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A Self-Attention Based Dynamic resource management for Satellite-Terrestrial Networks

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China Communications 2024年第4期21卷 136-150页

作者： Lin Tianhao Luo Zhiyong School of Electronics and Communication Engineering Sun Yat-Sen UniversityShenzhen 518107China Peng Cheng Laboratory Shenzhen 518107China

The satellite-terrestrial networks possess the ability to transcend geographical constraints inherent in traditional communication networks,enabling global coverage and offering users ubiquitous computing power support,which is an important development direction of future *** this paper,we take into account a multi-scenario network model under the coverage of low earth orbit(LEO)satellite,which can provide computing resources to users in faraway areas to improve task processing ***,LEO satellites experience limitations in computing and communication resources and the channels are time-varying and complex,which makes the extraction of state information a daunting ***,we explore the dynamic resource management issue pertaining to joint computing,communication resource allocation and power control for multi-access edge computing(MEC).In order to tackle this formidable issue,we undertake the task of transforming the issue into a Markov decision process(MDP)problem and propose the self-attention based dynamic resource management(SABDRM)algorithm,which effectively extracts state information features to enhance the training *** results show that the proposed algorithm is capable of effectively reducing the long-term average delay and energy consumption of the tasks.

关键词： mobile edge computing resource management satellite-terrestrial networks self-attention

Fog-computing based mobility and resource management for resilient mobile networks

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High-Confidence Computing

High-Confidence Computing 2024年第2期4卷 145-151页

作者： Hang Zhao Shengling Wang Hongwei Shi School of Artificial Intelligence Beijing Normal UniversityBeijing 100875China

Mobile networks are facing unprecedented challenges due to the traits of large scale,heterogeneity,and high ***,the emergence of fog computing offers surprisingly perfect solutions considering the features of consumer proximity,wide-spread geographical distribution,and elastic resource *** this paper,we propose a novel mobile networking framework based on fog computing which outperforms others in *** scheme is constituted of two parts:the personalized customization mobility management(MM)and the market-driven resource management(RM).The former provides a dynamically customized MM framework for any specific mobile node to optimize the handoff performance according to its traffic and mobility traits;the latter makes room for economic tussles to find out the competitive service providers offering a high level of service quality at sound ***,our proposed MM and RM schemes can holistically support a full-fledged resilient mobile network,which has been practically corroborated by numerical experiments。

关键词： Resilient mobile networking Fog computing Mobility management resource management

resource management and job scheduling of China earthquake grid experiment system: Construction of resource management and job dynamic scheduling model ProRMJS

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Acta Seismologica Sinica(English Edition) 2006年第6期19卷 695-703页

作者：侯建民刘瑞丰单保华赵永牛爱军邹立晔侯立华韩军 China Earthquake Networks Center Beijing 100036 China Institute of Computing Technology Chinese Academy of SciencesBeijing 100080 China The Second Academy of China-Aerospace Science and Industry Corporation Beijing 100854 China

Grid technique is taken as the third generation internet technology and resource management is the core of it. Aiming at the problems of resource management of CEDAGrid （China Earthquake Disaster Alleviation and Simulation Grid） in its preliminary construction, this paper presents a resource management and job scheduling model： ProRMJS to solve these problems. For platform supposed agreeably each computing node can provide computation service, ProRMJS uses ＂computation pool＂ to support scheduler, and then the scheduler allocates jobs dynamically according to computing capability and status of each node to ensure the stability of the platform. At the same time, ProRMJS monitors the status of job on each node and sets a time threshold to manage the job scheduling. By estimating the computing capability of each node, ProRMJS allocates jobs on demand to solve the problem of supposing each node can finish the job acquiescently. When calculating the computing capability of each node, ProRMJS allows for the various factors that affect the computing capability and then the efficiency of the platform is improved. Finally the validity of the model is verified by an example.

关键词： grid computing earthquake grid resource management job allocation

resource management in radio access and IP-based core networks for IMT Advanced and Beyond

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Science China(Information Sciences) 2013年第2期56卷 102-117页

作者： SU Gang HIDELL Markus ABRAHAMSSON Henrik AHLGREN Bengt LI Dan SJDIN Peter TANYINGYONG Voravit XU Ke Department of Electronics and Information Engineering Huazhong University of Science and Technology School of Information and Communication Technology KTH Royal Institute of Technology

The increased capacity needs, primarily driven by content distribution, and the vision of Internet-of-Things with billions of connected devices pose radically new demands on future wireless and mobile systems. In general the increased diversity and scale result in complex resource management and optimization problems in both radio access networks and the wired core network infrastructure. We summarize results in this area from a collaborative Sino-Swedish project within IMT Advanced and Beyond, covering adaptive radio resource management, energy-aware routing, OpenFlow-based network virtualization, data center networking, and access network caching for TV on demand.

