Optimal Load Balancing In Three Level Cloud Computing Using Osmotic Hybrid And Firefly Algorithm

2020 ◽  
Author(s):  
Sanjeev Kumar Ojha ◽  
Himanshu Rai ◽  
Alexey Nazarov
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Firefly Algorithm ◽  
Optimal Load

A Hybrid Meta-Heuristic for Optimal Load Balancing in Cloud Computing

2021 ◽  
Vol 19 (2) ◽  
Author(s):  
G. Annie Poornima Princess ◽  
A. S. Radhamani
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Optimal Load

scholarly journals Efficient Load Balancing and Service Broker Policy Using Local and Global Representatives in Cloud Computing

2019 ◽  
Vol 8 (10) ◽  
pp. 2680-2687
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Service Level Agreement ◽  
Service Level ◽  
The Other ◽  
Optimal Load ◽  
Important Challenge ◽  
Service Broker ◽  
Local Representative ◽  
Local User

Cloud computing is a technology in the field of computing which offer services to the customer from anywhere at any time [1]. In the cloud, resources are shared all around the work for quick servicing to the customer. The aggregation of two terms is referred as cloud computing. The term “cloud” is a pool of different resources offers services to the end customers and “computing” is done based on the Service Level Agreement (SLA) to make the resources efficiently to the customers. Load balancing is an important challenge in the environment of the cloud to increase the utilization of resources [3]. Here we proposed an algorithm which is based on load balancing and service broker policy. We user two representative thin the proposed approach local representative and global representative Local user representative is used to predict the parameters of user task and based on priority it allocate the task to the Virtual Machine (VM). Then for scheduling the task and provide the services to the users based on the available cloud brokers global user representative used Dynamic Optimal Load-Aware Service Broker (DOLASB).we used two scenario with different no. of user requests , in these scenario result of our proposed method is better as compared with the other existing methods in terms s of Execution Time, Makespan, Waiting Time, Energy Efficiency and Throughput.

Load balancing in cloud environs: Optimal task scheduling via hybrid algorithm

2021 ◽  
pp. 2150008
Author(s):  
Shashikant Raghunathrao Deshmukh ◽  
S. K. Yadav ◽  
D. N. Kyatanvar
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Task Scheduling ◽  
Optimization Algorithm ◽  
Critical Issue ◽  
Task Completion ◽  
Optimal Load ◽  
Whale Optimization ◽  
Np Hard Problem ◽  
Conventional Models

In cloud computing, a lot of challenges like the server failures, loss of confidentiality, improper workloads, etc. are still bounding the efficiency of cloud systems in real-world scenarios. For this reason, many research works are being performed to overcome the shortcoming of existing systems. Among them, load balancing seems to be the most critical issue that worsen the performance of the cloud sector, and hence there necessitates the optimal load balancing with optimal task scheduling. With the intention of accomplishing optimal load balancing by effectual task deployment, this paper plans to develop an advanced load balancing model with the assistance acquired from the metaheuristic algorithms. Usually, handling of tasks in cloud system is an NP-hard problem and moreover, nonpreemptive independent tasks are crucial in cloud computing. This paper goes with the introduction of a new optimal load balancing model by considering three major objectives: minimum makespan, priority, and load balancing, respectively. Moreover, a new single-objective function is also defined that incorporates all the three objectives mentioned above. Furthermore, the deployment of tasks must be optimal and for this a new hybrid optimization algorithm referred as Firefly Movement insisted WOA (FM-WOA) is introduced. This FM-WOA is the conceptual amalgamation of standard Whale Optimization Algorithm (WOA) and Firefly (FF) algorithm. Finally, the performances of the proposed FM-WOA model is compared over the conventional models with the intention of proving its efficiency in terms of makespan, task completion (priority), and degree of imbalance as well.

A load balancing model using bio inspired firefly algorithm in cloud computing

2017 ◽  
Vol 7 (1.1) ◽  
pp. 671 ◽  
Author(s):  
Vikas . ◽  
M Sai Vivek ◽  
Pushyami Manohar
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Firefly Algorithm ◽  
Process Time ◽  
Shared Resources ◽  
Time Intervals ◽  
Load Model ◽  
Request Sequence ◽  
Cloud Server ◽  
Index Table

Cloud computing is a model which helps in accessing the end-users interface which is adjustable as well as flexible service on Internet. The primary aim implemented scheme is for maximizing utilization of resource. It also offers a load which is good balanced compared to the all other resources in the servers of cloud. Some fundamental characteristics like usage of memory, process time, rate of the access, a resource load model can be deliver, by considering the load index which is new, present load computed to the virtual machine cloud server shared resources. If a load index calculated to the resources then initiation of balancing load for efficient utilization of resources. After all resources load index computed, the load balancing operation started to use the resources effectively by assigned resources processing for respective node for decreasing values of the load. The assignment of the resources to the nodes which are proper will become a problem i.e. optimal distribution. For this huge number of optimised schemes like algorithm of genetic, algorithm of modified genetic will be used to balance the load. But all these are may not be effective to offer best solutions. Because, the exploration issues are not overcome in these approaches. However, we can say that procedure of efficient optimisation is good for balancing load compared to others. Therefore, we implemented a new scheme for optimisation approach which is known as firefly algorithm for balancing the load. Initially the index table updated with the help of available virtual servers as well as request sequence. After that, based on new formulae, the load index will be calculated. The bal-ance of the load can be done with the help of load index using the algorithm of firefly. The results which are expected can be gathered and the implemented algorithm is efficient to balance the load in optimised time intervals.  

Sign in / Sign up

Export Citation Format

Share Document