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Online Computation Offloading and Trajectory Scheduling for UAV-Enabled Wireless Powered Mobile Edge Computing 被引量:4
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作者 Han Hu Xiang Zhou +1 位作者 Qun Wang Rose Qingyang Hu 《China Communications》 SCIE CSCD 2022年第4期257-273,共17页
The unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) architecture is expected to be a powerful technique to facilitate 5 G and beyond ubiquitous wireless connectivity and diverse vertical applications a... The unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) architecture is expected to be a powerful technique to facilitate 5 G and beyond ubiquitous wireless connectivity and diverse vertical applications and services, anytime and anywhere. Wireless power transfer(WPT) is another promising technology to prolong the operation time of low-power wireless devices in the era of Internet of Things(IoT). However, the integration of WPT and UAV-enabled MEC systems is far from being well studied, especially in dynamic environments. In order to tackle this issue, this paper aims to investigate the stochastic computation offloading and trajectory scheduling for the UAV-enabled wireless powered MEC system. A UAV offers both RF wireless power transmission and computation services for IoT devices. Considering the stochastic task arrivals and random channel conditions, a long-term average energyefficiency(EE) minimization problem is formulated.Due to non-convexity and the time domain coupling of the variables in the formulated problem, a lowcomplexity online computation offloading and trajectory scheduling algorithm(OCOTSA) is proposed by exploiting Lyapunov optimization. Simulation results verify that there exists a balance between EE and the service delay, and demonstrate that the system EE performance obtained by the proposed scheme outperforms other benchmark schemes. 展开更多
关键词 energy efficiency mobile edge computing UAV-enabled wireless power transfer trajectorys cheduling
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Computation Rate Maximization in Multi-User Cooperation-Assisted Wireless-Powered Mobile Edge Computing with OFDMA 被引量:1
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作者 Xinying Wu Yejun He Asad Saleem 《China Communications》 SCIE CSCD 2023年第1期218-229,共12页
In the era of Internet of Things(Io T),mobile edge computing(MEC)and wireless power transfer(WPT)provide a prominent solution for computation-intensive applications to enhance computation capability and achieve sustai... In the era of Internet of Things(Io T),mobile edge computing(MEC)and wireless power transfer(WPT)provide a prominent solution for computation-intensive applications to enhance computation capability and achieve sustainable energy supply.A wireless-powered mobile edge computing(WPMEC)system consisting of a hybrid access point(HAP)combined with MEC servers and many users is considered in this paper.In particular,a novel multiuser cooperation scheme based on orthogonal frequency division multiple access(OFDMA)is provided to improve the computation performance,where users can split the computation tasks into various parts for local computing,offloading to corresponding helper,and HAP for remote execution respectively with the aid of helper.Specifically,we aim at maximizing the weighted sum computation rate(WSCR)by optimizing time assignment,computation-task allocation,and transmission power at the same time while keeping energy neutrality in mind.We transform the original non-convex optimization problem to a convex optimization problem and then obtain a semi-closed form expression of the optimal solution by considering the convex optimization techniques.Simulation results demonstrate that the proposed multi-user cooperationassisted WPMEC scheme greatly improves the WSCR of all users than the existing schemes.In addition,OFDMA protocol increases the fairness and decreases delay among the users when compared to TDMA protocol. 展开更多
