MrLBA: multi-resource load balancing algorithm for cloud computing using ant colony optimization

2021 ◽  
Author(s):  
Arfa Muteeh ◽  
Muhammad Sardaraz ◽  
Muhammad Tahir
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Load Balancing Algorithm

A Performed Load Balancing Algorithm for Public Cloud Computing Using Ant Colony Optimization

2018 ◽  
Vol 11 (3) ◽  
pp. 179-195 ◽  
Author(s):  
Awatif Ragmani ◽  
Amina El Omri ◽  
Nouredine Abghour ◽  
Khalid Moussaid ◽  
Mohammed Rida
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Public Cloud ◽  
Load Balancing Algorithm

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 Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management

2021 ◽  
Vol 11 (22) ◽  
pp. 10807
Author(s):  
Fatma Mbarek ◽  
Volodymyr Mosorov
Keyword(s):  
Distributed Computing ◽  
Load Balancing ◽  
Ant Colony Optimization ◽  
Dynamic Load ◽  
Nearest Neighbor ◽  
Ant Colony ◽  
Dynamic Load Balancing ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Load Balancing Algorithm

Many computer problems that arise from real-world circumstances are NP-hard, while, in the worst case, these problems are generally assumed to be intractable. Existing distributed computing systems are commonly used for a range of large-scale complex problems, adding advantages to many areas of research. Dynamic load balancing is feasible in distributed computing systems since it is a significant key to maintaining stability of heterogeneous distributed computing systems (HDCS). The challenge of load balancing is an objective function of optimization with exponential complexity of solutions. The problem of dynamic load balancing raises with the scale of the HDCS and it is hard to tackle effectively. The solution to this unsolvable issue is being explored under a particular algorithm paradigm. A new codification strategy, namely hybrid nearest-neighbor ant colony optimization (ACO-NN), which, based on the metaheuristic ant colony optimization (ACO) and an approximate nearest-neighbor (NN) approaches, has been developed to establish a dynamic load balancing algorithm for distributed systems. Several experiments have been conducted to explore the efficiency of this stochastic iterative load balancing algorithm; it is tested with task and nodes accessibility and proved to be effective with diverse performance metrics.

scholarly journals IMPROVED ANT COLONY LOAD BALANCING ALGORITHM IN CLOUD COMPUTING

2015 ◽  
Vol 14 (4) ◽  
pp. 5636-5644
Author(s):  
Jaspreet Singh ◽  
Susmita Mishra
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Computing Paradigm ◽  
Share Data ◽  
Load Balancing Algorithm ◽  
Scalable Network

Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently over a scalable network of nodes. Since Cloud computing stores the data and disseminated resources in the open environment. Since, cloud has inherited characteristic of distributed computing and virtualization there is a possibility of machines getting unused. Hence, in this paper, a load balancing algorithm has been proposed to avoid deadlocks and to provide proper utilization of all the Virtual Machines (VMs) while processing the requests received from the users by VM migration. Further, this paper also provides the anticipated results with the implementation of the proposed algorithm. The main contributions of our work is to balance the entire system load while trying to minimize the make span of a given set of jobs. Compared with the other job scheduling algorithms, the improved Ant Colony Optimization algorithm can outperform them according to the experimental results.

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