Resource allocation strategy based on evolutionary strategy algorithm and Hungarian algorithm in Internet of Vehicles
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维普
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为了提高车联网中高清地图下载业务的吞吐量和降低车队行驶业务的传输时延,提出一种基于进化策略算法和匈牙利算法(Evolutionary Strategy Algorithm and Hungarian Algorithm,ES-HA)的网络切片资源分配策略.构建增强型移动带宽(Enhanced Mobile Broadband,eMBB)切片和高可靠低时延(Ultra Reliable&Low Latency Com-munication,uRLLC)切片,根据eMBB用户和uRLLC用户功率之间的函数关系求得最佳功率,采用ES算法获得两种用户的最佳带宽,并使用HA实现最佳信道匹配.仿真结果表明,与基于集群的资源块共享和功率分配(Cluster-based Resource Block Sharing and Power Allocation,CROWN)算法、基于基准算法的资源分配策略在总吞吐量、传输任务时延、链路容量及最小吞吐量方面进行对比,该策略在满足车到基础设施(Vehicle to Infrastructure,V2I)链路用户高容量需求的同时,能够提高下载业务的吞吐量和降低车队行驶业务的传输时延.
In order to improve the throughput of high-definition map download services in the Inter-net of Vehicles and reduce the transmission delay of fleet driving services,a network slicing resource allocation strategy based on evolutionary strategy algorithm and Hungarian algorithm is proposed.enhanced mobile broadband(eMBB)slice and ultra reliable and low latency communication(uRLLC)slice are built.The optimal power is obtained according to the functional relationship be-tween eMBB and uRLLC user power.The evolutionary strategy algorithm is adopted to get the opti-mal bandwidth of two types of users.The Hungarian algorithm is adopted to achieve the best chan-nel matching.Simulation results show that compared with resource allocation strategies based on the CROWN algorithm and the benchmark algorithm in terms of total throughput,transmission task delay,link capacity,and minimum throughput,the proposed strategy can improve the throughput of download services and reduce the transmission delay of fleet driving services while meeting the high capacity requirements of vehicle to infrastructure(V2I)link users.
Internet of Vehiclesnetwork slicingevolutionary strategy algorithmHungarian algo-rithmthroughputenhanced mobile broadband
维普
万方数据
