检索结果-南通市图书馆

Caching Strategies in NDN Based Wireless Ad Hoc Network:A Survey

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

computers, Materials & Continua 2024年第7期80卷 61-103页

作者： Ahmed Khalid Rana Asif Rehman Byung-Seo Kim Department of computer Science FAST School of ComputingNational University of Computer and Emerging SciencesLahore54000Pakistan Department of Software and communications Engineering Hongik UniversitySejong City30016Republic of Korea

Wireless Ad Hoc Networks consist of devices that are wirelessly *** Ad Hoc Networks(MANETs),Internet of Things(IoT),and Vehicular Ad Hoc Networks(VANETs)are the main domains of wireless ad hoc *** is used in wireless ad hoc *** is based on Transmission Control Protocol(TCP)/Internet Protocol(IP)network where clients and servers interact with each other with the help of IP in a pre-defined *** fetches data from a fixed *** redundancy,mobility,and location dependency are the main issues of the IP network *** these factors result in poor performance of wireless ad hoc *** main disadvantage of IP is that,it does not provide in-network ***,there is a need to move towards a new network that overcomes these *** Data Network(NDN)is a network that overcomes these *** is a project of Information-centric Network(ICN).NDN provides in-network caching which helps in fast response to user *** NDN in wireless ad hoc network provides many benefits such as caching,mobility,scalability,security,and *** considering the certainty,in this survey paper,we present a comprehensive survey on Caching Strategies in NDN-based Wireless *** cachingmechanism-based results are also *** the last,we also shed light on the challenges and future directions of this promising field to provide a clear understanding of what caching-related problems exist in NDN-based wireless ad hoc networks.

关键词： Content centric network Internet of Things mobile ad hoc network named data network vehicular ad hoc network

Spatiotemporal Prediction of Urban Traffics Based on Deep GNN

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

computers, Materials & Continua 2024年第1期78卷 265-282页

作者： Ming Luo Huili Dou Ning Zheng school of computer Science Hangzhou Dianzi UniversityHangzhou310018China Zhejiang Institute of communications Hangzhou310012China school of Cyberspace Security Hangzhou Dianzi UniversityHangzhou310018China

Traffic prediction already plays a significant role in applications like traffic planning and urban management,but it is still difficult to capture the highly non-linear and complicated spatiotemporal correlations of traffic *** well as to fulfil both long-termand short-termprediction objectives,a better representation of the temporal dependency and global spatial correlation of traffic data is *** order to do this,the Spatiotemporal Graph Neural Network(S-GNN)is proposed in this research as amethod for traffic *** S-GNN simultaneously accepts various traffic data as inputs and investigates the non-linear correlations between the *** terms of modelling,the road network is initially represented as a spatiotemporal directed graph,with the features of the samples at the time step being captured by a convolution *** order to assign varying attention weights to various adjacent area nodes of the target node,the adjacent areas information of nodes in the road network is then aggregated using a graph *** data is output using a fully connected layer at the *** findings show that S-GNN can improve short-and long-term traffic prediction accuracy to a greater extent;in comparison to the control model,the RMSE of S-GNN is reduced by about 0.571 to 9.288 and the MAE(Mean Absolute Error)by about 0.314 to *** experimental results on two real datasets,Pe MSD7(M)and PEMS-BAY,also support this claim.

关键词： Urban traffic traffic temporal correlation GNN prediction

XRL-SHAP-Cache:an explainable reinforcement learning approach for intelligent edge service caching in content delivery networks

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2024年第7期67卷 46-71页

作者： Xiaolong XU Fan WU Muhammad BILAL Xiaoyu XIA Wanchun DOU Lina YAO Weiyi ZHONG school of Software Nanjing University of Information Science and Technology school of Computing and communications Lancaster University school of Computing Technologies Royal Melbourne Institute of Technology State Key Laboratory for Novel Software Technology Nanjing University school of computer Science and Engineering University of New South Wales Data 61 Commonwealth Scientific and Industrial Research Organization school of computer Science Qufu Normal University

