{"title":"Priority Based Scheduler for Asymmetric Multi-Core Edge Computing","authors":"Rupendra Pratap Singh Hada;Abhishek Srivastava","doi":"10.13052/jwe1540-9589.2262","DOIUrl":null,"url":null,"abstract":"Edge computing technology has gained popularity due to its ability to process data near the source or collection device, benefiting from low bandwidth utilization and enhanced security. Edge devices are typically equipped with multiple devices that employ asymmetric multi-cores for efficient data processing. To ensure optimal performance, it is crucial to carefully assign tasks to the appropriate cores in asymmetric multi-core processors. However, the current Linux scheduler needs to consider the capabilities of individual cores when assigning tasks. Consequently, high-priority tasks may be assigned to energy-efficient cores, while low-priority tasks end up on high-performance cores. This sub-optimal task assignment negatively impacts the overall system performance. To address this issue, a new algorithm has been proposed. This algorithm considers both the core's capabilities and the task's priority. However, due to the asymmetric nature of the cores, prior knowledge of each core's speed is necessary. The algorithm fetches the priorities of the tasks and classifies them into high, medium, and low-priority categories. Highpriority tasks are scheduled on high-performance cores, while medium and low-priority tasks are allocated to energy-efficient cores. The proposed algorithm demonstrates superior performance for high-priority tasks compared to the existing Linux task scheduling algorithm. It significantly improves task scheduling time by up to 16%, thereby enhancing the system's overall efficiency.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"22 6","pages":"871-888"},"PeriodicalIF":0.7000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10376421","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Web Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10376421/","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Edge computing technology has gained popularity due to its ability to process data near the source or collection device, benefiting from low bandwidth utilization and enhanced security. Edge devices are typically equipped with multiple devices that employ asymmetric multi-cores for efficient data processing. To ensure optimal performance, it is crucial to carefully assign tasks to the appropriate cores in asymmetric multi-core processors. However, the current Linux scheduler needs to consider the capabilities of individual cores when assigning tasks. Consequently, high-priority tasks may be assigned to energy-efficient cores, while low-priority tasks end up on high-performance cores. This sub-optimal task assignment negatively impacts the overall system performance. To address this issue, a new algorithm has been proposed. This algorithm considers both the core's capabilities and the task's priority. However, due to the asymmetric nature of the cores, prior knowledge of each core's speed is necessary. The algorithm fetches the priorities of the tasks and classifies them into high, medium, and low-priority categories. Highpriority tasks are scheduled on high-performance cores, while medium and low-priority tasks are allocated to energy-efficient cores. The proposed algorithm demonstrates superior performance for high-priority tasks compared to the existing Linux task scheduling algorithm. It significantly improves task scheduling time by up to 16%, thereby enhancing the system's overall efficiency.
边缘计算技术能够在数据源或收集设备附近处理数据,具有带宽利用率低和安全性高的优点,因此越来越受欢迎。边缘设备通常配备多个设备,采用非对称多核高效处理数据。为确保最佳性能,将任务仔细分配给非对称多核处理器中的适当内核至关重要。然而,当前的 Linux 调度器在分配任务时需要考虑单个内核的能力。因此,高优先级的任务可能会被分配到能效高的内核上,而低优先级的任务最终会被分配到高性能的内核上。这种次优任务分配会对系统的整体性能产生负面影响。为解决这一问题,我们提出了一种新算法。该算法同时考虑了内核的能力和任务的优先级。不过,由于内核的非对称性质,事先了解每个内核的速度是必要的。该算法获取任务的优先级,并将其分为高、中、低三个优先级。高优先级任务安排在高性能内核上,而中优先级和低优先级任务则分配给高能效内核。与现有的 Linux 任务调度算法相比,所提出的算法在高优先级任务方面表现出更优越的性能。它能将任务调度时间大幅提高 16%,从而提高系统的整体效率。
期刊介绍:
The World Wide Web and its associated technologies have become a major implementation and delivery platform for a large variety of applications, ranging from simple institutional information Web sites to sophisticated supply-chain management systems, financial applications, e-government, distance learning, and entertainment, among others. Such applications, in addition to their intrinsic functionality, also exhibit the more complex behavior of distributed applications.