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Performance Comparison of Hyper-V and KVM for Cryptographic Tasks in cloud computing

Computers, Materials & Continua 2024年第2期78卷 2023-2045页

作者： Nader Abdel Karim Osama A.Khashan Waleed K.Abdulraheem Moutaz Alazab Hasan Kanaker Mahmoud E.Farfoura Mohammad Alshinwan Department of Intelligent Systems Faculty of Artificial IntelligenceAl-Balqa Applied UniversityAl-Salt1705Jordan Research and Innovation Centers Rabdan AcademyP.O.Box 114646Abu DhabiUnited Arab Emirates Department of Information Systems and Networks TheWorld Islamic Sciences and Education UniversityAmman11947Jordan Department of Cyber Security Isra UniversityAmman1162Jordan Faculty of Science and Information Technology Al-Zaytoonah University of JordanAmman11733Jordan Middle East University Research Unit Middle East UniversityAmman11831Jordan

As the extensive use of cloud computing raises questions about the security of any personal data stored there,cryptography is being used more frequently as a security tool to protect data confidentiality and privacy in the cloud environment.A hypervisor is a virtualization software used in cloud hosting to divide and allocate resources on various pieces of *** choice of hypervisor can significantly impact the performance of cryptographic operations in the cloud *** important issue that must be carefully examined is that no hypervisor is completely superior in terms of performance;Each hypervisor should be examined to meet specific *** main objective of this study is to provide accurate results to compare the performance of Hyper-V and Kernel-based Virtual Machine(KVM)while implementing different cryptographic algorithms to guide cloud service providers and end users in choosing the most suitable hypervisor for their cryptographic *** study evaluated the efficiency of two hypervisors,Hyper-V and KVM,in implementing six cryptographic algorithms:Rivest,Shamir,Adleman(RSA),Advanced Encryption Standard(AES),Triple Data Encryption Standard(TripleDES),Carlisle Adams and Stafford Tavares(CAST-128),BLOWFISH,and *** study’s findings show that KVM outperforms Hyper-V,with 12.2%less Central Processing Unit(CPU)use and 12.95%less time overall for encryption and decryption operations with various file *** study’s findings emphasize how crucial it is to pick a hypervisor that is appropriate for cryptographic needs in a cloud environment,which could assist both cloud service providers and end *** research may focus more on how various hypervisors perform while handling cryptographic workloads.

关键词： cloud computing performance virtualization hypervisors Hyper-V KVM cryptographic algorithm

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Hybrid Hierarchical Particle Swarm Optimization with Evolutionary Artificial Bee Colony Algorithm for Task Scheduling in cloud computing

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Computers, Materials & Continua 2024年第1期78卷 1135-1156页

作者： Shasha Zhao Huanwen Yan Qifeng Lin Xiangnan Feng He Chen Dengyin Zhang College of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing210003China Jiangsu Key Laboratory of Broadband Wireless Communication and Internet of Things Nanjing University of Posts and TelecommunicationsNanjing210003China Tongding Interconnection Information Co. Ltd.Suzhou215000China

Task scheduling plays a key role in effectively managing and allocating computing resources to meet various computing tasks in a cloud computing *** execution time and low load imbalance may be the challenges for some algorithms in resource scheduling *** this work,the Hierarchical Particle Swarm Optimization-Evolutionary Artificial Bee Colony Algorithm(HPSO-EABC)has been proposed,which hybrids our presented Evolutionary Artificial Bee Colony(EABC),and Hierarchical Particle Swarm Optimization(HPSO)*** HPSO-EABC algorithm incorporates both the advantages of the HPSO and the EABC *** testing including evaluations of algorithm convergence speed,resource execution time,load balancing,and operational costs has been *** results indicate that the EABC algorithm exhibits greater parallelism compared to the Artificial Bee Colony *** with the Particle Swarm Optimization algorithm,the HPSO algorithmnot only improves the global search capability but also effectively mitigates getting stuck in local *** a result,the hybrid HPSO-EABC algorithm demonstrates significant improvements in terms of stability and convergence ***,it exhibits enhanced resource scheduling performance in both homogeneous and heterogeneous environments,effectively reducing execution time and cost,which also is verified by the ablation experimental.

