A Novel Approach in Cloud Computing for Load Balancing Using Composite Algorithms

2017 ◽  
Vol 7 (2) ◽  
pp. 51-56 ◽  
Author(s):  
Rajesh Sachdeva ◽  
◽  
Sanjeev Kakkar ◽  
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Novel Approach

Hermit: A Novel Approach for Dynamic Load Balancing in Cloud Computing

2020 ◽  
pp. 275-287
Author(s):  
Subasish Mohapatra ◽  
Subhadarshini Mohanty ◽  
Arunima Hota ◽  
Prashanta Kumar Patra ◽  
Jijnasee Dash
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Dynamic Load ◽  
Dynamic Load Balancing ◽  
Novel Approach

A Novel Approach of Load Balancing and Task Scheduling Using Ant Colony Optimization Algorithm

2019 ◽  
Vol 7 (2) ◽  
pp. 9-20 ◽  
Author(s):  
Selvakumar A. ◽  
Gunasekaran G.
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Novel Approach ◽  
Productive Asset ◽  
Reduce Energy Consumption ◽  
Set Up

Cloud computing is a model for conveying data innovation benefits in which assets are recovered from the web through online devices and applications, instead of an immediate association with a server. Clients can set up and boot the required assets and they need to pay just for the required assets. Subsequently, later on giving a component to a productive asset administration and the task will be a vital target of Cloud computing. Load balancing is one of the major concerns in cloud computing, and the main purpose of it is to satisfy the requirements of users by distributing the load evenly among all servers in the cloud to maximize the utilization of resources, to increase throughput, provide good response time and to reduce energy consumption. To optimize resource allocation and ensure the quality of service, this article proposes a novel approach for load-balancing based on the enhanced ant colony optimization.

scholarly journals A NOVEL APPROACH OF OPTIMIZING PERFORMANCE USING K-MEANS CLUSTERING IN CLOUD COMPUTING

2016 ◽  
Vol 15 (14) ◽  
pp. 7435-7443 ◽  
Author(s):  
Sheenam Kamboj ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Turnaround Time ◽  
Cloud Environment ◽  
Single Node ◽  
Novel Approach ◽  
Load Balancing Algorithm

Cloud computing is distributed computing, storing, sharing and accessing data over the Internet. It provides a pool of shared resources to the users available on the basis of pay as you go service that means users pay only for those services which are used by him according to their access times. Load balancing ensures that no single node will be overloaded and used to distribute workload among multiple nodes. It helps to improve system performance and proper utilization of resources. We propose an improved load balancing algorithm for job scheduling in the cloud environment using K-Means clustering of cloudlets and virtual machines in the cloud environment. All the cloudlets given by the user are divided into 3 clusters depending upon client’s priority, cost and instruction length of the cloudlet. The virtual machines inside the datacenter hosts are also grouped into multiple clusters depending upon virtual machine capacity in terms of processor, memory, and bandwidth. Sorting is applied at both the ends to reduce the latency. Multiple number of experiments have been conducted by taking different configurations of cloudlets and virtual machine. Various parameters like waiting time, execution time, turnaround time and the usage cost have been computed inside the cloudsim environment to demonstrate the results. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results. 

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