关键词 mobile edge computing(mec) wireless power transfer(WPT) user cooperation OFDMA convex optimization
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Age of Information Based User Scheduling and Data Assignment in Multi-User Mobile Edge Computing Networks:An Online Algorithm
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作者 Ge Yiyang Xiong Ke +3 位作者 Dong Rui Lu Yang Fan Pingyi Qu Gang 《China Communications》 SCIE CSCD 2024年第5期153-165,共13页
This paper investigates the age of information(AoI)-based multi-user mobile edge computing(MEC)network with partial offloading mode.The weighted sum AoI(WSA)is first analyzed and derived,and then a WSA minimization pr... This paper investigates the age of information(AoI)-based multi-user mobile edge computing(MEC)network with partial offloading mode.The weighted sum AoI(WSA)is first analyzed and derived,and then a WSA minimization problem is formulated by jointly optimizing the user scheduling and data assignment.Due to the non-analytic expression of the WSA w.r.t.the optimization variables and the unknowability of future network information,the problem cannot be solved with known solution methods.Therefore,an online Joint Partial Offloading and User Scheduling Optimization(JPOUSO)algorithm is proposed by transforming the original problem into a single-slot data assignment subproblem and a single-slot user scheduling sub-problem and solving the two sub-problems separately.We analyze the computational complexity of the presented JPO-USO algorithm,which is of O(N),with N being the number of users.Simulation results show that the proposed JPO-USO algorithm is able to achieve better AoI performance compared with various baseline methods.It is shown that both the user’s data assignment and the user’s AoI should be jointly taken into account to decrease the system WSA when scheduling users. 展开更多
关键词 age of information(aoi) mobile edge computing(mec) user scheduling
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Energy Minimization for Heterogenous Traffic Coexistence with Puncturing in Mobile Edge Computing-Based Industrial Internet of Things
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作者 Wang Xue Wang Ying +1 位作者 Fei Zixuan Zhao Junwei 《China Communications》 SCIE CSCD 2024年第10期167-180,共14页
Puncturing has been recognized as a promising technology to cope with the coexistence problem of enhanced mobile broadband(eMBB) and ultra-reliable low latency communications(URLLC)traffic. However, the steady perform... Puncturing has been recognized as a promising technology to cope with the coexistence problem of enhanced mobile broadband(eMBB) and ultra-reliable low latency communications(URLLC)traffic. However, the steady performance of eMBB traffic while meeting the requirements of URLLC traffic with puncturing is a major challenge in some realistic scenarios. In this paper, we pay attention to the timely and energy-efficient processing for eMBB traffic in the industrial Internet of Things(IIoT), where mobile edge computing(MEC) is employed for data processing. Specifically, the performance of eMBB traffic and URLLC traffic in a MEC-based IIoT system is ensured by setting the threshold of tolerable delay and outage probability, respectively. Furthermore,considering the limited energy supply, an energy minimization problem of eMBB device is formulated under the above constraints, by jointly optimizing the resource blocks(RBs) punctured by URLLC traffic, data offloading and transmit power of eMBB device. With Markov's inequality, the problem is reformulated by transforming the probabilistic outage constraint into a deterministic constraint. Meanwhile, an iterative energy minimization algorithm(IEMA) is proposed.Simulation results demonstrate that our algorithm has a significant reduction in the energy consumption for eMBB device and achieves a better overall effect compared to several benchmarks. 展开更多