关键词： cloud computing distributed processing evolutionary artificial bee colony algorithm hierarchical particle swarm optimization load balancing

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MCWOA Scheduler:Modified Chimp-Whale Optimization Algorithm for Task Scheduling in cloud computing

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Computers, Materials & Continua 2024年第2期78卷 2593-2616页

作者： Chirag Chandrashekar Pradeep Krishnadoss Vijayakumar Kedalu Poornachary Balasundaram Ananthakrishnan School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Center for Cyber Physical Systems School of Computer Science and EngineeringVellore Institute of TechnologyChennai600127India

cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as *** has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud ***,efficient task scheduling can lower the cloud infrastructure’s energy consumption,thus maximizing the service provider’s revenue by decreasing user job processing *** proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),combines elements of the Chimp Optimization Algorithm(COA)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution ***,the traditional MCWOA’s local search capabilities are augmented by incorporating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating *** study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam *** outcomes reveal that the new method outperforms the original MCWOA,especially in multi-damage detection *** excels in avoiding false positives and enhancing computational speed,making it an optimal choice for structural damage *** efficiency of the proposed MCWOA is assessed against metrics such as energy usage,computational expense,task duration,and *** simulated data indicates that the new MCWOA outpaces other methods across all *** study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).

关键词： cloud computing scheduling chimp optimization algorithm whale optimization algorithm

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Hybrid Prairie Dog and Beluga Whale Optimization Algorithm for Multi-Objective Load Balanced-Task Scheduling in cloud computing Environments

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China Communications 2024年第7期21卷 307-324页

作者： K Ramya Senthilselvi Ayothi Department of Computer Science and Engineering SRM Institute of Science and TechnologyRamapuramChennaiTamil Nadu 600089India

The cloud computing technology is utilized for achieving resource utilization of remotebased virtual computer to facilitate the consumers with rapid and accurate massive data *** utilizes on-demand resource provisioning,but the necessitated constraints of rapid turnaround time,minimal execution cost,high rate of resource utilization and limited makespan transforms the Load Balancing(LB)process-based Task Scheduling(TS)problem into an NP-hard optimization *** this paper,Hybrid Prairie Dog and Beluga Whale Optimization Algorithm(HPDBWOA)is propounded for precise mapping of tasks to virtual machines with the due objective of addressing the dynamic nature of cloud *** capability of HPDBWOA helps in decreasing the SLA violations and Makespan with optimal resource *** is modelled as a scheduling strategy which utilizes the merits of PDOA and BWOA for attaining reactive decisions making with respect to the process of assigning the tasks to virtual resources by considering their priorities into *** addresses the problem of pre-convergence with wellbalanced exploration and exploitation to attain necessitated Quality of Service(QoS)for minimizing the waiting time incurred during TS *** further balanced exploration and exploitation rates for reducing the makespan during the task allocation with complete awareness of VM *** results of the proposed HPDBWOA confirmed minimized energy utilization of 32.18% and reduced cost of 28.94% better than approaches used for *** statistical investigation of the proposed HPDBWOA conducted using ANOVA confirmed its efficacy over the benchmarked systems in terms of throughput,system,and response time.

关键词： Beluga Whale Optimization Algorithm(BWOA) cloud computing Improved Hopcroft-Karp algorithm Infrastructure as a Service(IaaS) Prairie Dog Optimization Algorithm(PDOA) Virtual Machine(VM)

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Hybrid Approach for Cost Efficient Application Placement in Fog-cloud computing Environments

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Computers, Materials & Continua 2024年第6期79卷 4127-4148页

作者： Abdulelah Alwabel Chinmaya Kumar Swain Department of Computer Sciences College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Science and Engineering Institute of Management and Information TechnologyCuttackBPUTOdishaIndia

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data ***,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud *** approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing *** approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of *** this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing *** consider four cost-types for application deployment:Computation,communication,energy consumption,and *** proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the *** extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art *** results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.

