An Efficient Job Scheduling in Isometric HPCLOUD Using ZBLA Optimization

Miriam, D. Doreen Hephzibah; Prabha, B.; Lilian, J. Felicia

doi:10.1016/j.procs.2015.04.043

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…Honey bee behavior (HBB) in search of a food source was modeled as a scheduling algorithm in cloud computing by Miriam et al [16]. Te virtual machine workload was calculated by the HBB algorithm and classifed as overloaded, balanced, and light-weighed.…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of Novel Random Biased-Genetic Algorithm (NRB-GA): A Hybrid Load Balancing Algorithm in a Cloud Computing Environment

Subramanian

Dalu

2022

Scientific Programming

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A novel random biased-genetic algorithm (NRB-GA) load-balancing algorithm that exhibits the characteristics of both genetic algorithms and biased random algorithms is designed and developed to improve the processing time and response time metrics of the cloud computing environment. The NRB-GA is designed to discover a virtual machine with fewer loads by applying a genetic algorithm with a fitness function that is inversely proportional to the average load over a period of time for each virtual machine and with biased parent selection to maximize the fitness values of offspring. The developed NRB-GA load-balancing algorithm is evaluated by analysing its performance for various simulated scenarios in a cloud computing environment with different user bases and data center configurations. The analysis of the experimental results of NRB-GA indicates that the average response time is reduced by 27.22%, 21.15%, and 22.34%, and the processing time is reduced by 25.73%, 16.14%, and 18.82% for one, two, and three data centers, respectively. It is evident that the proposed NRB-GA algorithm for load balancing outperforms other existing algorithms significantly.

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Section: Related Workmentioning

confidence: 99%

Performance Evaluation of Novel Random Biased-Genetic Algorithm (NRB-GA): A Hybrid Load Balancing Algorithm in a Cloud Computing Environment

Subramanian

Dalu

2022

Scientific Programming

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“…In addition, round-robin, Max-Min, and Min-Min algorithms are also considered applications of BMHA. Whereas, OMHA fetches and processes jobs from queue waiting directly [8,20,21]. The BMHA is considered one of the most suitable algorithms for the cloud computing environment.…”

Section: Cloud Computingmentioning

confidence: 99%

A hybrid approach for scheduling applications in cloud computing environment

Abdalkafor¹,

Alheeti²

2020

IJECE

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Cloud computing plays an important role in our daily life. It has direct and positive impact on share and update data, knowledge, storage and scientific resources between various regions. Cloud computing performance heavily based on job scheduling algorithms that are utilized for queue waiting in modern scientific applications. The researchers are considered cloud computing a popular platform for new enforcements. These scheduling algorithms help in design efficient queue lists in cloud as well as they play vital role in reducing waiting for processing time in cloud computing. A novel job scheduling is proposed in this paper to enhance performance of cloud computing and reduce delay time in queue waiting for jobs. The proposed algorithm tries to avoid some significant challenges that throttle from developing applications of cloud computing. However, a smart scheduling technique is proposed in our paper to improve performance processing in cloud applications. Our experimental result of the proposed job scheduling algorithm shows that the proposed schemes possess outstanding enhancing rates with a reduction in waiting time for jobs in queue list.

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Valuable survey on scheduling algorithms in the cloud with various publications

Bansal

Singh

2022

Int J Syst Assur Eng Manag

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An Efficient Job Scheduling in Isometric HPCLOUD Using ZBLA Optimization

Cited by 3 publications

References 12 publications

Performance Evaluation of Novel Random Biased-Genetic Algorithm (NRB-GA): A Hybrid Load Balancing Algorithm in a Cloud Computing Environment

Performance Evaluation of Novel Random Biased-Genetic Algorithm (NRB-GA): A Hybrid Load Balancing Algorithm in a Cloud Computing Environment

A hybrid approach for scheduling applications in cloud computing environment

Valuable survey on scheduling algorithms in the cloud with various publications

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