QoS-DPSO: QoS-aware Task Scheduling for Cloud Computing System
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(2021) 29:5
QoS‑DPSO: QoS‑aware Task Scheduling for Cloud Computing System Weipeng Jing1 · Chuanyu Zhao2 · Qiucheng Miao1 · Houbing Song3 · Guangsheng Chen1 Received: 7 November 2019 / Revised: 22 April 2020 / Accepted: 28 July 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Dynamic provisioning of computational resources in cloud computing system is a challenging problem. With many VMs being deployed in clouds, managing so much resources to stable work becomes a critical problem. Therefore, how to meet the different quality of service (QoS), we consider the service quality requirements is very important. In this paper, we address this problem. We first establish a QoS scheduling model by incorporating the cloud characteristics, and then, we develop a task scheduling objects to ensure faults can be tolerated during the task exaction. Finally, we proposed a QoS-aware scheduling algorithm, QoS-DPSO, to satisfy the QoS required in cloud computing systems. For the target requirements of QoS requirement, we take the time, reliability and cost as a single object problem. Experimental results show that QoS-DPSO can effectively improve the performance and obtain the high reliability. Keywords Cloud computing · Quality of service · Fault-tolerant · Task scheduling · Multi-objective
1 Introduction Technology such as cloud computing and data centre, has aimed at allowing access to large amounts of computing power in a fully virtualized manner, by aggregating resources and offering a single system view [1]. The environment given by cloud computing for sharing resources(memory, bandwidth and CPU) by multiple virtual * Weipeng Jing [email protected] 1
College of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, China
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Computing Center of Heilongjiang, Harbin 150000, China
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Department of Electrical, Computer, Software, and Systems Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA
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machines (VMs) [2]. Virtualization technology can greatly improve the utilization of edge computing and cloud computing resources, such as such as Amazon’s Elastic Compute Cloud (EC2) [3]. Clouds computing system [4] provide resource in order to execute the task on virtualized machine which are provisioned dynamically and reliability [5]. In the medical cloud platform, various Internet of Things terminals [6] and mobile devices submit various business applications that need to be processed to the data center in real time. These business applications are abstracted into various types of tasks. This requires the medical cloud platform to meet your tasks. Platform processing time requirements. However, Resource allocation is the diligent deployment of resources on to tasks based on their skill set and timelines, therefore, it is difficult for users to obtain high reliability. Cloud computing can solve this problem by means of virtualization.
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