关键词 energy minimization enhanced mobile broadband(eMBB)and ultra-reliable low latency communications(URLLC)coexistence industrial Internet of Things(IIoT) mobile edge computing(mec) PUNCTURING
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Mobile Edge Communications, Computing, and Caching(MEC3) Technology in the Maritime Communication Network 被引量:18
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作者 Jie Zeng Jiaying Sun +1 位作者 Binwei Wu Xin Su 《China Communications》 SCIE CSCD 2020年第5期223-234,共12页
With the increasing maritime activities and the rapidly developing maritime economy, the fifth-generation(5G) mobile communication system is expected to be deployed at the ocean. New technologies need to be explored t... With the increasing maritime activities and the rapidly developing maritime economy, the fifth-generation(5G) mobile communication system is expected to be deployed at the ocean. New technologies need to be explored to meet the requirements of ultra-reliable and low latency communications(URLLC) in the maritime communication network(MCN). Mobile edge computing(MEC) can achieve high energy efficiency in MCN at the cost of suffering from high control plane latency and low reliability. In terms of this issue, the mobile edge communications, computing, and caching(MEC3) technology is proposed to sink mobile computing, network control, and storage to the edge of the network. New methods that enable resource-efficient configurations and reduce redundant data transmissions can enable the reliable implementation of computing-intension and latency-sensitive applications. The key technologies of MEC3 to enable URLLC are analyzed and optimized in MCN. The best response-based offloading algorithm(BROA) is adopted to optimize task offloading. The simulation results show that the task latency can be decreased by 26.5’ ms, and the energy consumption in terminal users can be reduced to 66.6%. 展开更多
关键词 best response-based offloading algorithm(BROA) energy consumption mobile edge computing(mec) mobile edge communications computing and caching(mec3) task offloading
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An Energy Efficient Design for UAV Communication With Mobile Edge Computing 被引量:10
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作者 Lingyan Fan Wu Yan +2 位作者 Xihan Chen Zhiyong Chen Qingjiang Shi 《China Communications》 SCIE CSCD 2019年第1期26-36,共11页
This paper considers a UAV communication system with mobile edge computing(MEC).We minimize the energy consumption of the whole system via jointly optimizing the UAV's trajectory and task assignment as well as CPU... This paper considers a UAV communication system with mobile edge computing(MEC).We minimize the energy consumption of the whole system via jointly optimizing the UAV's trajectory and task assignment as well as CPU's computational speed under the set of resource constrains.To this end,we first derive the energy consumption model of data processing,and then obtain the energy consumption model of fixed-wing UAV's flight.The optimization problem is mathematically formulated.To address the problem,we first obtain the approximate optimization problem by applying the technique of discrete linear state-space approximation,and then transform the non-convex constraints into convex by using linearization.Furthermore,a concave-convex procedure(CCCP) based algorithm is proposed in order to solve the optimization problem approximately.Numerical results show the efficacy of the proposed algorithm. 展开更多
关键词 mobile edge computing(mec) UAV COMMUNICATION concave-convex procedure(CCCP) energy minimization
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Mobile Edge Computing and Field Trial Results for 5G Low Latency Scenario 被引量:7
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作者 Jianmin Zhang Weiliang Xie +1 位作者 Fengyi Yang Qi Bi 《China Communications》 SCIE CSCD 2016年第S2期174-182,共9页
