network and Communication Technology

Dear editor,Discrete Gaussian sampling, that is, sampling from a discrete Gaussian distribution DΛ,σ,cwith parameter σ> 0 and center c∈R~n over an ndimensional lattice Λ, has been considered by the cryptography research community as one of the fundamental building blocks of lattice-based cryptography [1, 2]. The simplest lattice is the one-

关键词： A rejection sampling algorithm for off-centered discrete Gaussian distributions over the integers

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Interactive Evolutionary Multi-Objective Optimization Algorithm Using Cone Dominance

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Journal of Harbin Institute of technology(New Series) 2015年第6期22卷 76-84页

作者： Dalaijargal Purevsuren Saif ur Rehman Gang Cui Jianmin Bao Nwe Nwe Htay Win School of Computer Science and Technology Harbin Institute of Technology Key Lab of Broadband Wireless Communication and Sensor Network Technology (Jiangsu Provincial Engineering Research Center of Telecommunications and Network Technology) Ministry of Education

As the number of objectives increases,the performance of the Pareto dominance-based Evolutionary Multi-objective Optimization( EMO) algorithms such as NSGA-II,SPEA2 severely deteriorates due to the drastic increase in the Pareto-incomparable solutions. We propose a sorting method which classifies these incomparable solutions into several ordered classes by using the decision maker's( DM) preference *** is accomplished by designing an interactive evolutionary algorithm and constructing convex cones. This method allows the DMs to drive the search process toward a preferred region of the Pareto optimal front. The performance of the proposed algorithm is assessed for two,three,and four-objective knapsack problems. The results demonstrate the algorithm ' s ability to converge to the most preferred point. The evaluation and comparison of the results indicate that the proposed approach gives better solutions than that of NSGA-II. In addition,the approach is more efficient compared to NSGA-II in terms of the number of generations required to reach the preferred point.

关键词： multi-objective optimization evolutionary optimization preference information pareto dominance cone dominance

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DPNet: Dynamic Pooling network for Accurate and Efficient Size-Aware Tiny Object Detection

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IEEE Internet of Things Journal 2025年

作者： Gong, Luqi Chen, Haotian Chen, Yikun Yao, Tianliang Li, Chao Zhao, Shuai Han, Guangjie Beijing University of Posts and Telecommunications School of Computer Science Beijing China Zhejiang Lab Research Center for Space Computing System Hangzhou China Southwest Jiaotong University SWJTU-LEEDS Joint School Chengdu China LTD Guangdong Zhiyun City construction Technology Co Zhuhai China Tongji University College of Electronic and Information Engineering Department of Control Science and Engineering Shanghai China Hohai University Key Laboratory of Maritime Intelligent Network Information Technology Ministry of Education China

In unmanned aerial systems, especially in complex environments, accurately detecting tiny objects is crucial. Resizing images is a common strategy to improve detection accuracy, particularly for small objects. However, simply enlarging images significantly increases computational costs and the number of negative samples, severely degrading detection performance and limiting its applicability. This paper proposes a Dynamic Pooling network (DPNet) for tiny object detection to mitigate these issues. DPNet employs a flexible down-sampling strategy by introducing a factor (df) to relax the fixed down-sampling process of the feature map to an adjustable one. Furthermore, we design a lightweight predictor to predict df for each input image, which will be used to decrease the resolution of feature map in backbone. Thus, we achieve input-aware down-sampling. We design an Adaptive Normalization Module (ANM) to make a unified detector well compatible with different dfs. At the same time, we also design a guidance loss to supervise the predictor’s training. DPNet realizes the dynamic allocation of computing resources to trade off detection accuracy and efficiency through this. Experiments on the TinyCOCO and TinyPerson datasets show that our DPNet can save over 35% and 25% GFLOPs, respectively, while maintaining comparable detection *** code will be made publicly available. © 2014 IEEE.

关键词： Object detection

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Semantic QoS Ontology and Semantic Service Ranking Approach for IoT services

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Journal of Harbin Institute of technology(New Series) 2014年第6期21卷 102-112页

作者： Nwe Nwe Htay Win Jian-Min Bao Gang Cui Purevsuren Dalaijargal School of Computer Science and Technology Harbin Institute of Technology Key Lab of Broadband Wireless Communication and Sensor Network Technolog Jiangsu Provincial Engineering Research Center of Telecommunications and Network TechnologyMinistry of Education

Due to a rapid increase in the number of functionally equivalent web services at open and dynamic Io T service environment,Qo S has become a major discrimination factor to reflect the user's expectation and experience of using a *** are different languages and models for expressing Qo S advertisements and requirements among service providers and ***,it leads to the issues of semantic interoperability of Qo S information and semantic similarity match between a semantic description of the service being requested by the service consumer,and a formal description of the service being offered by the service *** this paper,we propose a hierarchical two-layer semantic Qo S ontology to promote the description and declaration of Qo S-based service information in detail for any domain and ***,we develop a semantic matchmaking algorithm to compare the web services according to their Qo S information and adopt analytical hierarchy process( AHP) to make decision for the ranked services depending on the Qo S *** comparison study and experimental result show that our proposed system is superior to other service ranking approaches.

关键词： IoT service environment semantic QoS ontology semantic matchmaking algorithm QoS-based service information analytical hierarchy process

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