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检索条件"任意字段=Third International Conference on Computer Network and Mobile Computing, ICCNMC 2005"

共 1715 条记录，以下是1-10 订阅

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Research on computer Cloud Intelligent System Based on Intelligent Virtualization Technology 3

Research on Computer Cloud Intelligent System Based on Intel...

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3rd IEEE international conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Shi, Qingfeng Zhao, Fei College of Physical Education Taishan University Tai'an271000 China Zibo High-sports Industry Development Zone Education and Sports Center Zibo City China

ISBN: (纸本)9798350380989

This paper is mainly the smart home system and some other intelligent devices and robot technology organic integration together, so that it can be more comprehensive for the robot service. At the same time, computer cloud computing technology is also integrated with the API of other third-party cloud computing platforms, so that it has more business capabilities. The goal of computer cloud computing architecture is to improve the computing and storage performance of robots with the help of massive data. The integration of third-party cloud computing services with intelligent hardware technology expands the resources and business functions of robots. By using cloud computing simulation technology, the inconsistency between observer and predictor is corrected, and a new cloud computing predictive control algorithm is designed to effectively suppress complex network attacks. Secondly, the D cloud computing system with predictive control mechanism is modeled, and the state convergence criterion in D cloud computing is established by using Lyapunov stability theory and LMI theory. Through remote operation of mobile terminals, the collaboration between mobile terminals based on cloud computing and third-party clouds is realized. © 2024 IEEE.

关键词： in the clouds service framework service model Virtualization

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Cloud-network Resource Scheduling for ONAP-Based IDN 1

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13th international conference on computer Engineering and networks (CENet)

作者： Li, Xiangning Cai, Yuqian Wu, Ruotong Tian, Jingyue China Telecom Beijing Res Inst Beijing Peoples R China

ISBN: (数字)9789819992478

ISBN: (纸本)9789819992492;9789819992478;9789819992461

In the 5G and 5G+ scenario, a large number of devices access to the network and a large number of different services are demanded by different vertical industries. To maintain the QoS and satisfy such a lot of demands, MEC (mobile edge computing) deployment and IDN (Intent-Driven network) scheduling are necessary. MEC could upload the third-part App to the cloud servers, which could save the calculate force in the local UE (user equipment). And IDN could identity and integrate UE intents in natural language and translate them into cloud-network scheduling policy to implement them and manage cloud-network resources. ONAP as the platform for orchestrating, manages and automating network and edge computing services. This paper introduces the intent instance management model of ONAP and IDN, introduces the MEC, containers and slices management and designs intent-and-resource -weighted algorithms to make the policies and ensure the QoS.

关键词： 5G IDN ONAP Cloud-network Cloud resource management Slice management

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mobile resources big data deduplication and offloading algorithm based on new computing network architecture 3

Mobile resources big data deduplication and offloading algor...

引用

3rd international conference on Intelligent computing and Human-computer Interaction, ICHCI 2022

作者： Xiong, Qi Computer and Information Engineering Guangzhou Huali College Guangzhou511325 China

ISBN: (纸本)9781510661301

The big data of mobile resources under the new computing network architecture is repetitive and redundant, which leads to poor classification in the process of data scheduling and detection. In order to reduce the error rate of big data deduplication and unloading of mobile resources under the new computing network architecture, a new method of big data deduplication and unloading of mobile resources under the new computing network architecture based on redundant data elimination is proposed. Autocorrelation matched filter detection model is used to filter redundant data and suppress symbol interval interference on the prior features of mobile resource big data under the new computing network architecture with random sampling, and the clustering convergence characteristic parameters of mobile resource big data under the new computing network architecture are extracted by using sample fuzzy regression analysis and least squares sample block fusion detection method. The constrained evolution method of multi-level iterative regression analysis is used to estimate the classification features of mobile resources big data under the new computing network framework. The classification target features are input into the BP neural network classifier, and the adaptive weight distribution control of BP neural network classification is carried out by combining the adaptive clustering center optimization control algorithm, which improves the adaptability of data classification and realizes the unloading of mobile resources big data under the new computing network framework. The simulation results show that the algorithm can effectively reduce the interference of redundant data, and the fidelity rate of data classification is high and the error rate is low, which improves the dynamic management ability of mobile resource data under the new computing network architecture. © 2023 SPIE.

关键词： network architecture

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A lightweight and fast style transfer method for mobile terminals 3

A lightweight and fast style transfer method for mobile term...

