计算机科学 ›› 2022, Vol. 49 ›› Issue (9): 242-248.doi: 10.11896/jsjkx.210700166
孙慧婷, 范艳芳, 马孟晓, 陈若愚, 蔡英
SUN Hui-ting, FAN Yan-fang, MA Meng-xiao, CHEN Ruo-yu, CAI Ying
摘要： 车载边缘计算(Vehicular Edge Computing,VEC)是移动边缘计算(Mobile Edge Computing,MEC)在车联网中的一个重要应用。在VEC中,请求服务的车辆可以通过付费的方式,将计算任务卸载到VEC服务器或者空闲计算资源丰富的服务车辆上,从而满足车辆任务对计算服务的需求。然而,对于VEC运营商来说,收益最大化是其追求的目标之一。由于系统中的计算需求和计算资源是动态变化的,因此如何在车辆协同场景下确定一个合理的定价策略是一个不容忽视的问题。针对该问题制定了一个动态定价策略,使VEC服务器和服务车辆的价格随着计算资源的供需关系而动态调整。基于此,设计了运营商收益最大化的车辆协同计算卸载方案,通过将时延约束下的VEC运营商收益最大化问题转化为多用户匹配问题,使用Kuhn-Munkres(KM)算法求得卸载结果。仿真实验表明,相比已有定价策略,该动态定价策略下VEC服务器和服务车辆的价格均可以根据计算资源供需关系动态调整,从而实现运营商收益最大化;相比已有卸载方案,该方案可以在满足任务时延约束的前提下提高运营商的收益。
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| [1]EJAZ A,HAMID G.Cooperative Vehicular Networking:A Survey[J].IEEE Transactions on Intelligent Transportation Systems,2018,19(3):996-1014. [2]LI Y,LIU J,CAO B,et al.Joint optimization of radio and virtual machine resources with uncertain user demands in mobile cloud computing[J].IEEE Transactions on Multimedia,2018,20(9):2427-2438. [3]LIU J,WANG S,WANG J,et al.A Task Oriented Computation Offloading Algorithm for Intelligent Vehicle Network with Mobile Edge Computing[J].IEEE Access,2019,7:180491-180502. [4]FAN Y F,YUAN S,CAI Y,et al.Deep Reinforcement Lear-ning-Based Collaborative Computation Offloading Scheme in Vehicular Edge Computing[J].Computer Science,2021,48(5):270-276. [5]ZHOU Z,LIU P,FENG J,et al.Computation Resource Allocation and Task Assignment Optimization in Vehicular Fog Computing:A Contract-Matching Approach[J].IEEE Transactions on Vehicular Technology,2019,68(4):3113-3125. [6]WANG Q,WANG Q,ZHU H,et al.Enabling CollaborativeComputing Sustainably Through Computational Latency-Based Pricing[J].IEEE Transactions on Sustainable Computing,2020,5(4):541-551. [7]SHENG Z G,MAHAPATRA C,LEUNG V C M,et al.Energy Efficient Cooperative Computing in Mobile Wireless Sensor Networks[J].IEEE Transactions on Cloud Computing,2018,6(1):114-126. [8]ZHANG W,LI X,ZHAO L,et al.Service Pricing and Selection for IoT Applications Offloading in the Multi-Mobile Edge Computing Systems[J/OL].IEEE Access,2020,99:1-1.https://xueshu.baidu.com/usercenter/paper/show?paperid=16660ew0tv0r0mh0yk3g04e048342759&site=xueshu_se. [9]SWAIN C,SAHOO M N,SATPATHY A,et al.METO:Ma-tching Theory Based Efficient Task Offloading in IoT-Fog Interconnection Networks[J/OL].IEEE Internet of Things Journal,2020,99:1-1.https://xueshu.baidu.com/usercenter/paper/show?paperid=1y0300d05y0v0m10kr3n0gg0t0725549&site=xueshu_se&hitarticle=1. [10]ZHANG T,CHEN W,YANG F.Data offloading inmobile edgecomputing:A coalitional game-based pricingapproach[J].IEEE Access,2017,99:2760-2767. [11]LI F,YAO H,DU J,et al.Stackelberg Game-Based Computation Offloading in Social and Cognitive Industrial Internet of Things[J].IEEE Transactions on Industrial Informatics,2020,16(8):5444-5455. [12]WANG Y,LANG P,TIAN D,et al.A Game-Based Computation Offloading Method in Vehicular Multiaccess Edge Computing Networks[J/OL].IEEE Internet of Things Journal,2020,99:1-1.https://xueshu.baidu.com/usercenter/paper/show?paperid=1w420r10ud2m0ma0ft060480qu181963&site=xueshu_se&hitarticle=1. [13]ZHANG Y,QIN X,SONG X.Mobility-Aware Cooperative Task Offloading and Resource Allocation in Vehicular Edge Computing[C]//IEEE Wireless Communications and Networking Conference Workshops.2020:1-6. [14]LIU Y,YU H,XIE S,et al.Deep Reinforcement Learning for Offloading and Resource Allocation in Vehicle Edge Computing and Networks[J].IEEE Transactions on Vehicular Technology,2019,68(11):11158-11168. [15]SIEW M,CAI D,LI L,et al.Dynamic Pricing for Resource-Quota Sharing in Multi-Access Edge Computing[J/OL].IEEE Transactions on Network Science and Engineering,2020,PP(99):1-1.https://xueshu.baidu.com/usercenter/paper/show?paperid=130p0eh0a5040jj0w97v0jh0fj162634&site=xueshu_se&hitarticle=1. [16]SU Z,HUI Y L,LUAN T H.Distributed Task Allocation to Enable Collaborative Autonomous Driving with Network Softwarization[J].IEEE Journal on Selected Areas in Communications,2018,36(10):2175-2186. [17]WANG Q,GUO S,LIU J,et al.Profit Maximization Incentive Mechanismfor Resource Providers in Mobile Edge Computing[J/OL].IEEE Transactions on Services Computing,2019,99:1-1.https://xueshu.baidu.com/usercenter/paper/show?paperid=1t4a0e60e34g0rc0596t0x30uq274048&site=xueshu_se&hita-rticle=1. [18]LIU P,LI J,SUN Z.Matching-based task offloading for vehicular edge computing[J/OL].IEEE Access,2019,7:27628-27640.https://xueshu.baidu.com/usercenter/paper/show?paperid=1c0f0ga08q5c0cx0a2680cb0va584063&site=xueshu_se&hitar-ticle=1. |
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