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Distributed matching theory-Based Task Re-Allocating for Heterogeneous Multi-UAV Edge Computing

China Communications 2024年第1期21卷 260-278页

作者： Yangang Wang Xianglin Wei Hai Wang Yongyang Hu Kuang Zhao Jianhua Fan College of Communications Engineering Army Engineering University of PLANanjing 210007China The Sixty-Third Research Institute National University of Defense TechnologyNanjing 210007China

Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge ***,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered ***,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy *** three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making *** tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and ***,a Distributed matching theory-based Re-allocating(DiMaToRe)algorithm is put *** formally proved that a stable matching can be achieved by our *** simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.

关键词： edge computing heterogeneity matching theory service function unmanned aerial vehicle

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Joint computation offloading and resource allocation in vehicular edge computing networks

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Digital Communications and Networks 2023年第6期9卷 1399-1410页

作者： Shuang Liu Jie Tian Chao Zhai Tiantian Li School of Information Science and Engineering Shandong Normal UniversityJinan250358China School of Information Science and Engineering Shandong UniversityQingdao266237China

Vehicular Edge Computing(VEC)is a promising technique to accommodate the computation-intensive and delaysensitive tasks through offloading the tasks to the RoadSide-Unit(RSU)equipped with edge computing servers or neighboring ***,the limited computation resources of edge computing servers and the mobility of vehicles make the offloading policy design very *** this context,through considering the potential transmission gains brought by the mobility of vehicles,we propose an efficient computation offloading and resource allocation scheme in VEC networks with two kinds of offloading modes,i.e.,Vehicle to Vehicle(V2V)and Vehicle to RSU(V2R).We define a new cost function for vehicular users by incorporating the vehicles’offloading delay,energy consumption,and expenses with a differentiated pricing strategy,as well as the transmission *** optimization problem is formulated to minimize the average cost of all the task vehicles under the latency and computation capacity constraints.A distributed iterative algorithm is proposed by decoupling the problem into two subproblems for the offloading mode selection and the resource *** theorybased and Lagrangian-based algorithms are proposed to solve the two subproblems,*** results show the proposed algorithm achieves low complexity and significantly improves the system performance compared with three benchmark schemes.

关键词： Vehicular edge computing Task offloading matching theory Lagrangian method Distributed algorithm

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Joint Computing and Communication Resource Allocation for Satellite Communication Networks with Edge Computing

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China Communications 2021年第7期18卷 236-252页

作者： Shanghong Zhang Gaofeng Cui Yating Long Weidong Wang School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Universal Wireless Communications(Beijing University of Posts and Telecommunications) Beijing 100876China Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory Hebei 050000China

Benefit from the enhanced onboard processing capacities and high-speed satellite-terrestrial links,satellite edge computing has been regarded as a promising technique to facilitate the execution of the computation-intensive applications for satellite communication networks(SCNs).By deploying edge computing servers in satellite and gateway stations,SCNs can achieve significant performance gains of the computing capacities at the expense of extending the dimensions and complexity of resource ***,in this paper,we investigate the joint computing and communication resource management problem for SCNs to minimize the execution latency of the computation-intensive applications,while two different satellite edge computing scenarios and local execution are ***,the joint computing and communication resource allocation problem for the computation-intensive services is formulated as a mixed-integer programming problem.A game-theoretic and many-to-one matching theorybased scheme(JCCRA-GM)is proposed to achieve an approximate optimal *** results show that the proposed method with low complexity can achieve almost the same weight-sum latency as the Brute-force method.

关键词： satellite communication networks edge computing resource allocation matching theory

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