General Framework for Task Scheduling and Resource Provisioning in Cloud Computing Systems

2016 ◽  
Author(s):  
Xiaomin Zhu ◽  
Yabing Zha ◽  
Ling Liu ◽  
Peng Jiao
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
General Framework ◽  
Resource Provisioning ◽  
Computing Systems

scholarly journals Enhanced Round-Robin Algorithm in the Cloud Computing Environment for Optimal Task Scheduling

Computers ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 63
Author(s):  
Fahd Alhaidari ◽  
Taghreed Zayed Balharith
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Critical Role ◽  
Turnaround Time ◽  
Round Robin ◽  
Computing Systems ◽  
Time Quantum ◽  
Dynamic Time ◽  
High Level ◽  
Level Performance

Recently, there has been significant growth in the popularity of cloud computing systems. One of the main issues in building cloud computing systems is task scheduling. It plays a critical role in achieving high-level performance and outstanding throughput by having the greatest benefit from the resources. Therefore, enhancing task scheduling algorithms will enhance the QoS, thus leading to more sustainability of cloud computing systems. This paper introduces a novel technique called the dynamic round-robin heuristic algorithm (DRRHA) by utilizing the round-robin algorithm and tuning its time quantum in a dynamic manner based on the mean of the time quantum. Moreover, we applied the remaining burst time of the task as a factor to decide the continuity of executing the task during the current round. The experimental results obtained using the CloudSim Plus tool showed that the DRRHA significantly outperformed the competition in terms of the average waiting time, turnaround time, and response time compared with several studied algorithms, including IRRVQ, dynamic time slice round-robin, improved RR, and SRDQ algorithms.

scholarly journals Scheduling under Open stack – The Current State and Future Enhancements

2019 ◽  
Vol 8 (2) ◽  
pp. 375-382
Keyword(s):  
Cloud Computing ◽  
Open Source ◽  
Task Scheduling ◽  
Computing System ◽  
Important Task ◽  
Shared Resources ◽  
Computing Systems ◽  
Current State ◽  
Cloud Computing System ◽  
Research Findings

Cloud computing is being heavily used for implementing different kinds of applications. Many of the client applications are being migrated to cloud for the reasons of cost and elasticity. Cloud computing is generally implemented on distributing computing wherein the Physical servers are heavily distributed considering both hardware and software, the connectivity among which is established through Internet. The cloud computing systems as such have many physical servers which contain many resources. The resources can be made to be shared among many users who are the tenants to the cloud computing system. The resources can be virtualized so as to provide shared resources to the clients. Scheduling is one of the most important task of a cloud computing system which is concerned with task scheduling, resource scheduling and scheduling Virtual Machin Migration. It is important to understand the issue of scheduling within a cloud computing system more in-depth so that any improvements with reference to scheduling can be investigated and implemented. For carrying in depth research, an OPEN source based cloud computing system is needed. OPEN STACK is one such OPEN source based cloud computing system that can be considered for experimenting the research findings that are related to cloud computing system. In this paper an overview on the way the Scheduling aspect per say has been implemented within OPEN STACK cloud computing system

scholarly journals SLA-DQTS: SLA Constrained Adaptive Online Task Scheduling Based on DDQN in Cloud Computing

2021 ◽  
Vol 11 (20) ◽  
pp. 9360
Author(s):  
Kaibin Li ◽  
Zhiping Peng ◽  
Delong Cui ◽  
Qirui Li
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Performance Optimization ◽  
Heuristic Algorithms ◽  
Scheduling Algorithm ◽  
Computing Systems ◽  
Q Learning ◽  
Reward Function ◽  
Task Scheduling Algorithm ◽  
Comparison Algorithms

Task scheduling is key to performance optimization and resource management in cloud computing systems. Because of its complexity, it has been defined as an NP problem. We introduce an online scheme to solve the problem of task scheduling under a dynamic load in the cloud environment. After analyzing the process, we propose a server level agreement constraint adaptive online task scheduling algorithm based on double deep Q-learning (SLA-DQTS) to reduce the makespan, cost, and average overdue time under the constraints of virtual machine (VM) resources and deadlines. In the algorithm, we prevent the change of the model input dimension with the number of VMs by taking the Gaussian distribution of related parameters as a part of the state space. Through the design of the reward function, the model can be optimized for different goals and task loads. We evaluate the performance of the algorithm by comparing it with three heuristic algorithms (Min-Min, random, and round robin) under different loads. The results show that the algorithm in this paper can achieve similar or better results than the comparison algorithms at a lower cost.

Value of Service Based Task Scheduling for Cloud Computing Systems

2016 ◽  
Author(s):  
Cihan Tunc ◽  
Nirmal Kumbhare ◽  
Ali Akoglu ◽  
Salim Hariri ◽  
Dylan Machovec ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Computing Systems

scholarly journals A WOA-Based Optimization Approach for Task Scheduling in Cloud Computing Systems

2020 ◽  
Vol 14 (3) ◽  
pp. 3117-3128
Author(s):  
Xuan Chen ◽  
Long Cheng ◽  
Cong Liu ◽  
Qingzhi Liu ◽  
Jinwei Liu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Optimization Approach ◽  
Computing Systems
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