SWARM INTELLIGENCE BASED TASK SCHEDULING ALGORITHM FOR LOAD BALANCING IN CLOUD SYSTEM

2022 ◽  
Vol 13 (2) ◽  
pp. 1
Author(s):  
Komalavalli D ◽  
Padma T
Keyword(s):  
Load Balancing ◽  
Swarm Intelligence ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Cloud System ◽  
Task Scheduling Algorithm

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.

Research of Load Balancing Scheduling under Grid Computing

2014 ◽  
Vol 577 ◽  
pp. 935-938
Author(s):  
Cheng Yu Cai ◽  
Yuan Sheng Lou
Keyword(s):  
Load Balancing ◽  
Grid Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
The Other ◽  
Task Scheduling Algorithm ◽  
Better Than

In order to make up for the shortage of Min-Min in load balancing, a new task scheduling algorithm T-Max-Int Under the grid computing has been proposed in this paper. In T-Max-Int, the Loss Degree of Max-Int has been brought into Min-Min. T was in the form of percentage, which represents the proportion of selected tasks that have loss degree in the total tasks. Then, experiments of T have been taken to make Makespan the minimum. Finally, T-Max-Int, Max-Min, Min-Min were compared, which proved that T-Max-Min is better than the other two algorithms in aspects of Makespan and load balancing.

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.

scholarly journals Ant Colony Optimization Task Scheduling Algorithm for SWIM Based on Load Balancing

2019 ◽  
Vol 11 (4) ◽  
pp. 90 ◽  
Author(s):  
Gang Li ◽  
Zhijun Wu
Keyword(s):  
Load Balancing ◽  
Ant Colony Optimization ◽  
Task Scheduling ◽  
Large Scale ◽  
Scheduling Algorithm ◽  
Pso Algorithm ◽  
Ant Colony ◽  
Experimental Simulation ◽  
Task Completion ◽  
Task Scheduling Algorithm

This paper focuses on the load imbalance problem in System Wide Information Management (SWIM) task scheduling. In order to meet the quality requirements of users for task completion, we studied large-scale network information system task scheduling methods. Combined with the traditional ant colony optimization (ACO) algorithm, using the hardware performance quality index and load standard deviation function of SWIM resource nodes to update the pheromone, a SWIM ant colony task scheduling algorithm based on load balancing (ACTS-LB) is presented in this paper. The experimental simulation results show that the ACTS-LB algorithm performance is better than the traditional min-min algorithm, ACO algorithm and particle swarm optimization (PSO) algorithm. It not only reduces the task execution time and improves the utilization of system resources, but also can maintain SWIM in a more load balanced state.

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