Content delivery networks(CDNs) play a pivotal role in the modern internet infrastructure by enabling efficient content delivery across diverse geographical regions. As an essential component of CDNs, the edge caching scheme directly influences the user experience by determining the caching and eviction of content on edge servers. With the emergence of 5G technology, traditional caching schemes have faced challenges in adapting to increasingly complex and dynamic network environments. Consequently, deep reinforcement learning(DRL) offers a promising solution for intelligent zero-touch network governance. However, the blackbox nature of DRL models poses challenges in understanding and making trusting decisions. In this paper,we propose an explainable reinforcement learning(XRL)-based intelligent edge service caching approach,namely XRL-SHAP-Cache, which combines DRL with an explainable artificial intelligence(XAI) technique for cache management in CDNs. Instead of focusing solely on achieving performance gains, this study introduces a novel paradigm for providing interpretable caching strategies, thereby establishing a foundation for future transparent and trustworthy edge caching solutions. Specifically, a multi-level cache scheduling framework for CDNs was formulated theoretically, with the D3QN-based caching scheme serving as the targeted interpretable model. Subsequently, by integrating Deep-SHAP into our framework, the contribution of each state input feature to the agent's Q-value output was calculated, thereby providing valuable insights into the decision-making process. The proposed XRL-SHAP-Cache approach was evaluated through extensive experiments to demonstrate the behavior of the scheduling agent in the face of different environmental *** results demonstrate its strong explainability under various real-life scenarios while maintaining superior performance compared to traditional caching schemes in terms of cache hit ratio, quality of service(QoS),a

关键词： deep reinforcement learning (DRL) explainable artificial intelligence (XAI) multi-level cache content delivery network (CDN) D3QN algorithm Deep-SHAP

A cost-efficient quantum access network with qubit-based synchronization

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Physics,Mechanics & Astronomy) 2024年第4期67卷 12-22页

作者： Chunfeng Huang Ye Chen Tingting Luo Wenjie He Xin Liu Zhenrong Zhang Kejin Wei Guangxi Key Laboratory for Relativistic Astrophysics School of Physical Science and TechnologyGuangxi UniversityNanning 530004China Guangxi Key Laboratory of Multimedia communications and Network Technology School of Computer Electronics and InformationGuangxi UniversityNanning 530004China

Quantum key distribution(QKD)is a physical layer encryption technique that enables two distant parties to exchange secure keys with information-theoretic *** the last two decades,QKD has transitioned from laboratory research to real-world applications,including multi-user quantum access networks(QANs).This network structure allows users to share a single-photon detector at a network node through time-division multiplexing,thereby significantly reducing the network ***,current QAN implementations require additional hardware for auxiliary tasks such as time *** address this issue,we propose a cost-efficient QAN that uses qubit-based *** this approach,the transmitted qubits facilitate time synchronization,eliminating the need for additional synchronization *** tested our scheme by implementing a network for two users and successfully achieved average secure key rates of 53.84 kbps and 71.90 kbps for each user over a 50-km commercial fiber *** addition,we investigated the capacity of the access network under cross-talk and loss *** simulation results demonstrate that this scheme can support a QAN with 64 users with key rates up to 1070 *** work provides a feasible and cost-effective way to implement a multi-user QKD network,further promoting the widespread application of QKD.

