Encryption with access policy and cloud data selection for secure and energy-efficient cloud computing

Multimedia Tools and Applications, Journal Year: 2023, Volume and Issue: 83(6), P. 15649 - 15675

Published: July 18, 2023

Language: Английский

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Multi-objective secure aware workflow scheduling algorithm in cloud computing based on hybrid optimization algorithm

Web Intelligence, Journal Year: 2023, Volume and Issue: 21(4), P. 385 - 405

Published: July 28, 2023

Cloud computing provides the on-demand service of user with use distributed physical machines, in which security has become a challenging factor while performing various tasks. Several methods were developed for cloud workflow scheduling based on optimal resource allocation; still, consideration and efficient allocation are challenging. Hence, this research introduces hybrid optimization algorithm multi-objective environment. The Regressive Whale Water Tasmanian Devil Optimization (RWWTDO) is proposed fitness function nine factors, like Predicted energy, Quality (QoS), Resource utilization, Actual task running time, Bandwidth Memory capacity, Make span equivalent total cost, Task priority, Trust. Besides, secure data transmission employed using triple encryption standard (3DES) to acquire enhanced scheduling. method’s performance evaluated predicted time acquired values 1.00000, 0.16587, 0.00041, 0.00314, respectively.

Language: Английский

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Evaluation of Secure Methods for Migrating Virtual Machines to the Cloud

Published: Feb. 9, 2024

Cloud services are becoming more popular due to their numerous benefits, such as low cost, dependability, and user-friendliness. Data security protocols have been created in response the increasing demand. It is critical for cloud computing ensure that data can only be accessed by authorized users. To safeguard cloud-based platforms, ML-dependent solutions employed, even though cryptographic procedures still principal means of guaranteeing security. Any information technology infrastructure might benefit significantly from artificial intelligence's capacity assess real-time while providing threat information. When migrating VMs, it crucial keep consideration. Conducting an analysis methods used during VM migration primary goal this work. Beyond that, we covered various ML In addition, certain properties accuracy, security, computational speed, time savings, throughput, so on compare with algorithms inference gathering. Apart comparative based approaches has done metrics like authentication process, delay, throughput CIA triad We could enhance through integrating cryptography procedures.

Language: Английский

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Improving Virtual Machine Migration Effects in Cloud Computing Environments Using Depth First Inspired Opportunity Exploration

International Journal of Cloud Applications and Computing, Journal Year: 2022, Volume and Issue: 12(1), P. 1 - 22

Published: Nov. 17, 2022

The cloud platform has established itself as the de-facto standard in IT outsourcing. This is resulting large-scale migration of infrastructure and development platforms from in-house to service providers. Many recent proposals on have addressed several issues that appeared horizon. VM placement (VMP) been a serious concern when it comes VMs after or reallocation. Most works lacked multiple (MVMP) problem instances. A recently researched idea MVMP through depth first opportunistic exploration (DFOE) proposed this paper. performance compared with existing single benchmark algorithm. Improvement terms number migrations, energy consumption, reallocation reported simulation real-time load scenario. Cloud environments can benefit improve operating margins power saving balancing.

Language: Английский

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