Joint Optimization Strategy of Computing Offloading and Edge Caching for Intelligent Connected Vehicles

doi:10.16182/j.issn1004731x.joss.22-0147

Abstract

Abstract:

To guarantee the low-delay communication of intelligent connected vehicles, the V2X channel model and the multi-access edge computing (MEC) technology, are used to carry out the research of the joint optimization strategy of computing offloading and edge caching. An intelligent connected vehicle with task offloading and edge caching model least-deep deterministic policy gradient(L-DDPG) is developed. By integrating the vehicular local and edge computing resources, the classification processing of different computing tasks in V2X scenarios is supported. The vehicular computing request is prejudged by edge platform to ensure the rapid response of continuous homogeneous computing tasks. Combining with the least recently used strategy, the new computing tasks are efficiently managed. A joint offloading decision for computing offloading and edge caching is carried out based on deep deterministic policy gradient(DDPG) algorithm. Simulation results show that the performance of L-DDPG model is better than that of traditional models, which can effectively improve the system performance, ensure the service quality, and reduce the time delay and resource consumption.

Key words: intelligent connected vehicle, vehicle to everything(V2X), multi-access edge computing, deep reinforcement learning, computing offloading, edge caching

CLC Number:

TP393

Fei Ding, Yuchen Sha, Ying Hong, Xiao Kuai, Dengyin Zhang. Joint Optimization Strategy of Computing Offloading and Edge Caching for Intelligent Connected Vehicles[J]. Journal of System Simulation, 2023, 35(6): 1203-1214.

Figures/Tables 10

Fig. 1

Fig. 2

Fig. 3

Table 1

Simulation parameters

参数	数值
RSU覆盖半径/m	300
车辆发射功率 $p v / d B m$	20
CPU能耗功率 $p c / W$	5
路侧边缘节点数	[3, 7]
单个MEC节点的计算能力 $f i m / G H z$	[5, 9]
上行传输信道数量 $K$	10
信道总带宽 $B / M H z$	20
高斯白噪声功率 $σ 2 / d B m$	-100
车辆计算能力 $f i v / G H z$	1
计算任务大小 $d i / M B$	20
权重因子 $α$	0.5
缓存空间 $H m / M B$	500
最大容忍时延 $t i m a x / s$	0.003
载波频率 $f c / G H z$	5.915
基站的高度 $h B S / m$	35
车辆的高度 $h U T / m$	1.5
发送信号功率 $P t x / d B m$	23
天线增益 $G a n t e n n a / d B i$	3
噪声功率 $P n o i s e / W$	$3 × 10 - 13$

Table 1

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

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