DEEP LEARNING BASED LOAD BALANCING USING MULTIDIMENSIONAL QUEUING LOAD OPTIMIZATION ALGORITHM FOR CLOUD ENVIRONMENT
Journal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.9, No. 10)Publication Date: 2020-10-30
Authors : Deeksha Verma; Er. Shivani Rana;
Page : 156-167
Keywords : Cloud computing; Resource Scheduling; Load Balancing; Virtual Machines; MQLO algorithm; MRSQN technique and ANN.;
Abstract
Cloud computing becoming one of the most advanced and promising technologies in these days for information technology era. It has also helped to reduce the cost of small and medium enterprises based on cloud provider services. Resource scheduling with load balancing is one of the primary and most important goals of the cloud computing scheduling process. Resource scheduling in cloud is a non-deterministic problem and is responsible for assigning tasks to virtual machines (VMs) by a servers or service providers in a way that increases the resource utilization and performance, reduces response time, and keeps the whole system balanced. So in this paper, we presented a model deep learning based resource scheduling and load balancing using multidimensional queuing load optimization (MQLO) algorithm with the concept of for cloud environment Multidimensional Resource Scheduling and Queuing Network (MRSQN) is used to detect the overloaded server and migrate them to VMs. Here, ANN is used as deep learning concept as a classifier that helps to identify the overloaded or under loaded servers or VMs and balanced them based on their basis parameters such as CPU, memory and bandwidth. In particular, the proposed ANN-based MQLO algorithm has improved the response time as well success rate. The simulation results show that the proposed ANN-based MQLO algorithm has improved the response time compared to the existing algorithms in terms of Average Success Rate, Resource Scheduling Efficiency, Energy Consumption and Response Time
Other Latest Articles
- AN ARTIFICIAL NEURAL NETWORK BASED DEVELOPMENT OF CLOUD BURST FORECASTING MODEL BY USING TIME-SERIES DATA
- AN OPTIMIZED ENCRYPTION BASED STEGANOGRAPHY MODEL TO SECURE MEDICAL IMAGES USING METAHEURISTIC TECHNIQUE
- SOME MULTIPLICATIVE NEIGHBORHOOD TOPOLOGICAL INDICES OF NANOCONES AND DENDRIMERS
- RESEARCH ON APPLICATION OF TRAFFIC INFORMATION COLLECTION BASED ON MILLIMETER WAVE RADAR
- AN OPTIMIZED ANN BASED IMPROVED ENERGY EFFICIENT ZONE BASED ROUTING PROTOCOL IN MANET
Last modified: 2020-11-03 08:22:18