Workflow Scheduling Based on Mobile Cloud Computing Machine Learning

In recent years, cloud workflow task scheduling has always been an important research topic in the business world. Cloud workflow task scheduling means that the workflow tasks submitted by users are allocated to appropriate computing resources for execution, and the corresponding fees are paid in real time according to the usage of resources. For most ordinary users, they are mainly concerned with the two service quality indicators of workflow task completion time and execution cost. Therefore, how cloud service providers design a scheduling algorithm to optimize task completion time and cost is a very important issue. This paper proposes research on workflow scheduling based on mobile cloud computing machine learning, and this paper conducts research by using literature research methods, experimental analysis methods, and other methods. This article has deeply studied mobile cloud computing, machine learning, task scheduling, and other related theories, and a workflow task scheduling system model was established based on mobile cloud computing machine learning from different algorithms used in processing task completion time, task service costs, task scheduling, and resource usage The situation and the influence of different tasks on the experimental results are analyzed in many aspects. The algorithm in this paper speeds up the scheduling time by about 7% under a different number of tasks and reduces the scheduling cost by about 2% compared with other algorithms. The algorithm in this paper has been obviously optimized in time scheduling and task scheduling.

Download Full-text

Multi-resource Task Scheduling for Minimum Task Completion Time in Cloud Computing Using Credit-Based Assignment Problem

Smart Computing Techniques and Applications - Smart Innovation, Systems and Technologies ◽

10.1007/978-981-16-0878-0_58 ◽

2021 ◽

pp. 597-607

Author(s):

Animoni Nagaraju ◽

Y. Rama Devi

Keyword(s):

Cloud Computing ◽

Task Scheduling ◽

Assignment Problem ◽

Completion Time ◽

Task Completion ◽

Task Completion Time

Download Full-text

Task Scheduling Allocation based on Task Completion Time in Cloud Environment

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.d7409.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 5207-5213

Keyword(s):

Resource Allocation ◽

Cloud Computing ◽

Load Balancing ◽

Task Scheduling ◽

Task Allocation ◽

Completion Time ◽

Resource Provisioning ◽

Task Completion ◽

Task Completion Time ◽

Survey Paper

Cloud computing is a prominent computing model wherein shared resources can be given as per the customer request at a time. The available resources in the cloud are gathered to execute several tasks that are submitted by the customer. While implementing the tasks, there is a need to optimize performance in terms of execution time, response time and resource utilization of the cloud. The optimization of the mentioned factors in the Cloud Computing can be achieved by one of the major areas known as Load balancing which refers to dealing with client requests from diverse application servers that are functioning in the cloud. An efficient Load Balancing algorithm enables the cloud to be more proficient and enhances customer contentment. So, this survey paper highlights the latest studies regarding the application of Load Balancing techniques for task allocation such as resource allocation (RA) strategies, cloud task scheduling centered on Load Balancing, dynamic Resource Allocation schemes, and cloud resource provisioning scheduling heuristics. Finally, Load Balancing performance for task allocation methods is compared based on task completion time.

Download Full-text

Research of Cloud Computing Task Scheduling Algorithm Based on Improved Genetic Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.347-350.2426 ◽

2013 ◽

Vol 347-350 ◽

pp. 2426-2429 ◽

Cited By ~ 6

Author(s):

Jun Wei Ge ◽

Yong Sheng Yuan

Keyword(s):

Genetic Algorithm ◽

Cloud Computing ◽

Task Scheduling ◽

Completion Time ◽

Scheduling Algorithm ◽

Task Completion ◽

Improved Genetic Algorithm ◽

Task Completion Time ◽

Task Scheduling Algorithm ◽

Reasonable Use

Use genetic algorithm for task allocation and scheduling has get more and more scholars' attention. How to reasonable use of computing resources make the total and average time of complete the task shorter and cost smaller is an important issue. The paper presents a genetic algorithm consider total task completion time, average task completion time and cost constraint. Compared with algorithm that only consider cost constraint (CGA) and adaptive algorithm that only consider total task completion time by the simulation experiment. Experimental results show that this algorithm is a more effective task scheduling algorithm in the cloud computing environment.

Download Full-text