Through enabling the IT and cloud computation capacities at Radio Access Network(RAN),Mobile Edge Computing(MEC) makes it possible to deploy and provide services locally.Therefore,MEC becomes the potential technology ... Through enabling the IT and cloud computation capacities at Radio Access Network(RAN),Mobile Edge Computing(MEC) makes it possible to deploy and provide services locally.Therefore,MEC becomes the potential technology to satisfy the requirements of 5G network to a certain extent,due to its functions of services localization,local breakout,caching,computation offloading,network context information exposure,etc.Especially,MEC can decrease the end-to-end latency dramatically through service localization and caching,which is key requirement of 5G low latency scenario.However,the performance of MEC still needs to be evaluated and verified for future deployment.Thus,the concept of MEC is introduced into5 G architecture and analyzed for different 5G scenarios in this paper.Secondly,the evaluation of MEC performance is conducted and analyzed in detail,especially for network end-to-end latency.In addition,some challenges of the MEC are also discussed for future deployment. 展开更多
关键词 mobile edge computing(mec) 5G network architecture low latency
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无线供电MEC系统的计算能效最大化策略
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作者 李陶深 巩健 +1 位作者 曾续玲 吕品 《郑州大学学报(工学版)》 CAS 北大核心 2025年第1期133-142,共10页
为了解决无线供电移动边缘计算(MEC)系统的计算能效优化问题,提出一种基于非正交多址接入的无线供电MEC系统的资源分配策略。该策略将非线性能量收集模型应用到移动设备上,通过联合优化MEC服务器和移动设备的计算频率、执行时间、基站... 为了解决无线供电移动边缘计算(MEC)系统的计算能效优化问题,提出一种基于非正交多址接入的无线供电MEC系统的资源分配策略。该策略将非线性能量收集模型应用到移动设备上,通过联合优化MEC服务器和移动设备的计算频率、执行时间、基站发射功率、设备发射功率、卸载时间和能量收集时间,比较充分地利用移动设备和MEC服务器的可用计算资源,提高设备的吞吐量和计算位数,进而最大限度地提升系统计算能效。将该联合优化问题转化为非凸分式规划问题,设计一种基于Dinkelbach的迭代算法来获得最优的资源分配方案。仿真实验表明:该资源分配策略所获得的系统计算能效更高,具有更好的性能增益。 展开更多
关键词 无线供电移动边缘计算系统 非正交多址接入 计算能效 能量收集 资源分配 计算卸载
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Novel Private Data Access Control Scheme Suitable for Mobile Edge Computing 被引量:2
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作者 Wei Liang Songyou Xie +3 位作者 Jiahong Cai Chong Wang Yujie Hong Xiaoyan Kui 《China Communications》 SCIE CSCD 2021年第11期92-103,共12页
Efficient response speed and information processing speed are among the characteristics of mobile edge computing(MEC).However,MEC easily causes information leakage and loss problems because it requires frequent data e... Efficient response speed and information processing speed are among the characteristics of mobile edge computing(MEC).However,MEC easily causes information leakage and loss problems because it requires frequent data exchange.This work proposes an anonymous privacy data protection and access control scheme based on elliptic curve cryptography(ECC)and bilinear pairing to protect the communication security of the MEC.In the proposed scheme,the information sender encrypts private information through the ECC algorithm,and the information receiver uses its own key information and bilinear pairing to extract and verify the identity of the information sender.During each round of communication,the proposed scheme uses timestamps and random numbers to ensure the freshness of each round of conversation.Experimental results show that the proposed scheme has good security performance and can provide data privacy protection,integrity verification,and traceability for the communication process of MEC.The proposed scheme has a lower cost than other related schemes.The communication and computational cost of the proposed scheme are reduced by 31.08% and 22.31% on average compared with those of the other related schemes. 展开更多
关键词 mobile edge computing(mec) privacy protection access control anonymous authentication
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Reliable and Energy-Aware Job Offloading at Terahertz Frequencies for Mobile Edge Computing 被引量:2
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作者 Sha Xie Haoran Li +2 位作者 Lingxiang Li Zhi Chen Shaoqian Li 《China Communications》 SCIE CSCD 2020年第12期17-36,共20页