关键词： quantum key distribution quantum access network qubit-based synchronization

维普期刊数据库

ResNeSt-biGRU: An Intrusion Detection Model Based on Internet of Things

在线全文

学校读者我要写书评

暂无评论

computers, Materials & Continua 2024年第4期79卷 1005-1023页

作者： Yan Xiang Daofeng Li Xinyi Meng Chengfeng Dong Guanglin Qin school of computer and Electronics Information Guangxi UniversityNanning530004China Guangxi Colleges and Universities Key Laboratory of Multimedia communications and Information Processing Guangxi UniversityNanning530004China

The rapid expansion of Internet of Things (IoT) devices across various sectors is driven by steadily increasingdemands for interconnected and smart technologies. Nevertheless, the surge in the number of IoT device hascaught the attention of cyber hackers, as it provides them with expanded avenues to access valuable data. Thishas resulted in a myriad of security challenges, including information leakage, malware propagation, and financialloss, among others. Consequently, developing an intrusion detection system to identify both active and potentialintrusion traffic in IoT networks is of paramount importance. In this paper, we propose ResNeSt-biGRU, a practicalintrusion detection model that combines the strengths of ResNeSt, a variant of Residual Neural Network, andbidirectionalGated RecurrentUnitNetwork (biGRU).Our ResNeSt-biGRUframework diverges fromconventionalintrusion detection systems (IDS) by employing this dual-layeredmechanism that exploits the temporal continuityand spatial feature within network data streams, a methodological innovation that enhances detection *** conjunction with this, we introduce the PreIoT dataset, a compilation of prevalent IoT network behaviors, totrain and evaluate IDSmodels with a focus on identifying potential intrusion traffics. The effectiveness of proposedscheme is demonstrated through testing, wherein it achieved an average accuracy of 99.90% on theN-BaIoT datasetas well as on the PreIoT dataset and 94.45% on UNSW-NB15 dataset. The outcomes of this research reveal thepotential of ResNeSt-biGRU to bolster security measures, diminish intrusion-related vulnerabilities, and preservethe overall security of IoT ecosystems.

关键词： Internet of Things cyberattack intrusion detection internet security

Deep Learning and Tensor-Based Multiple Clustering Approaches for Cyber-Physical-Social Applications

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

computers, Materials & Continua 2024年第3期78卷 4109-4128页

作者： Hongjun Zhang Hao Zhang Yu Lei Hao Ye Peng Li Desheng Shi school of computer Science Nanjing University of Posts and TelecommunicationsNanjing210023China China communications Services Co. Ltd.Beijing100071China China communications Services Hexin Science&Technology Co. Ltd.Hefei230031China

The study delves into the expanding role of network platforms in our daily lives, encompassing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Instagram. While these platforms offer avenues for self-expression and community support, they concurrently harbor negative impacts, fostering antisocial behaviors like phishing, impersonation, hate speech, cyberbullying, cyberstalking, cyberterrorism, fake news propagation, spamming, and fraud. Notably, individuals also leverage these platforms to connect with authorities and seek aid during disasters. The overarching objective of this research is to address the dual nature of network platforms by proposing innovative methodologies aimed at enhancing their positive aspects and mitigating their negative repercussions. To achieve this, the study introduces a weight learning method grounded in multi-linear attribute ranking. This approach serves to evaluate the significance of attribute combinations across all feature spaces. Additionally, a novel clustering method based on tensors is proposed to elevate the quality of clustering while effectively distinguishing selected features. The methodology incorporates a weighted average similarity matrix and optionally integrates weighted Euclidean distance, contributing to a more nuanced understanding of attribute importance. The analysis of the proposed methods yields significant findings. The weight learning method proves instrumental in discerning the importance of attribute combinations, shedding light on key aspects within feature spaces. Simultaneously, the clustering method based on tensors exhibits improved efficacy in enhancing clustering quality and feature distinction. This not only advances our understanding of attribute importance but also paves the way for more nuanced data analysis methodologies. In conclusion, this research underscores the pivotal role of network platforms in contemporary society, emp

关键词： Network platform tensor-based clustering weight learning multi-linear euclidean

Distortion-aware beamforming design for multi-beam satellite communications with nonlinear power amplifiers

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2024年第6期67卷 359-369页

作者： Xiang XIAO Li YOU Kezhi WANG Xiqi GAO National Mobile communications Research Laboratory Southeast University Purple Mountain Laboratories Department of computer Science Brunel University London

