A Constrained Static Scheduling Strategy in Edge Computing for Industrial Cloud Systems

2021 ◽  
Vol 14 (1) ◽  
pp. 33-61
Author(s):  
Yuliang Ma ◽  
Yinghua Han ◽  
Jinkuan Wang ◽  
Qiang Zhao
Keyword(s):  
Resource Management ◽  
Task Scheduling ◽  
Dynamic Scheduling ◽  
Edge Computing ◽  
Task Completion ◽  
Scheduling Strategy ◽  
Static Scheduling ◽  
System A ◽  
Industrial Internet ◽  
Industrial Cloud

With the development of industrial internet, attention has been paid for edge computing due to the low latency. However, some problems remain about the task scheduling and resource management. In this paper, an edge computing supported industrial cloud system is investigated. According to the system, a constrained static scheduling strategy is proposed to over the deficiency of dynamic scheduling. The strategy is divided into the following steps. Firstly, the queue theory is introduced to calculate the expectations of task completion time. Thereupon, the task scheduling and resource management problems are formulated and turned into an integer non-linear programming (INLP) problem. Then, tasks that can be scheduled statically are selected based on the expectation of task completion and constrains of various aspects of task. Finally, a multi-elites-based co-evolutionary genetic algorithm (MEB-CGA) is proposed to solve the INLP problem. Simulation result shows that the MEB-CGA significantly outperforms the scheduling quality of greedy algorithm.

scholarly journals An Overhead-Optimizing Task Scheduling Strategy for Ad-hoc Based Mobile Edge Computing

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 5609-5622 ◽  
Author(s):  
Li Tianze ◽  
Wu Muqing ◽  
Zhao Min ◽  
Liao Wenxing
Keyword(s):  
Task Scheduling ◽  
Ad Hoc ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Scheduling Strategy

scholarly journals REVIEW OF TASK SCHEDULING METHODS FOR REAL TIME TASKS IN CLOUD ENVIRONMENT

2020 ◽  
Vol 5 (1) ◽  
pp. 85-89
Author(s):  
Dinkan Patel ◽  
Anjuman Ranavadiya
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Task Scheduling ◽  
Virtual Machines ◽  
Dynamic Scheduling ◽  
Scheduling Algorithms ◽  
Minimum Time ◽  
Cloud Environment ◽  
Static Scheduling ◽  
On Demand

Cloud Computing is a type of Internet model that enables convenient, on-demand resources that can be used rapidly and with minimum effort. Cloud Computing can be IaaS, PaaS or SaaS. Scheduling of these tasks is important so that resources can be utilized efficiently with minimum time which in turn gives better performance. Real time tasks require dynamic scheduling as tasks cannot be known in advance as in static scheduling approach. There are different task scheduling algorithms that can be utilized to increase the performance in real time and performing these on virtual machines can prove to be useful. Here a review of various task scheduling algorithms is done which can be used to perform the task and allocate resources so that performance can be increased.

scholarly journals Research on Intelligent Scheduling Mechanism in Edge Network for Industrial Internet of Things

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Zhenzhong Zhang ◽  
Wei Sun ◽  
Yanliang Yu
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Task Scheduling ◽  
Edge Computing ◽  
The Internet ◽  
Computing Technology ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Internet Of Things Technology

With the vigorous development of the Internet of Things, the Internet, cloud computing, and mobile terminals, edge computing has emerged as a new type of Internet of Things technology, which is one of the important components of the Industrial Internet of Things. In the face of large-scale data processing and calculations, traditional cloud computing is facing tremendous pressure, and the demand for new low-latency computing technologies is imminent. As a supplementary expansion of cloud computing technology, mobile edge computing will sink the computing power from the previous cloud to a network edge node. Through the mutual cooperation between computing nodes, the number of nodes that can be calculated is more, the types are more comprehensive, and the computing range is even greater. Broadly, it makes up for the shortcomings of cloud computing technology. Although edge computing technology has many advantages and has certain research and application results, how to allocate a large number of computing tasks and computing resources to computing nodes and how to schedule computing tasks at edge nodes are still challenges for edge computing. In view of the problems encountered by edge computing technology in resource allocation and task scheduling, this paper designs a dynamic task scheduling strategy for edge computing with delay-aware characteristics, which realizes the reasonable utilization of computing resources and is required for edge computing systems. This paper proposes a resource allocation scheme combined with the simulated annealing algorithm, which minimizes the overall performance loss of the system while keeping the system low delay. Finally, it is verified through experiments that the task scheduling and resource allocation methods proposed in this paper can significantly reduce the response delay of the application.

Software-Defined Task Scheduling Strategy Towards Edge Computing

2021 ◽  
pp. 197-211
Author(s):  
Yue Guo ◽  
Junfeng Hou ◽  
Heng Wang ◽  
Changjin Li ◽  
Hongjun Zhang ◽  
...  
Keyword(s):  
Task Scheduling ◽  
Edge Computing ◽  
Scheduling Strategy

scholarly journals ACPEC: A Resource Management Scheme Based on Ant Colony Algorithm for Power Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Zhu Liu ◽  
Xuesong Qiu ◽  
Nan Zhang
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Resource Sharing ◽  
Ant Colony Algorithm ◽  
Dynamic Scheduling ◽  
Edge Computing ◽  
Ant Colony ◽  
Good Effect ◽  
Management Scheme ◽  
Internet Of Things Technology

With the development of power IoTs (Internet of Things) technology, more and more intelligent devices access the network. Cloud computing is used to provide the resource storage and task computing services for power network. However, there are many problems with traditional cloud computing such as the long-time delay and resource bottleneck. Therefore, in this paper, a two-level resource management scheme is put forward based on the idea of edge computing. Furthermore, a new task scheduling algorithm is presented based on the ant colony algorithm, which realized the resource sharing and dynamic scheduling. The data of simulation show that this algorithm has a good effect on the performance of task execution time, power consumption, and so on.

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