关键词： IMT Advanced and Beyond resource management resource optimization traffic engineering network virtualization

Self-Adaptive resource management for Large-Scale Shared Clusters

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Journal of Computer Science & Technology 2010年第5期25卷 945-957页

作者：李研陈峰宏孙熙周明辉焦文品曹东刚梅宏 Key Laboratory of High Confidence Software Technologies Ministry of EducationInstitute of Software School of Electronics Engineering and Computer SciencePeking University CCF

In a shared cluster,each application runs on a subset of nodes and these subsets can overlap with one another. resource management in such a cluster should adaptively change the application placement and workload assignment to satisfy the dynamic applications workloads and optimize the resource *** becomes a challenging problem with the cluster scale and application amount growing *** paper proposes a novel self-adaptive resource management approach which is inspired from human market：the nodes trade their shares of applications＇ requests with others via auction and bidding to decide its own resource allocation and a global high-quality resource allocation is achieved as an emergent collective behavior of the *** results show that the proposed approach can ensure quick responsiveness, high scalability,and application prioritization in addition to managing the resources effectively.

关键词： distributed system resource management self-adaptation shared cluster

A survey of cloud resource management for complex engineering applications

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Frontiers of Computer Science 2016年第3期10卷 447-461页

作者： Haibao CHEN Song WU Hai JIN Wenguang CHEN Jidong ZHAI Yingwei LUO Xiaolin WANG Services Computing Technology and System Lab Cluster and Grid Computing LabSchool of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China Institute of High Performance Computing Tsinghua University Beijing 100084 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China School of Computer and Information Engineering Chuzhou University Chuzhou 239000 China

Traditionally, complex engineering applications （CEAs）, which consist of numerous components （software） and require a large amount of computing resources, usu- ally run in dedicated clusters or high performance computing （HPC） centers. Nowadays, Cloud computing system with the ability of providing massive computing resources and cus- tomizable execution environment is becoming an attractive option for CEAs. As a new type on Cloud applications, CEA also brings the challenges of dealing with Cloud resources. In this paper, we provide a comprehensive survey of Cloud resource management research for CEAs. The survey puts forward two important questions： 1） what are the main chal- lenges for CEAs to run in Clouds？ and 2） what are the prior research topics addressing these challenges？ We summarize and highlight the main challenges and prior research topics. Our work can be probably helpful to those scientists and en- gineers who are interested in running CEAs in Cloud envi- ronment.

关键词： Cloud computing complex engineering application resource management virtualization

Energy-efficient resource management for CCFD massive MIMO systems in 6G networks

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Journal of Systems Engineering and Electronics 2022年第4期33卷 877-886页

作者： SU Yumeng GAO Hongyuan ZHANG Shibo College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China

This paper presents a co-time co-frequency fullduplex(CCFD)massive multiple-input multiple-output(MIMO)system to meet high spectrum efficiency requirements for beyond the fifth-generation(5G)and the forthcoming the sixth-generation(6G)*** achieve equilibrium of energy consumption,system resource utilization,and overall transmission capacity,an energy-efficient resource management strategy concerning power allocation and antenna selection is designed.A continuous quantum-inspired termite colony optimization(CQTCO)algorithm is proposed as a solution to the resource management considering the communication reliability while promoting energy conservation for the CCFD massive MIMO *** effectiveness of CQTCO compared with other algorithms is evaluated through *** results reveal that the proposed resource management scheme under CQTCO can obtain a superior performance in different communication scenarios,which can be considered as an eco-friendly solution for promoting reliable and efficient communication in future wireless networks.

关键词： the sixth-generation(6G) massive multiple-input multiple-output(MIMO) co-time co-frequency full-duplex energy-efficient resource management

A Game-Theoretic Perspective on resource management for Large-Scale UAV Communication Networks

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China Communications 2021年第1期18卷 70-87页

作者： Jiaxin Chen Ping Chen Qihui Wu Yuhua Xu Nan Qi Tao Fang Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information TechnologyCollege of Electronic and Information EngineeringNanjing University of Aeronautics and AstronauticsNanjing 211106China State Key Laboratory of Air Traffic management System and Technology Nanjing 210014China th Research Institute of China Electronics Technology Group Corporation Nanjing 210007China College of Communications Engineering Army Engineering University of PLANanjing 210007China

As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated *** it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved ***,due to the inherent requirements and future development trend,distributed resource management is *** this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous *** exploring the inherent features,the distinctive challenges are ***,we explore several gametheoretic models that not only combat the challenges but also have broad application *** provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication ***,mean-field game,graphical game,Stackelberg game,coalition game and potential game are *** that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic ***,we give some future research directions to shed light on future opportunities and applications.

关键词： large-scale UAV communication networks resource management game-theoretic model

Edge Intelligence Assisted resource management for Satellite Communication

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China Communications 2022年第8期19卷 31-40页

作者： Yaohua Sun Mugen Peng State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

Satellite communication has been seen as a vital part of the sixth generation communication,which greatly extends network *** satellite communication,resource management is a key problem attracting many research ***,previous study mainly focuses on throughput improvement via power allocation and spectrum assignment and the proposed approaches are mostly model-based and dedicated to specific problem ***,with the trend of edge intelligence,complex resource management problems can be efficiently resolved in a model-free *** this paper,a joint beam activation,user-beam association and time resource allocation approach is *** core idea is using stochastic learning at the ground station to identify active user-link beams to meet user rate *** addition,the convergence,optimality and complexity of our proposal are rigorously *** simulation,it is shown that the rate goal of most of the users can be met and meanwhile satellite energy is saved owing to much less active beams.

关键词： satellite communication resource management stochastic learning