首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Recent Advances in Collaborative Scheduling of Computing Tasks in an Edge Computing Paradigm
【2h】

Recent Advances in Collaborative Scheduling of Computing Tasks in an Edge Computing Paradigm

机译:边缘计算范式计算任务的协同调度最新进展

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

In edge computing, edge devices can offload their overloaded computing tasks to an edge server. This can give full play to an edge server’s advantages in computing and storage, and efficiently execute computing tasks. However, if they together offload all the overloaded computing tasks to an edge server, it can be overloaded, thereby resulting in the high processing delay of many computing tasks and unexpectedly high energy consumption. On the other hand, the resources in idle edge devices may be wasted and resource-rich cloud centers may be underutilized. Therefore, it is essential to explore a computing task collaborative scheduling mechanism with an edge server, a cloud center and edge devices according to task characteristics, optimization objectives and system status. It can help one realize efficient collaborative scheduling and precise execution of all computing tasks. This work analyzes and summarizes the edge computing scenarios in an edge computing paradigm. It then classifies the computing tasks in edge computing scenarios. Next, it formulates the optimization problem of computation offloading for an edge computing system. According to the problem formulation, the collaborative scheduling methods of computing tasks are then reviewed. Finally, future research issues for advanced collaborative scheduling in the context of edge computing are indicated.
机译:在边缘计算中,边缘设备可以将其重载的计算任务卸载到边缘服务器。这可以充分发挥到Edge Server在计算和存储方面的优势,并有效执行计算任务。但是,如果它们一起将所有过载的计算任务一起卸载到边缘服务器,则可以过载,从而导致许多计算任务的高处理延迟和意外的高能耗。另一方面,可以浪费空闲边缘设备中的资源,并且可以未冷冻资源的云中心。因此,必须根据任务特征,优化目标和系统状态探索具有边缘服务器,云中心和边缘设备的计算任务协同调度机制。它可以帮助一个人实现高效的协作调度和精确执行所有计算任务。此工作分析并概述了边缘计算范例中的边缘计算方案。然后,它将计算任务分类为边缘计算方案。接下来,它制定用于边缘计算系统的计算卸载的优化问题。根据问题制定,然后综述计算任务的协同调度方法。最后,指出了在边缘计算上下文中的未来研究问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号