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3rd international conference on Electronic Information Engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Su, Rijian Ma, Haoshen Chi, Shihao Wang, Yuefeng Yang, Xianglong School of Computer Science and Technology Zhengzhou University of Light Industry Zhengzhou450001 China

ISBN: (纸本)9781510680449

Style transfer methods based on deep learning usually have problems such as high memory usage and large computing resource requirements, which limit their application on mobile devices. To address this problem, this paper proposes a lightweight and fast style transfer algorithm for mobile terminals. The method first introduces a consistency loss to enhance the robustness of the generated stylized images to input image changes. Secondly, depth-separable convolution is used in the residual block instead of standard convolution to effectively reduce model parameters and improve computational efficiency. Experimental results show that the proposed method can not only generate high-quality stylized results, but also significantly reduce memory usage and greatly improve computational efficiency, providing an important reference for the deployment of deep neural network models to mobile terminals. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Convolution

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Cloud-network resource management based on IDN and ONAP 4

Cloud-network resource management based on IDN and ONAP

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4th international conference on computer Science and Communication Technology, ICCSCT 2023

作者： Li, Jun Wang, Jianxiu Li, Xiangning China Telecom Beijing100024 China

ISBN: (纸本)9781510671232

With the rapid development of 5G, networks are moving towards ubiquity, sharing, and intelligence. Traditional networks suffer from the problem of not being able to schedule routes accurately. The advent of intent-driven network (IDN) has made the network more flexible and efficient. IDN could identify and integrate UE intents in natural language and translate them into cloud network scheduling policy to manage cloud-network resources on the ONAP (Open network Automation Platform), which is the platform for managing and automating network and edge computing services. To satisfy a lot of different demands, ONAP and IDN scheduling are necessary. MEC cloudifies the third-part App and saves the calculated resources in the local UE (user equipment). This paper introduces the containers and slices management, components of ONAP and IDN, introduces the MEC (mobile edge computing), and designs the procedure to manage the cloud-network user intent instances. © 2023 SPIE.

关键词： mobile edge computing

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Time Optimal Distance-k-Dispersion on Dynamic Ring 25

Time Optimal Distance-k-Dispersion on Dynamic Ring

引用

26th international conference on Distributed computing and networking, ICDCN 2025

作者： Mondal, Brati Goswami, Pritam Sau, Buddhadeb Department of Mathematics Jadavpur University Kolkata India Department of Computer Science and Engineering Sister Nivedita University Kolkata India

ISBN: (纸本)9798400710629

In the problem of Dispersion by mobile robots, l robots placed arbitrarily on nodes of a network having n nodes are asked to relocate themselves autonomously so that each node contains at most ⌈l/n⌉ robots. When l ≤ n, each node of the network contains at most one robot. In this work, dispersion has been considered by introducing another variant called Distance-k-Dispersion (D-k-D), where the robots have to disperse on a network in such a way that the shortest distance between any two pairs of robots is at least k and there exist at least one pair of robots for which the shortest distance is exactly k for a dynamic ring (1-interval connected ring) for rooted initial configuration. Note that, when k = 1 we have normal dispersion, and when k = 2 we have Distance-2-Dispersion (D-2-D). We have proved the necessity of fully synchronous scheduler to solve this problem and provided an algorithm that solves (n) rounds under a fully synchronous scheduler. So, the presented algorithm is time-optimal too. To the best of our knowledge, this is the first work that considers this specific variant. © 2025 Copyright held by the owner/author(s).

关键词： mobile robots

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Data mining of encrypted network traffic for adult content and gambling Android applications 3

Data mining of encrypted network traffic for adult content a...

引用

3rd international conference on Electronic Information Engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Wang, Luhua Ning, Zhengyao Cheng, Yanan Li, Yitao Zhang, Zhaoxin The National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing China Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9781510680449

With the advancement of mobile computing technology, there has been a rampant increase in mobile-based pornography, gambling, and scams in the recent past, leading to deception and loss of personal property, resulting in serious societal and legal issues. Therefore, we decided to investigate adult and gambling applications, discover, and analyze their encrypted traffic characteristics. We crawled a massive database of malicious domains and automatically downloaded data, including 687 gambling applications and 334 adult Android applications. This paper presents an empirical research study based on the real traffic of mobile pornography and gambling applications, delving into data mining and analyzing their traffic characteristics at the packet and session flow levels. As these applications involve the dissemination of adult content and scams, running them on an emulator and collecting traffic files does not constitute a violation of privacy. Through quantitative analysis of the encrypted traffic features of such applications, this research aims to provide assistance in the identification and classification of adult and gambling applications and related tasks. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Data mining

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Applying Johnson's Algorithm for Efficient Shortest Path Analysis in Big Data 6

Applying Johnson's Algorithm for Efficient Shortest Path Ana...

