A Novel Parallel Jobs Scheduling Algorithm in The Cloud Computing

Mohtajollah, Zahra; Adibnia, Fazlollah

doi:10.1109/iccke48569.2019.8964727

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…Mohtajollah and Adibnia [47] proposed an algorithm for parallel job scheduling in cloud computing. They used tentative runs, workload consolidation and two-tier virtual machines architecture.…”

Section: Co-schedulingmentioning

confidence: 99%

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A State of Art: Survey for Concurrent Computation and Clustering of Parallel Computing for Distributed Systems

Shukur

Zeebaree

Ahmed

et al. 2020

JASTT

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In this paper, several works has been presented related to the clustering parallel computing for distributed system. The trend of the paper is to focus on the strength points of previous works in this field towards enhancing performance of the distributed systems. This concentration conducted via presenting several techniques where each of them has the weak and strong features. The most challenging points for all techniques vary from increasing the performance of the system to time responding to overcome overhead running of the system. For more specific addressing concurrent computation besides parallel computing classifications for distributed systems, this paper depended comprehensive features study and comparison between SYNC and ASYNC Modes.

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Section: Co-schedulingmentioning

confidence: 99%

“…and Adibnia [47]  The authors used several techniques to propose a new algorithm in order to improve job scheduling in cloud computing.  The make-span of the job scheduling was reduced and maximum waiting time.…”

Section: Mohtajollahmentioning

confidence: 99%

A State of Art: Survey for Concurrent Computation and Clustering of Parallel Computing for Distributed Systems

Shukur

Zeebaree

Ahmed

et al. 2020

JASTT

View full text Add to dashboard Cite

show abstract

“…Different architectures, such as monolithic or microservices, can have different requirements in terms of resource allocation and workload scheduling [10]. It is important to select the right architecture for the specific workload and to ensure that the workload scheduling process is optimized accordingly [11], [12]. In summary, workload scheduling for web server composition in the cloud is a complex process that requires careful consideration of a range of factors, including traffic variability, energy consumption, deadline execution and load balancing.…”

Section: Introductionmentioning

confidence: 99%

Quality of Service Aware Task Replanning Algorithm for Web-Service Provisioning in Cloud Environment

2024

IJIES

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In web service composition, the combination of multiple individual services to create complex workflows introduces additional challenges, and task scheduling is a crucial aspect that significantly impacts the overall system performance. The main challenge in web service composition task scheduling arises from the varying nature of services, which may have diverse processing requirements, data dependencies, and execution times. Hence, to address these challenges, the existing work have proposed many methods. But, as cloud environments often host these web services, the dynamic nature of cloud resources and the unpredictability of workloads add another layer of complexity to the task scheduling process. Due to this the existing works have attempted very less work on providing an efficient replanning task based on real-time changes in resource availability. Hence, this paper proposes a novel approach to cloud workload task scheduling in web service composition that incorporates efficient replanning and time complexity analysis called as Web service composition-efficient re-planning (WSC-ERP). The proposed approach takes into account various factors, such as task dependencies, and resource availability, to generate an optimized schedule that minimizes execution time and maximizes resource utilization. The WSC-ERP has been evaluated using the Montage scientific workload. The results show that the WSC-ERP provides better performance in terms of executional time, power sum, power average, energy consumption and reliability when compared with the Energy-Minimized Scheduling (EMS), and Evolutionary Computing based Web Service Composition (EC-WSC). The results show that the WSC-ERP has showed an improvement of 80.27% and 78.45% for average execution time, 89.98% and 87.49% for average power sum, 63.44% and 41.93% for average power average, 92.58% and 87.87% for average energy consumption, 4.97% and 4.07% for average reliability when compared with the existing EMS and EC-WSC models respectively.

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Optimizing User-PC Computing System with Multicore CPU Utilization through Parallel Computing Jobs Distributions

Riyantoko,

Funabiki,

Zhuo

et al. 2023

2023 International Electronics Symposium (IES)

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A Novel Parallel Jobs Scheduling Algorithm in The Cloud Computing

Cited by 3 publications

References 9 publications

A State of Art: Survey for Concurrent Computation and Clustering of Parallel Computing for Distributed Systems

A State of Art: Survey for Concurrent Computation and Clustering of Parallel Computing for Distributed Systems

Quality of Service Aware Task Replanning Algorithm for Web-Service Provisioning in Cloud Environment

Optimizing User-PC Computing System with Multicore CPU Utilization through Parallel Computing Jobs Distributions

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