In this paper,we co-design the transmission power and the offloading strategy for job offloading to a mobile edge computing(MEC)server at Terahertz(THz)frequencies.The goal is to minimize the communication energy cons... In this paper,we co-design the transmission power and the offloading strategy for job offloading to a mobile edge computing(MEC)server at Terahertz(THz)frequencies.The goal is to minimize the communication energy consumption while providing ultra-reliable low end-to-end latency(URLLC)services.To that end,we first establish a novel reliability framework,where the end-to-end(E2E)delay equals a weighted sum of the local computing delay,the communication delay and the edge computing delay,and the reliability is defined as the probability that the E2E delay remains below a certain pre-defined threshold.This reliability gives a full view of the statistics of the E2E delay,thus constituting advancement over prior works that have considered only average delays.Based on this framework,we establish the communication energy consumption minimization problem under URLLC constraints.This optimization problem is non-convex.To handle that issue,we first consider the special single-user case,where we derive the optimal solution by analyzing the structure of the optimization problem.Further,based on the analytical result for the single-user case,we decouple the optimization problem for multi-user scenarios into several sub-optimization problems and propose a sub-optimal algorithm to solve it.Numerical results verify the performance of the proposed algorithm. 展开更多
关键词 Terahertz(THz)communications mobile edge computing(mec) ultra-reliable low end-to-end latency(URLLC)services green communications
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Task Offloading and Resource Allocation for Edge-Enabled Mobile Learning 被引量:2
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作者 Ziyan Yang Shaochun Zhong 《China Communications》 SCIE CSCD 2023年第4期326-339,共14页
Mobile learning has evolved into a new format of education based on communication and computer technology that is favored by an increasing number of learning users thanks to the development of wireless communication n... Mobile learning has evolved into a new format of education based on communication and computer technology that is favored by an increasing number of learning users thanks to the development of wireless communication networks,mobile edge computing,artificial intelligence,and mobile devices.However,due to the constrained data processing capacity of mobile devices,efficient and effective interactive mobile learning is a challenge.Therefore,for mobile learning,we propose a"Cloud,Edge and End"fusion system architecture.Through task offloading and resource allocation for edge-enabled mobile learning to reduce the time and energy consumption of user equipment.Then,we present the proposed solutions that uses the minimum cost maximum flow(MCMF)algorithm to deal with the offloading problem and the deep Q network(DQN)algorithm to deal with the resource allocation problem respectively.Finally,the performance evaluation shows that the proposed offloading and resource allocation scheme can improve system performance,save energy,and satisfy the needs of learning users. 展开更多
关键词 mobile learning mobile edge computing(mec) system construction OFFLOADING resource allocation
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Optimization and Design of Cloud-Edge-End Collaboration Computing for Autonomous Robot Control Using 5G and Beyond
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作者 Hao Wang 《Journal of Beijing Institute of Technology》 EI CAS 2022年第5期454-463,共10页
