TY  - EJOU
AU  - Kumar, V. Dhilip 
AU  - Praveenchandar, J. 
AU  - Arif, Muhammad 
AU  - Brezulianu, Adrian 
AU  - Geman, Oana 
AU  - Ikram, Atif 

TI  - Efficient Cloud Resource Scheduling with an Optimized Throttled Load Balancing Approach
T2  - Computers, Materials \& Continua

PY  - 2023
VL  - 77
IS  - 2
SN  - 1546-2226

AB  - Cloud Technology is a new platform that offers on-demand computing Peripheral such as storage, processing power, and other computer system resources. It is also referred to as a system that will let the consumers utilize computational resources like databases, servers, storage, and intelligence over the Internet. In a cloud network, load balancing is the process of dividing network traffic among a cluster of available servers to increase efficiency. It is also known as a server pool or server farm. When a single node is overwhelmed, balancing the workload is needed to manage unpredictable workflows. The load balancer sends the load to another free node in this case. We focus on the Balancing of workflows with the proposed approach, and we present a novel method to balance the load that manages the dynamic scheduling process. One of the preexisting load balancing techniques is considered, however it is somewhat modified to fit the scenario at hand. Depending on the experimentation’s findings, it is concluded that this suggested approach improves load balancing consistency, response time, and throughput by 6%.
KW  - Load balancing; throttled algorithm; efficient resource allocation

DO  - 10.32604/cmc.2023.034764