Internet of Vehicles (IoV) over Vehicular Ad-hoc Networks (VANETS) is an emerging technology enabling the development of smart cities applications for safer, efficient, and pleasant travel. These applications have stringent requirements expressed in Service Level Agreements (SLAs). Considering vehicles limited computational and storage capabilities, applications requests are offloaded into an integrated edge-cloud computing system. Existing offloading solutions focus on optimizing applications Quality of Service (QoS) while respecting a single SLA constraint. They do not consider the impact of overlapped requests processing. Very few contemplate the varying speed of a vehicle. This paper proposes a novel Artificial Intelligence (AI) QoS-SLA-aware genetic algorithm (GA) for multi-request offloading in a heterogeneous edge-cloud computing system, considering the impact of overlapping requests processing and dynamic vehicle speed. The objective of the optimization algorithm is to improve the applications' Quality of Service (QoS) by minimizing the total execution time. The proposed algorithm integrates an adaptive penalty function to assimilate the SLAs constraints in terms of latency, processing time, deadline, CPU, and memory requirements. Numerical experiments and comparative analysis are achieved between our proposed QoS-SLA-aware GA, random, and GA baseline approaches. The results show that the proposed algorithm executes the requests 1.22 times faster on average compared to the random approach with 59.9% less SLA violations. While the GA baseline approach increases the performance of the requests by 1.14 times, it has 19.8% more SLA violations than our approach.
翻译:由于车辆计算和储存能力有限,申请请求被卸入一个综合的边球计算系统。现有卸载解决方案侧重于优化应用程序质量(QOS),同时尊重单一的SLA限制。它们不考虑重叠请求处理方法的影响。很少有人考虑车辆速度不同。本文件建议对多请求卸载在混合的边球计算系统中采用新的人工智能(AI)QOS-SLA-aware遗传算法(GA),考虑到重复请求处理和动态车辆速度的影响。优化算法的目标是通过尽可能缩短总执行时间来提高应用程序质量(QOS)。拟议的算法结合了调整处罚功能,以在延缩、处理时间、SLA-SA-遗传算法(QA)方面将限制与59次的随机速度(AI),QOS-S-SLA遗传算法(GA)相比,在拟议的平均递增时间、SLA1级的递增时间、比较存储结果分析比AAA(CSLA)要求(NU-CLA)之间,在拟议的递增时间和随机要求方面,在拟议的递增要求方面,在提议的递减要求方面,在提议的递减要求方面,在比较的递减要求方面,在ASALA1的递增要求方面,在比较的递减要求方面,在提议的递减要求中,在比较的递减要求中增加了。