Robots have important applications in industrial production, transportation, environmental monitoring and other fields, and multi-robot collaboration is a research hotspot in recent years. Multi-robot autonomous colla... Robots have important applications in industrial production, transportation, environmental monitoring and other fields, and multi-robot collaboration is a research hotspot in recent years. Multi-robot autonomous collaborative tasks are limited by communication, and there are problems such as poor resource allocation balance, slow response of the system to dynamic changes in the environment, and limited collaborative operation capabilities. The combination of 5G and beyond communication and edge computing can effectively reduce the transmission delay of task offloading and improve task processing efficiency. First, this paper designs a robot autonomous collaborative computing architecture based on 5G and beyond and mobile edge computing(MEC).Then, the robot cooperative computing optimization problem is studied according to the task characteristics of the robot swarm. Then, a reinforcement learning task offloading scheme based on Qlearning is further proposed, so that the overall energy consumption and delay of the robot cluster can be minimized. Finally, simulation experiments demonstrate that the method has significant performance advantages. 展开更多
关键词 robot collaboration mobile edge computing(mec) 5G and beyond network task offloading resource allocation
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电力物联网中时延能耗均衡的MEC资源调度策略 被引量:2
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作者 黄东海 亢中苗 吴赞红 《太赫兹科学与电子信息学报》 2024年第9期944-951,共8页
针对电力物联网中(PIoT)海量智能设备接入导致的流量激增问题,提出一种时延能耗均衡的边缘计算(MEC)资源调度策略。综合考虑信道条件、电力设备安全温度保护机制和设备能耗等因素,以兰道尔(Landaer)原理为基础构建设备侧的能耗模型和热... 针对电力物联网中(PIoT)海量智能设备接入导致的流量激增问题,提出一种时延能耗均衡的边缘计算(MEC)资源调度策略。综合考虑信道条件、电力设备安全温度保护机制和设备能耗等因素,以兰道尔(Landaer)原理为基础构建设备侧的能耗模型和热功耗约束。在保证队列稳定性的前提下,通过联合优化任务卸载决策、传输功率和计算资源分配,最小化系统长期平均时间能耗。为解决随机优化问题,引入李雅普诺夫(Lyapunov)理论,将问题转化为每个时隙的确定性优化问题。仿真结果表明,该策略相对于基准方案能够降低系统能耗,并实现能耗与时延之间的均衡。 展开更多
关键词 电力物联网 边缘计算 任务卸载 资源分配 能耗优化
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基于MEC-UAV的海域物联网设备的覆盖优化算法 被引量:1
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作者 苑毅 黄珍 《吉林大学学报(信息科学版)》 CAS 2024年第3期387-392,共6页
为增强对海域物联网(MIoT:Maritime Internet-of-Things)设备的覆盖,提出基于移动边缘计算(MEC:Mobile Edge Computing)的无人机(UAV:Unmanned Aerial Vehicle)部署的MIoTs的覆盖优化算法(UMCO:MEC-UAV-based Coverage Optimization alg... 为增强对海域物联网(MIoT:Maritime Internet-of-Things)设备的覆盖,提出基于移动边缘计算(MEC:Mobile Edge Computing)的无人机(UAV:Unmanned Aerial Vehicle)部署的MIoTs的覆盖优化算法(UMCO:MEC-UAV-based Coverage Optimization algorithm)。UMCO算法通过部署配备MEC-UAV,从而满足日益增加MIoTs的覆盖需求,提升网络增益。先将MEC-UAVs的部署以及其关联的MIoT设备问题形成联合问题,并将其转换成线性规划问题,最后利用基于Bender分解法的迭代算法求解该线性规划问题。仿真结果表明,该UMCO算法能获取逼近穷尽搜索算法的最优解。 展开更多
关键词 海域物联网 无人机 移动边缘计算 BENDERS分解法 网络增益
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无人机辅助MEC车辆任务卸载与功率控制近端策略优化算法
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作者 谭国平 易文雄 +1 位作者 周思源 胡鹤轩 《电子与信息学报》 EI CAS CSCD 北大核心 2024年第6期2361-2371,共11页
无人机(UAVs)辅助移动边缘计算(MEC)架构是灵活处理车载计算密集、时延敏感型任务的有效模式。但是,如何在处理任务时延与能耗之间达到最佳均衡,一直是此类车联网应用中长期存在的挑战性问题。为了解决该问题,该文基于无人机辅助移动边... 无人机(UAVs)辅助移动边缘计算(MEC)架构是灵活处理车载计算密集、时延敏感型任务的有效模式。但是,如何在处理任务时延与能耗之间达到最佳均衡,一直是此类车联网应用中长期存在的挑战性问题。为了解决该问题,该文基于无人机辅助移动边缘计算架构,考虑无线信道时变特性及车辆高移动性等动态变化特征,构建出基于非正交多址(NOMA)的车载任务卸载与功率控制优化问题模型,然后将该问题建模成马尔可夫决策过程,并提出一种基于近端策略优化(PPO)的分布式深度强化学习算法,使得车辆只需根据自身获取局部信息,自主决策任务卸载量及相关发射功率,从而达到时延与能耗的最佳均衡性能。仿真结果表明,与现有方法相比较,本文所提任务卸载与功率控制近端策略优化方案不仅能够显著获得更优的时延与能耗性能,所提方案平均系统代价性能提升至少13%以上,而且提供一种性能均衡优化方法,能够通过调节用户偏好权重因子,达到系统时延与能耗水平之间的最佳均衡。 展开更多
关键词 无人机辅助计算 移动边缘计算 近端策略优化 深度强化学习 功率控制和任务卸载
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MEC在5G无线接入网中的应用
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作者 洪鹰群 《通信电源技术》 2024年第22期195-197,238,共4页
在5G时代,低时延通信已成为实现高效数据处理和实时服务的关键需求。移动边缘计算技术通过将计算资源和服务部署在网络边缘,显著减少数据传输时间和延迟。详细探讨移动边缘计算(Mobile Edge Computing,MEC)技术在5G无线接入网中的应用,... 在5G时代,低时延通信已成为实现高效数据处理和实时服务的关键需求。移动边缘计算技术通过将计算资源和服务部署在网络边缘,显著减少数据传输时间和延迟。详细探讨移动边缘计算(Mobile Edge Computing,MEC)技术在5G无线接入网中的应用,包括MEC的任务卸载与调度策略、与网络切片技术的结合以及与软件定义网络/网络功能虚拟化(Software Defined Network/Network Functions Virtualization,SDN/NFV)技术的协同,实现5G网络的低时延通信。 展开更多
关键词 移动边缘计算(mec)技术 5G无线接入网 低时延通信
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异步移动边缘计算网络中的联合任务调度与计算资源分配优化策略
