scholarly journals Study of Task Scheduling Strategy based on Trustworthiness

2021 ◽  
Vol 12 (05) ◽  
pp. 01-09
Author(s):  
Jun QIN ◽  
Yanyan SONG ◽  
Ping ZONG
Keyword(s):  
Task Scheduling ◽  
Programming Model ◽  
Fault Tolerant ◽  
Scheduling Algorithm ◽  
Massive Data ◽  
Scheduling Strategy ◽  
Computing Model ◽  
Scheduling Model ◽  
Task Scheduling Algorithm ◽  
The Stability

MapReduce is a distributed computing model for cloud computing to process massive data. It simplifies the writing of distributed parallel programs. For the fault-tolerant technology in the MapReduce programming model, tasks may be allocated to nodes with low reliability. It causes the task to be reexecuted, wasting time and resources. This paper proposes a reliability task scheduling strategy with a failure recovery mechanism, evaluates the trustworthiness of resource nodes in the cloud environment and builds a trustworthiness model. By using the simulation platform CloudSim, the stability of the task scheduling algorithm and scheduling model are verified in this paper.

scholarly journals Research on Task Scheduling Strategy based on the Trustworthiness of MapReduce

2021 ◽  
Author(s):  
QIN Jun ◽  
SONG Yanyan ◽  
ZONG Ping
Keyword(s):  
Task Scheduling ◽  
Programming Model ◽  
Fault Tolerant ◽  
Scheduling Algorithm ◽  
Rapid Development ◽  
Computing Technology ◽  
Scheduling Strategy ◽  
Task Scheduling Algorithm ◽  
Good Environment ◽  
Massive Data Processing

With the rapid development and popularization of information technology, cloud computing technology provides a good environment for solving massive data processing. Hadoop is an open-source implementation of MapReduce and has the ability to process large amounts of data. Aiming at the shortcomings of the fault-tolerant technology in the MapReduce programming model, this paper proposes a reliability task scheduling strategy that introduces a failure recovery mechanism, evaluates the trustworthiness of resource nodes in the cloud environment, establishes a trustworthiness model, and avoids task allocation to low reliability node, causing the task to be re-executed, wasting time and resources. Finally, the simulation platform CloudSim verifies the validity and stability of the task scheduling algorithm and scheduling model proposed in this paper.

scholarly journals Optimization and Simulation of a Reasonable Scheduling Model under Multiple Tasks in Company Management

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Zhuo Wang
Keyword(s):  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Rapid Development ◽  
Optimal Solution ◽  
Solution Space ◽  
Corporate Management ◽  
Model Based ◽  
Scheduling Model ◽  
Optimization And Simulation ◽  
The Stability

With the rapid development of market economy, the task scheduling model has become the core problem in the field of corporate management. In order to solve the problem that the stability of the model will decline due to the interference of human factors in the process of multitask scheduling in the traditional algorithm, a reasonable scheduling model based on the priority principle is proposed in this paper. This paper expounds the principle of multitask scheduling in company management, constructs a multitask scheduling network model based on priority, performs virtual scheduling on the model, searches the optimal solution in the solution space of the scheduling problem, and obtains the reasonable multitask scheduling method in the company management. Through the analysis of relevant simulation experiments, it can be concluded that the task scheduling algorithm proposed in this paper can not only allocate the corresponding resources for high-priority tasks effectively, but also can save the cost, so as to show better execution efficiency.

scholarly journals Edge computing task scheduling strategy based on load balancing

2020 ◽  
Vol 309 ◽  
pp. 03025
Author(s):  
Lintan Sun ◽  
Zigan Li ◽  
Jingxian Lv ◽  
Chenfei Wang ◽  
Yajuan Wang ◽  
...  
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Rapid Development ◽  
Mobile Terminal ◽  
Heavy Load ◽  
Dynamic Selection ◽  
Scheduling Strategy ◽  
Light Load ◽  
Task Scheduling Algorithm

With the rapid development and wide application of the Internet of Everything, in order to cope with the increasing amount of data and computational scale of mobile terminal processing, and the imbalance of existing scheduling algorithms and low resource utilization, this paper proposes a task scheduling algorithm based on business priority. The algorithm firstly divides the service according to the priority of the service. Secondly, the standard deviation of the computing task group is used to determine the proportion of long and short services, and the dynamic selection model is established. Finally, according to the idea of secondary allocation, the task of heavy load is assigned to the scheduling strategy of light load resources to execute, and the service redistribution model is established. The simulation results show that compared with the typical algorithm, the proposed algorithm achieves the result of comprehensive consideration of Makespan and load balancing to improve system efficiency.

Optimization of makespan and resource utilization in the fog computing environment through task scheduling algorithm

2020 ◽  
Vol 18 (01) ◽  
pp. 1941025
Author(s):  
R. Vijayalakshmi ◽  
V. Vasudevan ◽  
Seifedine Kadry ◽  
R. Lakshmana Kumar
Keyword(s):  
Resource Utilization ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Utilization Rate ◽  
Test Results ◽  
Computing Environment ◽  
Computing Model ◽  
Task Scheduling Algorithm ◽  
The Mean

The Fog computing is rising as a dominant and modern computing model to deliver Internet of Things (IoT) computations, which is an addition to the cloud computing standard to get it probable to perform the IoT requests in the network of edge. In those above independent and dispersed environment, resource allocation is vital. Therefore, scheduling will be a test to enhance potency and allot resources properly to the tasks. This paper offers a distinct task scheduling algorithm in the fog computing environment that tries to depreciate the makespan and maximize resource utilization. This algorithm catalogues the task based on the mean Suffrage value. The suggested algorithm gives much resource utilization and diminishes makespan. Our offered algorithm is compared with different alive scheduling for performance investigation, and test results confirm that our algorithm has a more significant resource utilization rate and low makespan than other familiar algorithms.

Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

2018 ◽  
pp. 96-101
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Waiting Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Task Scheduling Algorithm ◽  
Machine Utilization ◽  
Independent Tasks ◽  
Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

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