Task Scheduling for Multi-Cloud Computing Subject to Security and Reliability Constraints

Zhu, Qinghua; Tang, Huan; Huang, Jia-Jie; Yan, Haowen

doi:10.1109/jas.2021.1003934

Cited by 99 publications

(44 citation statements)

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“…This algorithm has a temporary storage area, that is secure and easily accessible by cloud consumers. The authors in [49] proposed a trust aware task scheduling approach known as matching and multi-round allocation (MMA) for optimizing the makespan and the associated cost for each task. The paper also deals with the security constraints concerning the tasks that works in two phases for executing the scheduling of tasks.…”

Section: Related Workmentioning

confidence: 99%

Alts: An Adaptive Load Balanced Task Scheduling Approach for Cloud Computing

et al. 2021

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According to the research, many task scheduling approaches have been proposed like GA, ACO, etc., which have improved the performance of the cloud data centers concerning various scheduling parameters. The task scheduling problem is NP-hard, as the key reason is the number of solutions/combinations grows exponentially with the problem size, e.g., the number of tasks and the number of computing resources. Thus, it is always challenging to have complete optimal scheduling of the user tasks. In this research, we proposed an adaptive load-balanced task scheduling (ALTS) approach for cloud computing. The proposed task scheduling algorithm maps all incoming tasks to the available VMs in a load-balanced way to reduce the makespan, maximize resource utilization, and adaptively minimize the SLA violation. The performance of the proposed task scheduling algorithm is evaluated and compared with the state-of-the-art task scheduling ACO, GA, and GAACO approaches concerning average resource utilization (ARUR), Makespan, and SLA violation. The proposed approach has revealed significant improvements concerning the makespan, SLA violation, and resource utilization against the compared approaches.

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Section: Related Workmentioning

confidence: 99%

Alts: An Adaptive Load Balanced Task Scheduling Approach for Cloud Computing

et al. 2021

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“…On the other hand, the DVFS technique was conducted to reduce the processor frequency at both processor and task levels to save more power and reduce energy consumption. In a heterogeneous multicloud environment, matching and multiround allocation (MMA) as a scheduling algorithm was proposed to meet trust constraints 35 . This algorithm aims to minimize the makespan and total cost of tasks while ensuring security and reliability criteria.…”

Section: Related Workmentioning

confidence: 99%

A new reliability‐based task scheduling algorithm in cloud computing

Motlagh

Movaghar

Rahmani

2021

Int J Communication

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Summary In the last decade, the scale of heterogeneous computing (HC) systems such as heterogeneous cloud computing environments was growing like never before. So network failures are unavoidable in such systems, which affect system reliability. Since the task scheduling algorithm in HC is challenging, we investigate a new reliability‐aware task scheduling algorithm (RATSA) in this paper. RATSA is designed to schedule tasks on directed acyclic graphs (DAGs) by using the shuffled frog‐leaping algorithm (SFLA) and genetic algorithm (GA) as evolutionary algorithms. The population‐based SFLA‐GA is applied to optimize makespan in the RATSA as an NP‐complete problem. Moreover, the proposed algorithm exploits a new heuristic‐based earliest finish time technique for task mapping to virtual machines (VMs) section to decrease the failure rate. Experimental results on random DAGs indicate that RATSA improves some current algorithms in terms of reliability and has acceptable performance in makespan. The results reveal that the RATSA decreases the overall failure rate by 43% compared to some current task scheduling algorithms.

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“…Zhu et al [13] proposed a new scheduling technique named MMA for optimizing make span and overall costs for entire submitted process subject to reliability and security limitations. This technique is separated to 2 stages for scheduling task.…”

Section: Review Of Existing Security Related Solutions For Multi-cloud Architecturesmentioning

confidence: 99%

An Analysis of Privacy Preserving Data Storage and Retrieval Approaches in Heterogeneous Multi-cloud Architectures

Suganya¹,

Sasipraba²

2021

INDJCSE

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Cloud storage and retrieval are considered essential services of cloud computing (CC), which enables the data owner to store the data from the local computing systems to the cloud. Though cloud storage provides several benefits such as minimal cost and short turnaround time, data security is found to be a highly challenging and difficult process. One of the effective solutions to avoid data loss related to security risks is the concurrent usage of multi-cloud. The multi-cloud allows the data owner to easily access their data from remote areas via the web interfaces offered by Amazon EC2. However, even if such multi-cloud environments are susceptible to security attacks, it would bring irreversible challenges to the owners namely integrity, availability, and confidentiality of data. In order to resolve these issues, several privacy preserving data storage and retrieval models are presented in the literature to store data securely and reduce the computational resources. In this view, this study performs a review of existing state of art data storage and retrieval approaches for heterogeneous multi-cloud architectures. The reviewed methods are investigated based on their objectives, underlying techniques, implementation data, and evaluation parameters. Besides, a comparative results analysis of few of the reviewed models takes place. Finally, a discussion along with the possible future direction is given to enable the readers to find the research problem.

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Task Scheduling for Multi-Cloud Computing Subject to Security and Reliability Constraints

Cited by 99 publications

References 50 publications

Alts: An Adaptive Load Balanced Task Scheduling Approach for Cloud Computing

Alts: An Adaptive Load Balanced Task Scheduling Approach for Cloud Computing

A new reliability‐based task scheduling algorithm in cloud computing

An Analysis of Privacy Preserving Data Storage and Retrieval Approaches in Heterogeneous Multi-cloud Architectures

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