Hardware components can cause different impairments, including power amplifier(PA) nonlinearities, which inevitably impact the system performance of satellite communications(SATCOM). In this work, we consider a multi-beam SATCOM downlink system and investigate the distortion-aware beamforming scheme with the characteristics of PA non-linearities. Notably, we aim to maximize the resource efficiency(RE), defined as the weighted sum of energy efficiency(EE) with spectral efficiency(SE), to obtain a flexible EE-SE tradeoff while accounting for the characteristics of PA distortion and the total power *** that the optimization objective is a sum of ratios and the high non-convexity involved in constraints,we propose an efficient approach that exploits the quadratic transformation, the Lagrange multiplier method,and the gradient ascent approach to handle this issue. Simulation results demonstrate the effectiveness of the distortion-aware beamforming approach in achieving the EE-SE tradeoff and exhibit a substantial RE performance gain over the conventional approach with ideal linear PAs assumed at the satellite transmitters.

关键词： multi-beam satellite communications nonlinear power amplifier energy and spectral efficiency tradeoff resource efficiency robust beamforming

Formal Verification of Data Modifications in Cloud Block Storage Based on Separation Logic

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2024年第1期33卷 112-127页

作者： Bowen ZHANG Zhao JIN Hanpin WANG Yongzhi CAO Key Laboratory of High Confidence Software Technologies (MOE) School of Computer Science Peking University school of computer and Artificial Intelligence Zhengzhou University school of computer Science and Cyber Engineering Guangzhou University

Cloud storage is now widely used, but its reliability has always been a major concern. Cloud block storage(CBS) is a famous type of cloud storage. It has the closest architecture to the underlying storage and can provide interfaces for other types. Data modifications in CBS have potential risks such as null reference or data *** verification of these operations can improve the reliability of CBS to some extent. Although separation logic is a mainstream approach to verifying program correctness, the complex architecture of CBS creates some challenges for verifications. This paper develops a proof system based on separation logic for verifying the CBS data modifications. The proof system can represent the CBS architecture, describe the properties of the CBS system state, and specify the behavior of CBS data modifications. Using the interactive verification approach from Coq, the proof system is implemented as a verification tool. With this tool, the paper builds machine-checked proofs for the functional correctness of CBS data modifications. This work can thus analyze the reliability of cloud storage from a formal perspective.

关键词： Cloud computing Behavioral sciences Reliability Formal verification

Meta label associated loss for fine-grained visual recognition

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2024年第6期67卷 230-247页

作者： Yanchao LI Fu XIAO Hao LI Qun LI Shui YU school of computer Science Nanjing University of Posts and Telecommunications school of Network Engineering Zhoukou Normal University school of computer Science University of Technology Sydney

Recently, intensive attempts have been made to design robust models for fine-grained visual recognition, most notably are the impressive gains for training with noisy labels by incorporating a reweighting strategy into a meta-learning framework. However, it is limited to up or downweighting the contribution of an instance for label reweighting approaches in the learning process. To solve this issue, a novel noise-tolerant method with auxiliary web data is proposed. Specifically, first, the associations made from embeddings of well-labeled data with those of web data and back at the same class are measured. Next, its association probability is employed as a weighting fusion strategy into angular margin-based loss, which makes the trained model robust to noisy datasets. To reduce the influence of the gap between the well-labeled and noisy web data, a bridge schema is proposed via the corresponding loss that encourages the learned embeddings to be coherent. Lastly, the formulation is encapsulated into the meta-learning framework, which can reduce the overfitting of models and learn the network parameters to be noise-tolerant. Extensive experiments are performed on benchmark datasets, and the results clearly show the superiority of the proposed method over existing state-of-the-art approaches.

关键词： label associated loss weighting noisy samples fine-grained visual recognition noise-tolerant learning meta-learning