Load Balancing in Cloud Environment Using a Novel Hybrid Scheduling Algorithm

2015 ◽  
Author(s):  
Shridhar G. Domanal ◽  
G. Ram Mohana Reddy
Keyword(s):  
Load Balancing ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Hybrid Scheduling

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.

scholarly journals Dynamic Load Balancing Ant Colony Optimization (DLBACO) Algorithm for Task Scheduling in Cloud Environment

2019 ◽  
Vol 8 (12) ◽  
pp. 939-946
Keyword(s):  
Load Balancing ◽  
Ant Colony Optimization ◽  
Task Scheduling ◽  
Dynamic Load ◽  
Heuristic Algorithms ◽  
Scheduling Algorithm ◽  
Ant Colony ◽  
Dynamic Load Balancing ◽  
Cloud Environment ◽  
Task Scheduling Algorithm

Cloud computing is a framework which provides on-demand services to the user for scalability, security, and reliability based on pay as used service anytime & anywhere. For load balancing, task scheduling is the most critical issues in the cloud environment. There are so many meta-heuristic algorithms used to solve the load balancing problem. A good task scheduling algorithm should be used for optimum load balancing in cloud environment. Such scheduling algorithm must have some vital characteristic like minimum makespan, maximum throughput, and maximum resource utilization, etc. In this paper, a dynamic load balancing and task scheduling algorithm based on ant colony optimization (DLBACO) has been proposed. This algorithm assigns the task the VM which has highest probability of availability in minimum time. The proposed algorithm balances the whole system by minimizing the makespan of the task and maximizing the throughput. CloudSim simulator is used to simulate the proposed scheduling algorithm and results show that the proposed (DLBACO) algorithm is better than the existing algorithms such as FCFS, LBACO (Load balancing ACO), and primary ACO

scholarly journals A Hybrid AFSS-SHC Optimization Methodology for Balancing the Load Efficiently in Cloud Environment

2018 ◽  
Vol 7 (2.19) ◽  
pp. 70
Author(s):  
Aswini J ◽  
N Malarvizhi ◽  
Anitha. K ◽  
. .
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Main Challenge ◽  
Share Data ◽  
Cloud Framework ◽  
Optimization Methodology ◽  
The Cost

Cloud computing helps to share data and provide many resources to users. Users pay only for those resources as much they used. Rapid increase in load to these cloud framework cannot be predicted. Load balancing is one of the issues in cloud computing that distributes the workload to the nodes in such a way no node is overloaded or under - loaded. Load balancing is a main challenge in cloud environment.  In this work,  scheduling algorithm is applied for load balancing by considering the cost of  task execution and make span. This scheduling algorithm efficiently maps task to available nodes in cloud and it is beneficial to user and service provider. Load balancing segregates assignments of tasks among all available virtual machines from datacenters. Assignment of tasks to virtual machines can be done with minimum delay. To enhance the make span, resource utilization, our proposed framework utilizes AFSS-SHC load balancing strategy.  A metaheuristics swarm intelligence algorithm which is NP-hard have been suggested to balance load across devices. The algorithms taken into account are-HEFT,PSO and PSO-HC. The proposed methodology AFSS-SHC optimized the task scheduling. Random tasks have been taken for this purpose and simulated to show that the proposed methodology works efficiently to reduce the make span of tasks to reduce the cost.  

scholarly journals Enhancement of Security and Energy Efficiency in Cloud Computing

2019 ◽  
Vol 8 (2) ◽  
pp. 2459-2462
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Load Balancing ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Gang Scheduling ◽  
Job Scheduler ◽  
Heavy Application

This paper focuses on the job scheduling in cloud environment. Here the task has been scheduled in cloud and fog. Cloud provides services to heavy application while fog provides service to lighter application. The job scheduler would be helpful to reduce burden of cloud and help in energy optimization. The jobs are scheduled according to their types and priority. Various job scheduling algorithm such as gang scheduling, FCFS and round robin mechanism have been discussed in this research for load balancing and improve the compilation time. The simulation has been made using Matlab on virtual machines.

A Review on Load Balancing Model Using Best Partition Technique

2017 ◽  
Vol 7 (8) ◽  
pp. 284
Author(s):  
M. Chaitanya ◽  
K. Durga Charan
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
Load Balance ◽  
Large Impact ◽  
Cloud Environment ◽  
Public Cloud ◽  
The Public ◽  
Partition Technique ◽  
Textual Content

Load balancing makes cloud computing greater knowledgeable and could increase client pleasure. At reward cloud computing is among the all most systems which offer garage of expertise in very lowers charge and available all the time over the net. However, it has extra vital hassle like security, load administration and fault tolerance. Load balancing inside the cloud computing surroundings has a large impact at the presentation. The set of regulations relates the sport idea to the load balancing manner to amplify the abilties in the public cloud environment. This textual content pronounces an extended load balance mannequin for the majority cloud concentrated on the cloud segregating proposal with a swap mechanism to select specific strategies for great occasions.

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