Reliable and Energy Efficient Resource Provisioning and Allocation in Cloud Computing

Sharma, Yogesh; Javadi, Bahman; Si, Weisheng; Sun, Daniel

doi:10.1145/3147213.3147218

Cited by 9 publications

(2 citation statements)

References 23 publications

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“…The term "Digital Watermarking" had its dawn in 1992 and since then it has been an active topic of research [21]. Its applications are continuously branching out to new advents in technology; for example, the process of watermarking a neural network is known as "passporting" [22,23], security in cloud storage systems [24,25], electronic money transfers, e-governance [26]. However, the use of watermarking for purposes of copyright protection and authentication has always been a key focus ever since its arrival [27,28], thus is also the focus of this discussion.…”

Section: Related Workmentioning

confidence: 99%

A single watermark based scheme for both protection and authentication of identities

Sharma

Zou

Fang

2022

IET Image Processing

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The security of a watermarking scheme is mainly categorised as either robust or fragile. The former can withstand an authorised alteration/attack, primarily used in copyright protection. The latter follows a zero tolerance towards any modification, used primarily in content authentication processes. The existing literature in the field projects that two separate watermarks are required to make a watermarking scheme robust and fragile, thus making the overall process cumbersome and complex. A novel image watermarking scheme that uses only one watermark while achieving both goals of copyright protection and authentication of identities is presented. An unconventional concept of checkpointing is introduced, which equips the proposed scheme to be either robust or fragile, making it superior in its application versatility. First, watermark embedding within the host/original image is achieved by a combination of transform domain techniques along with a novel median‐based embedding block selection procedure. Second, checkpointing is performed in the spatial domain. The watermarked image in the absence of an attack is correlated to the one that is being attacked, using the template energy comparison‐based approach. In the case of the robust watermark, such checkpointing can establish whether the carried out attack is authorised or not, determining the successful recovery of the watermark or vice‐versa. Moreover, in the case of the fragile watermark, a sole confirmation of the occurrence of an attack is sufficient to make the watermark recovery impossible. Finally, the experimental analysis of the proposed scheme illustrates its excellent performance and superiority over state‐of‐the‐art methods within the field.

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Section: Related Workmentioning

confidence: 99%

A single watermark based scheme for both protection and authentication of identities

Sharma

Zou

Fang

2022

IET Image Processing

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“…A dynamic load balancing method was presented based on dynamic workload and performance factors. Sharma et al considered three cloud resource provisioning methods and used a mathematical model to calculate the reliability and energy consumption of VMs on cloud computing. The methods are named Reliability Aware Best Fit Decreasing, Energy Aware Best Fit Decreasing, and Reliability‐Energy Aware Best Fit Decreasing.…”

Section: Related Workmentioning

confidence: 99%

An autonomic risk‐ and penalty‐aware resource allocation with probabilistic resource scaling mechanism for multilayer cloud resource provisioning

Mazidi

Golsorkhtabaramiri

Tabari

2020

Int J Communication

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Cloud computing environment allows presenting different services on the Internet in exchange for cost payment. Cloud providers can minimize their operational costs by auto-scaling of the computational resources based on demand received from users. However, the time and cost required to increase and decrease the number of active computational resources are among the biggest limitations of scalability. Thus, auto-scaling is considered as one of the most important challenges in the field of cloud computing.The present study aimed to present a new solution to automatic scalability of resources for multilayered cloud applications under the Monitor-Analysis-Plan-Execute-Knowledge loop. In addition, the Google penalty payment model was used to model the penalty costs in the problem and to accurately evaluate the earned profit. A hybrid resource load prediction algorithm was proposed to evaluate the future of resources in each cloud layer. Further, we used statistical solution to determine the statuses of VMs in addition to presenting a risk-aware algorithm to allocate the user requests to active resources. The experimental results by Cloudsim indicated the improvement of the proposed approach in terms of operational costs, the number of used resources, and the amount of profit. K E Y W O R D Scloud computing, multilayered application, operational cost, scalability

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An autonomic decision tree‐based and deadline‐constraint resource provisioning in cloud applications

Mazidi

Mahdavi

Roshanfar

2021

Concurrency and Computation

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Cloud computing provides a set of resources and services for customers on the Internet on demand and based on a pay as you go model. Cloud providers are looking to decrease costs and increase profits. Therefore, resource management and provisioning are very important for cloud providers. Automated scaling can be used to provide resources for user requests. Auto‐scaling can decrease the total operational costs for providers, although it does have its own cost and time overheads. In this paper, a new solution is presented for resource provisioning on multi‐layered cloud applications based on MAPE‐K loop. A weighted ensemble prediction model is proposed to estimate the resources utilization in each cloud layer. In addition, accuracy of the model and a regularization technique are used to regulate the weights of the models in the proposed hybrid prediction model. Furthermore, a decision tree‐based algorithm is presented to analyze status of the resources to make scaling decision. In addition, we propose a resource allocation algorithm that is based on Virtual Machine priority and request deadline in order to allocate requests on suitable resources. The experimental results indicate that the proposed algorithm has the best performance among its counterparts.

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Reliable and Energy Efficient Resource Provisioning and Allocation in Cloud Computing

Cited by 9 publications

References 23 publications

A single watermark based scheme for both protection and authentication of identities

A single watermark based scheme for both protection and authentication of identities

An autonomic risk‐ and penalty‐aware resource allocation with probabilistic resource scaling mechanism for multilayer cloud resource provisioning

An autonomic decision tree‐based and deadline‐constraint resource provisioning in cloud applications

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