引用

6th international conference on mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Mohankumar, N. Reddy, P.L. Kishan Kumar Uthayakumar, C. Parkavi, S. Rajmohan, M. Srinivasan, C. Maharastra Pune India Andhra Pradesh Guntur India Department of Electronics and Communication Engineering Vivekanandha College of Engineering For Women Tamil Nadu Tiruchengode India Department of Computer Science and Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering College Tamil Nadu Chennai India Department of Electronics and Communication Engineering Hindustan Institute of Technology and Science Tamil Nadu Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798331522667

In this paper, Johnson's Algorithm is employed for Big Data shortest route analysis. Its efficiency and efficacy in managing massive datasets to improve data processing and decision-making is studied. To solve big dataset’s computing problems, Johnson's Algorithm, which efficiently finds shortest routes in networks with negative edge weights, is used. This method optimizes route analysis operations in Big Data settings to extract insights faster and more accurately. The study shows Johnson's Algorithm's viability and advantages in big data analytics, possibly enabling its use in network routing, transportation optimization, and social network analysis. Three cases are shown in Sample City Distance Matrix data. The initial Original Distance Matrix data was collected in a random sample of 5 cities and showed a 10-43 km range. In the second Reweighted Matrix with Potential Values instance, data from 5 random cities was collected to calculate the shortest route with a minimum and maximum km of 5-30 km. The data from the third Final Shortest Path Matrix in a random sample of 5 cities is relevant for transportation planning and network optimization with a minimum and maximum distance of -3 and -21 kilometers. © 2025 IEEE.

关键词： Data accuracy

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Secrecy energy efficiency maximization in D2D-enabled MEC networks: a GNN-based approach 3

Secrecy energy efficiency maximization in D2D-enabled MEC ne...

引用

3rd international conference on Electronic Information Engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Hu, Jingying Zhang, Zhifei Ge, Yiyang Mao, Jin Chu, Zhipeng Xiong, Ke Fan, Pingyi Eng. Res. Center of Network Management Technology for High Speed Railway of Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Collaborative Innovation Center of Railway Traffic Safety Beijing Jiaotong University Beijing100044 China National Engineering Research Center of Advanced Network Technologies Beijing Jiaotong University Beijing100044 China Department of Electronic Engineering Tsinghua University Beijing100084 China

ISBN: (纸本)9781510680449

This paper investigates the device-to-device (D2D)-enabled mobile edge computing (MEC) network, where multiple users offload their tasks to an MEC server or their paired devices for computing. In such a network, secrecy and green communication requirements are crucial due to the presence of potential eavesdroppers and the energy demands of global carbon emissions. To this end, a secrecy energy efficiency (SEE) maximization problem is formulated by jointly optimizing the computation frequency at users, the transmit power at users and the subchannel assignments, subject to the quality of service (QoS) and the available energy constraints. To solve the formulated non-convex mixed-integer nonlinear programming problem, a graph neural networks (GNNs) and genetics based resource allocation (GGRA) method is presented, where the communication system is modelled as a directed graph with relationships among users as edges. In order to enhance the ability to process users' own features and handle deep data patterns, self-loops and the ResNet blocks in convolutions and the genetics based optimization are employed. Simulations show that the proposed GGRA improves SEE performance by about 40% compared with the traditional GNN-based method with the same energy budget. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Energy efficiency

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Digital Precision Marketing Strategy of Consumer Goods Based on mobile Internet 3

Digital Precision Marketing Strategy of Consumer Goods Based...

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3rd international conference on Intelligent computing and Human-computer Interaction, ICHCI 2022

作者： Hu, Yuehang Research and Development of Centre of China Tobacco Yunnan Industrial Co. Ltd. Kunming650231 China

ISBN: (纸本)9781510661301

Due to the rapid product market cycle in the consumer goods industry, the development of digital technology has promoted the market layout of consumer goods. It is necessary to carry out brand publicity and strategy research by means of big data, the Internet of Things, 5G and other digital means, and form interactive communication with consumers. With the popularization and application of mobile Internet and mobile terminal equipment, great changes have taken place in people ' s consumption behavior and information acquisition mode. Marketing technology and methods have changed from offline to online. Through the current situation analysis and data research, this paper puts forward new ideas and opinions on the digitalization of marketing from the aspects of business model innovation, precision marketing and data security, and studies the digital practice research of online network, product tracking and user information management, so as to improve the digital network of deep integration among enterprises, products and consumers. © 2023 SPIE.

关键词： Marketing

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