WITHDRAWN: Optimized Adaptive load balancing algorithm in cloud computing

Velde, Venkateshwarlu; Enumala, Kiran; Bandi, Krishna

doi:10.1016/j.matpr.2021.01.750

Cited by 5 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Depending on their capabilities, the scheduling and load balancing method should accomplish the best/minimal task migration with equal load distribution across the resources. In a cloud setting, this method/process helps to get the best/fastest execution time [14]. By considering the jobs that do various tasks and their interdependencies, the algorithm should also consider the unpredictable nature of task allocation to the appropriate VMs.…”

Section: Related Workmentioning

confidence: 99%

Advanced scheduling algorithm for multi resource scheduling with minimum time consumption

Shakya

Tripathi

2023

Preprint

View full text Add to dashboard Cite

The scheduling of appropriate resources for cloud workloads is a difficult task, as it depends on the quality of service needs of cloud applications. Due to their limited data storage and energy capabilities, IoT applications demand high-speed data transfer and low latency. Many IoT devices generate data continuously and want to store it on the cloud quickly and efficiently. Dynamic virtual machine (VM) allocation in cloud data centers (DCs) is taking advantage of the cloud computing paradigm. Each VM request is characterized by four parameters: CPU, RAM, disk, and bandwidth. Allocators are designed to accept as many VM requests as possible, considering the power consumption of the IoT device's network. Resource scheduling and time consumption is the two most significant problems in cloud computing. To overcome this problem, in this paper, the author has extended CloudSim with a multi-resource scheduling and minimum time consumption model that allows a more accurate valuation of time consumption in dynamic multi-resource scheduling. The author proposes a new scheduling algorithm advance scheduling algorithm(ASA), which provides a better solution to other scheduling algorithms like Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Artificial Bee Colony(ABC). also tries to reduce energy consumption and time to give a task to the VM.

show abstract

Section: Related Workmentioning

confidence: 99%