Heterogeneous Task Allocation Model and Algorithm for Intelligent Connected Vehicles
作者机构：Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China Southwest Forestry Univ Sch Mech & Transportat Kunming 650224 Peoples R China
出 版 物：《CMC-COMPUTERS MATERIALS & CONTINUA》 (计算机、材料和连续体（英文）)
年 卷 期：2024年第80卷第3期
页 面：4281-4302页
核心收录：
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：National Natural Science Foundation of China Applied Basic Research Foundation of Yunnan Province [2019FD071] Yunnan Scientific Research Foundation Project [2019J0187]
主 题：Task allocation intelligent connected vehicles dispersed computing matching algorithm RESOURCE-ALLOCATION PARADIGM
摘 要：With the development of vehicles towards intelligence and connectivity, vehicular data is diversifying and growing dramatically. A task allocation model and algorithm for heterogeneous Intelligent Connected Vehicle (ICV) applications are proposed for the dispersed computing network composed of heterogeneous task vehicles and Network Computing Points (NCPs). Considering the amount of task data and the idle resources of NCPs, a computing resource scheduling model for NCPs is established. Taking the heterogeneous task execution delay threshold as a constraint, the optimization problem is described as the problem of maximizing the utilization of computing resources by NCPs. The proposed problem is proven to be NP-hard by using the method of reduction to a 0-1 knapsack problem. A many-to-many matching algorithm based on resource preferences is proposed. The algorithm first establishes the mutual preference lists based on the adaptability of the task requirements and the resources provided by NCPs. This enables the filtering out of un-schedulable NCPs in the initial stage of matching, reducing the solution space dimension. To solve the matching problem between ICVs and NCPs, a new many-to-many matching algorithm is proposed to obtain a unique and stable optimal matching result. The simulation results demonstrate that the proposed scheme can improve the resource utilization of NCPs by an average of 9.6% compared to the reference scheme, and the total performance can be improved by up to 15.9%.
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