Efficient Workflow Scheduling algorithm in cloud computing using Whale Optimization

Mangalampalli, Sudheer; Karri, Ganesh Reddy; Satish, G Naga

doi:10.1016/j.procs.2023.01.170

Cited by 8 publications

(2 citation statements)

References 12 publications

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“…It consistently outperforms alternative algorithms across various scenarios, underlining its supremacy in effectively managing dynamic workflow scheduling imbued with multiple objectives and unknown true Pareto-optimal fronts. Mangalampalli, et al [25] introduced a novel workflowscheduling mechanism that incorporates task priorities to schedule tasks onto appropriate virtual resources efficiently. The Whale Optimization Algorithm (WOA) was used as the methodology to model this algorithm.…”

Section: Related Workmentioning

confidence: 99%

Efficient Cloud Workflow Scheduling with Inverted Ant Colony Optimization Algorithm

DING,

ZHANG

2023

IJACSA

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Cloud computing has risen as a prominent paradigm, offering users on-demand access to computing resources and services via the Internet. In cloud environments, workflow scheduling plays a vital role in optimizing resource utilization, reducing execution time, and minimizing overall costs. As workflows comprise interdependent tasks that need to be assigned to Virtual Machines (VMs), the complexity of the scheduling problem increases in proportion to workflow size and VM availability. Due to its NP-hard nature, finding an optimal scheduling solution for workflows remains a challenging task. To address this problem, researchers have turned to metaheuristic approaches, which have shown promise in finding near-optimal solutions for complex combinatorial optimization problems. This paper proposes a novel metaheuristic algorithm called Inverted Ant Colony Optimization (IACO) for workflow scheduling in cloud environments. IACO is a variation of the traditional ACO algorithm, where the updated pheromone has an inverted influence on the path chosen by the ants. By leveraging the complementary nature of these two algorithms, our proposed algorithm aims to achieve superior workflow scheduling performance regarding total execution time and cost, surpassing existing approaches.

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Section: Related Workmentioning

confidence: 99%

Efficient Cloud Workflow Scheduling with Inverted Ant Colony Optimization Algorithm

DING,

ZHANG

2023

IJACSA

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“…Results proved that AINN-PSO is dominant in minimizing energy consumption, start time, makespan. In [13], authors used whale optimization to model scheduling algorithm addresses makespan, migration time, energy consumption. For this approach, authors calculated task priorities carefully to schedule workflows onto precise virtual resources.…”

Section: Related Workmentioning

confidence: 99%

SLA based Workflow Scheduling algorithm in Cloud Computing using Haris Hawks optimization

Mangalampalli,

Karri,

Pokkuluri

et al. 2023

ICST Transactions on Scalable Information Systems

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Task Scheduling is crucial facet in cloud paradigm as virtual resources need to be provisioned to the variable requests coming onto cloud console from various users and more over that tasks are depends on each other which creates a workflow which is a difficult task for cloud service provider to provision these tasks over appropriate VMs. Inefficient mapping of tasks to VMs increases makespan and lead to violation of SLA between users, cloud provider. In this paper, we modeled a SLA based workflow scheduling algorithm focuses on minimization of makespan and SLA violations. This algorithm developed using Harris hawks optimization. Experimentation carried out using workflowsim. Random workload fed as input to algorithm and it is evaluated against existing baseline approaches and simulation results revealed that our proposed approach minimizes makespan and SLA violations over existing approaches by 40% and 43% respectively.

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A comprehensive survey on scheduling algorithms using fuzzy systems in distributed environments

Jalali Khalil Abadi,

Mansouri

2024

Artif Intell Rev

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Efficient Workflow Scheduling algorithm in cloud computing using Whale Optimization

Cited by 8 publications

References 12 publications

Efficient Cloud Workflow Scheduling with Inverted Ant Colony Optimization Algorithm

Efficient Cloud Workflow Scheduling with Inverted Ant Colony Optimization Algorithm

SLA based Workflow Scheduling algorithm in Cloud Computing using Haris Hawks optimization

A comprehensive survey on scheduling algorithms using fuzzy systems in distributed environments

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