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Research On Offloading In Edge Computing-Enabled Networks With Dynamic Time Division Duplex

Posted on:2021-04-29Degree:MasterType:Thesis
Country:ChinaCandidate:Q ZhangFull Text:PDF
GTID:2428330614970756Subject:Communication and Information System
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Mobile Internet and the Internet of Things,as the main driving force for the development of mobile communications in the future,bring new challenges to Fifth generation(5G)mobile communication systems,such as the growth of explosive business data volume,asymmetric business requirements and massive device connections.Mobile computing offloading in Mobile edge computing(MEC)provides a feasible solution for the problems of massive data processing and energy limitation for mobile device.Dynamic time division duplex(DTDD)can effectively support dynamic and asymmetric uplink and downlink services in future networks by scheduling spectrum resources dynamically.These two technologies complement each other and are of great significance to the research of 5G systems.Most of the existing offload technology research in the DTDD scenario considers homogenous scenarios,and the cross-slot interference problem in heterogeneous scenarios is more difficult to handle and less relevant research.In addition,compared to traditional static cellular network scenarios,most of the existing of the research on computing offload in high-speed mobile scenarios considers static channels,and does not study the impact of timevarying channels and Doppler effects on resource allocation,this paper studies the computing offloading in edge computing scenario with dynamic time division duplex for two typical scenarios with different mobility characteristics.The main innovative work and contributions are summarized as follows.Firstly,this paper studies the computational offloading in MEC-enabled static heterogeneous network scenarios with DTDD mode.First,a system model in heterogeneous network is constructed,and a joint optimization problem of computing offloading and spectrum resources to minimize the average user energy consumption is proposed.Since this problem is a mixed integer programming(MIP)problem,this paper converts it into two sub-problems,namely a linear programming problem(for solving offloading decisions)and a many-to-one matching problem(for solving subcarrier allocation),and then proposes a joint optimization algorithm based on user and subcarrier priority sequence.Simulation results show that the strategy proposed in this paper is significantly better than other benchmark schemes.In addition,it has been observed that as the uplink transmission ratio increases,the average energy consumption of mobile users decreases.Secondly,the above scheme is researched on the traditional static cellular network.Based on this,this scheme studies the computational offloading e in high-speed railway network with DTDD mode.The research modeled the computing task of all users in the train as a "big task".Considering the resource constrain of the vehicle server on the train,the vehicle server processes the "big task" in two modes,local computing and compute offloading.In addition,the channel model of the moving train is proposed based on the predictable characteristics of the vehicle trajectories in high-speed moving scenarios.Through the joint optimization of computing offloading,task allocation,computation resources and communication resources,the problem of minimizing energy consumption for vehicle server is constructed.Since this problem is a non-convex problem,a mathematical derivation and transformation is used to convert it into a convex problem that is easy to solve,and a two-layer optimization algorithm is proposed.The simulation results illustrate the gains in system performance brought by the computing offloading technology and DTDD technology,verify the effectiveness of the proposed algorithm,and analyze the impact of vehicle speed and Doppler frequency shift on the system.This article has completed the preliminary exploration of the research on computing offloading in the typical scenario of MEC-enabled networks with DTDD mode,which will bring new research ideas to the research work related to edge computing and have important research significance.
Keywords/Search Tags:MEC, Computing offloading, DTDD, High-speed mobile scenarios
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