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作者 王汝言 杨安琪 +2 位作者 吴大鹏 唐桐 祝志远 《电子与信息学报》 北大核心 2025年第2期470-479,共10页
移动边缘计算(MEC)通过将密集型任务从传感器卸载到附近边缘服务器,来增强本地的计算能力,延长其电池寿命。然而,在面向无线传感器网等时变环境中,任务之间的异构性可能会导致通信低效率、高时延等问题。为此,该文提出一种异步移动边缘... 移动边缘计算(MEC)通过将密集型任务从传感器卸载到附近边缘服务器,来增强本地的计算能力,延长其电池寿命。然而,在面向无线传感器网等时变环境中,任务之间的异构性可能会导致通信低效率、高时延等问题。为此,该文提出一种异步移动边缘计算网络中的联合任务调度与计算资源分配优化策略,该策略实时感知任务信息年龄和能耗,将异步边缘卸载问题数学建模为NP难(NP-hard problem)的混合整数规划问题,并提出基于混合动作优势演员-评论家(HA2C)强化学习算法的任务调度和计算资源分配方案解决该问题。仿真结果表明,该文方法能显著降低异步卸载网络的平均信息年龄和能耗,满足无线传感器网络对任务时效性的要求。 展开更多
关键词 异步移动边缘计算 无线传感器网络 平均信息年龄 平均能耗 混合动作强化学习
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Intelligent Energy-Efficient Resource Allocation for Multi-UAV-Assisted Mobile Edge Computing Networks
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作者 Hu Han Shen Le +2 位作者 Zhou Fuhui Wang Qun Zhu Hongbo 《China Communications》 2025年第4期339-355,共17页
The unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC)has been deemed a promising solution for energy-constrained devices to run smart applications with computationintensive and latency-sensitive require... The unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC)has been deemed a promising solution for energy-constrained devices to run smart applications with computationintensive and latency-sensitive requirements,especially in some infrastructure-limited areas or some emergency scenarios.However,the multi-UAVassisted MEC network remains largely unexplored.In this paper,the dynamic trajectory optimization and computation offloading are studied in a multi-UAVassisted MEC system where multiple UAVs fly over a target area with different trajectories to serve ground users.By considering the dynamic channel condition and random task arrival and jointly optimizing UAVs'trajectories,user association,and subchannel assignment,the average long-term sum of the user energy consumption minimization problem is formulated.To address the problem involving both discrete and continuous variables,a hybrid decision deep reinforcement learning(DRL)-based intelligent energyefficient resource allocation and trajectory optimization algorithm is proposed,named HDRT algorithm,where deep Q network(DQN)and deep deterministic policy gradient(DDPG)are invoked to process discrete and continuous variables,respectively.Simulation results show that the proposed HDRT algorithm converges fast and outperforms other benchmarks in the aspect of user energy consumption and latency. 展开更多
关键词 dynamic trajectory optimization intelligent resource allocation unmanned aerial vehicle uav assisted uav assisted mec energy efficiency smart applications mobile edge computing mec deep reinforcement learning
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部分可观测环境中基于图强化的任务卸载与资源分配方法
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作者 代钰 景宗明 +1 位作者 杨雷 高振 《东北大学学报(自然科学版)》 北大核心 2025年第1期9-17,25,共10页
为了解决部分可观测环境中由于边缘服务器之间缺乏有效通信而导致的全局信息缺失问题,构建了基于图注意力机制的边缘服务器间沟通机制,将移动边缘计算(mobile edge computing,MEC)系统构建为图结构,使边缘服务器之间可以通过图中的边进... 为了解决部分可观测环境中由于边缘服务器之间缺乏有效通信而导致的全局信息缺失问题,构建了基于图注意力机制的边缘服务器间沟通机制,将移动边缘计算(mobile edge computing,MEC)系统构建为图结构,使边缘服务器之间可以通过图中的边进行消息传递,进而间接得到MEC系统的全局状态信息.同时引入双注意力机制,使边缘服务器更多关注对策略优化更有用的通信消息,加快模型收敛速度并提高算法性能.仿真实验结果表明,与基线算法相比,本文所提出的算法可以有效降低任务完成时延与能耗,同时具有收敛速度快的优点. 展开更多
关键词 移动边缘计算 深度强化学习 任务卸载 资源分配 消息通信
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一种基于无线携能通信的MEC与用户匹配算法 被引量:3
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作者 陈智雄 肖楠 韩东升 《电讯技术》 北大核心 2019年第12期1378-1384,共7页
多接入边缘计算(Multi-access Edge Computing,MEC)和无线携能通信可有效提高用户的服务质量和体验。在计算、通信和能量等资源的约束条件下,用户匹配是优化MEC任务卸载时系统效用的重要方法。针对无线携能通信的MEC网络结构,综合考虑... 多接入边缘计算(Multi-access Edge Computing,MEC)和无线携能通信可有效提高用户的服务质量和体验。在计算、通信和能量等资源的约束条件下,用户匹配是优化MEC任务卸载时系统效用的重要方法。针对无线携能通信的MEC网络结构,综合考虑用户的需求差异性和多元化能量供给,建立了基于计算资源、传输资源和能量资源的系统效用函数;以系统效用最大化为目标,采用基于多维背包理论的多轮拍卖,提出了一种适用于多用户和多网络边缘服务器的用户匹配算法。仿真验证了所提用户匹配算法的有效性与可靠性,结果表明所提匹配算法可优化系统资源配置,有效提高整体性能。 展开更多
关键词 无线携能通信 多接入边缘计算 用户匹配 拍卖理论
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