A novel approach for IoT tasks offloading in edge-cloud environments

Journal of Cloud Computing

Mohammad Aldossary¹  Jaber Almutairi² 

[1]Department of Computer Science, College of Arts and Science, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia

[2]Department of Computer Science, College of Computer Science and Engineering, Taibah University, Al-Madinah, Saudi Arabia

关键词: Edge-cloud computing;    Edge orchestrator;    Resource management;    Latency sensitivity;    Task offloading;    Scheduling;    Internet of things;   

DOI  :  10.1186/s13677-021-00243-9

来源: Springer

【 摘 要 】

Recently, the number of Internet of Things (IoT) devices connected to the Internet has increased dramatically as well as the data produced by these devices. This would require offloading IoT tasks to release heavy computation and storage to the resource-rich nodes such as Edge Computing and Cloud Computing. Although Edge Computing is a promising enabler for latency-sensitive related issues, its deployment produces new challenges. Besides, different service architectures and offloading strategies have a different impact on the service time performance of IoT applications. Therefore, this paper presents a novel approach for task offloading in an Edge-Cloud system in order to minimize the overall service time for latency-sensitive applications. This approach adopts fuzzy logic algorithms, considering application characteristics (e.g., CPU demand, network demand and delay sensitivity) as well as resource utilization and resource heterogeneity. A number of simulation experiments are conducted to evaluate the proposed approach with other related approaches, where it was found to improve the overall service time for latency-sensitive applications and utilize the edge-cloud resources effectively. Also, the results show that different offloading decisions within the Edge-Cloud system can lead to various service time due to the computational resources and communications types.

【 授权许可】

CC BY