Literature DB >> 33498910

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

Shichao Chen1,2, Qijie Li3, Mengchu Zhou1,4,5, Abdullah Abusorrah5.   

Abstract

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.

Entities:  

Keywords:  collaborative scheduling; edge computing; internet of things; limited resources; optimization; task offloading

Year:  2021        PMID: 33498910      PMCID: PMC7865659          DOI: 10.3390/s21030779

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

1.  Encapsulation of Capacitive Micromachined Ultrasonic Transducers (CMUTs) for the Acoustic Communication between Medical Implants.

Authors:  Jorge Oevermann; Peter Weber; Steffen H Tretbar
Journal:  Sensors (Basel)       Date:  2021-01-09       Impact factor: 3.576

2.  An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks.

Authors:  Jaime A Rincon; Solanye Guerra-Ojeda; Carlos Carrascosa; Vicente Julian
Journal:  Sensors (Basel)       Date:  2020-12-21       Impact factor: 3.576

  2 in total
  2 in total

1.  An Efficient Resource Management Optimization Scheme for Internet of Vehicles in Edge Computing Environment.

Authors:  Anqing Zhu; Youyun Wen
Journal:  Comput Intell Neurosci       Date:  2022-05-28

2.  The Use of Internet of Things and Cloud Computing Technology in the Performance Appraisal Management of Innovation Capability of University Scientific Research Team.

Authors:  Siyu Meng; Xue Zhang
Journal:  Comput Intell Neurosci       Date:  2022-04-10
  2 in total

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