C-AVPSO: DYNAMIC LOAD BALANCING USING AFRICAN VULTURE PARTICLE SWARM OPTIMIZATION
Journal Title: International Journal of Data Science and Artificial Intelligence - Year 2023, Vol 1, Issue 02
Abstract
Cloud computing is a novel technology that allows consumers to access services from anywhere, at any time, under different conditions, and is controlled by a third-party cloud provider. Cloud task scheduling is a complicated optimisation problem. However, both under- and over-loading conditions cause a range of system problems as far as power consumption, machine failures, and so forth are concerned. consequently, virtual machine (VM) work-load balancing is regarded as a key component of cloud task scheduling. In this paper, a novel cloud-based African vulture particle swarm optimisation [C-AVPSO] has been proposed. Using C-AVPSO, the developed optimization algorithm solves the dynamic load balancing problem effectively. In this method, the exploration space was obtained by using the AVO procedure whereas the enhanced response was identified by the PSO procedure. This algorithm successfully resolves resource utilization, response time, and cost constraints of the task. As a result of combining the AVO and PSO algorithms into the proposed AVPSO algorithm, the convergence rate and performance metrics for load balancing in the cloud environment are improved. To improve the operation's efficiency, the proposed method balances VM loads efficiently. The proposed framework is compared to existing approaches like QMPSO, FIMPSO and ACSO based on energy utilization, degree of imbalance and task migration, response time and resource utilization. The proposed C-AVPSO technique reduces resource utilization of 19.1%, 31%, and 54% than, QMPSO, FIMPSO and ACSO existing techniques.
Authors and Affiliations
D. Champla, Ghazanfar Ali Safdar, B. Muthukumar and M. Mohamed Sithik
Keywords
Related Articles
- EP ID EP742454
- DOI -
- Views 37
- Downloads 0
A STUDY ON SURGICAL ROBOTS AND THEIR RECENT DEVELOPMENTS
In recent years, Robotics has been rapidly developing with outstanding growth and innovation. This paper aims to analyze the key developments in the sub-domain of robotics such as medical robots, especially surgical robo...
EFFICIENT DATA SEARCH AND RETRIEVAL IN CLOUD ASSISTED IOT ENVIRONMENT
Internet of Things (IoT) is expanding across a number of industries, including the medical field. Such a scenario might easily reveal sensitive information, such as private digital medical records, presenting potential s...
SAREE TEXTURE ANALYSIS AND CLSSIFICATION VIA DEEP LEARNING FRAMEWORK
Indian women have worn sarees for centuries and have a significant market share in their clothing. Despite the ability to identify saree materials with tactile texture and the possibility to purchase online, it may not a...
YOLO-VEHICLE: REALTIME VEHICLE LICENCE PLATE DETECTION AND CHARACTER RECOGNITION USING YOLOV7 NETWORK
The demand for a secure lifestyle and travel is increasing due to the rapid development of technology. Since the turn of the century, the number of road vehicles has risen dramatically. The rapid growth of the vehicular...
REAL TIME MASKED FACE RECOGNITION USING DEEP LEARNING BASED YOLOV4 NETWORK
A global outbreak of COVID-19 has been spreading rapidly since 2019. This pandemic is making human existence more complex and intricate and thousands have been killed by this disease. A lack of antiviral medications is o...