关键词： Placement mechanism application module placement fog computing cloud computing genetic algorithm flamingo search algorithm

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Systematic Review:Load Balancing in cloud computing by Using Metaheuristic Based Dynamic Algorithms

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Intelligent Automation & Soft computing 2024年第3期39卷 437-476页

作者： Darakhshan Syed Ghulam Muhammad Safdar Rizvi Department of Computer Science Bahria UniversityKarachi CampusKarachiPakistan

cloud computing has the ability to provide on-demand access to a shared resource *** has completely changed the way businesses are managed,implement applications,and provide *** rise in popularity has led to a significant increase in the user demand for ***,in cloud environments efficient load balancing is essential to ensure optimal performance and resource *** systematic review targets a detailed description of load balancing techniques including static and dynamic load balancing ***,metaheuristic-based dynamic load balancing algorithms are identified as the optimal solution in case of increased *** a cloud-based context,this paper describes load balancing measurements,including the benefits and drawbacks associated with the selected load balancing *** also summarizes the algorithms based on implementation,time complexity,adaptability,associated issue(s),and targeted QoS ***,the analysis evaluates the tools and instruments utilized in each investigated ***,comparative analysis among static,traditional dynamic and metaheuristic algorithms based on response time by using the cloudSim simulation tool is also ***,the key open problems and potential directions for the state-of-the-art metaheuristic-based approaches are also addressed.

关键词： cloud computing load balancing metaheuristic algorithm dynamic algorithm load balancer QoS

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A Study on Technology Application and Performance of Small and Medium-sized Enterprises in the Context of cloud computing Application-A Case Study of Hotel Industry in Henan,China

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Journal of Sustainable Business and Economics 2024年第2期7卷 69-75页

作者： Zhang Hui Alireza Mohammadi Faculty Of Creative Industries City University MalaysiaMalaysia City Graduate School City University MalaysiaMalaysia

This paper examines how the adoption of cloud computing affects the relationship between the technical and environmental capabilities of small and medium-sized enterprises(SMEs)in the tourism industry in Henan Province,China,thereby promoting the stable and sustainable development of the tourism industry,combining the laws of tourism market development,vigorously constructing a smart tourism project,guiding tourism cloud service providers to strengthen the cooperation and contact with the market’s tourism enterprises,introducing and utilizing cloud computing technology,optimizing and improving the functions of various tourism services of the enterprises,and enhancing the processing and analysis of enterprise-related data to provide tourism *** the processing and analysis of enterprise-related data to provide tourism information,and further study the adoption of cloud computing and its impact on small and medium-sized enterprises(SMEs)in terms of technology and business environment knowledge,so as to make the best enterprise management decisions and realize the overall enhancement of the enterprise’s tourism brand value.

关键词： SMEs cloud computing Technology Adoption Performance Henan Hotels

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Enhancing Cybersecurity through cloud computing Solutions in the United States

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Intelligent Information Management 2024年第4期16卷 176-193页

作者： Omolola F. Hassan Folorunsho O. Fatai Oluwadare Aderibigbe Abdullah Oladoyin Akinde Tolulope Onasanya Mariam Adetoun Sanusi Oduwunmi Odukoya Department of Computer Science Austin Peay State University Clarksville USA Department of Computer Science North Carolina Agricultural and Technical State University Greensboro USA Department of Cybersecurity University of Texas Dallas USA Department of Information Systems East Tennessee State University Johnson City USA

This study investigates how cybersecurity can be enhanced through cloud computing solutions in the United States. The motive for this study is due to the rampant loss of data, breaches, and unauthorized access of internet criminals in the United States. The study adopted a survey research design, collecting data from 890 cloud professionals with relevant knowledge of cybersecurity and cloud computing. A machine learning approach was adopted, specifically a random forest classifier, an ensemble, and a decision tree model. Out of the features in the data, ten important features were selected using random forest feature importance, which helps to achieve the objective of the study. The study’s purpose is to enable organizations to develop suitable techniques to prevent cybercrime using random forest predictions as they relate to cloud services in the United States. The effectiveness of the models used is evaluated by utilizing validation matrices that include recall values, accuracy, and precision, in addition to F1 scores and confusion matrices. Based on evaluation scores (accuracy, precision, recall, and F1 scores) of 81.9%, 82.6%, and 82.1%, the results demonstrated the effectiveness of the random forest model. It showed the importance of machine learning algorithms in preventing cybercrime and boosting security in the cloud environment. It recommends that other machine learning models be adopted to see how to improve cybersecurity through cloud computing.

关键词： Cybersecurity cloud computing cloud Solutions Machine Learning Algorithm

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QoS-Constrained,Reliable and Energy-Efficient Task Deployment in cloud computing

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计算机科学与技术汇刊（中英文版） 2024年第1期11卷 22-31页

作者： Zhenghui Zhang Yuqi Fan School of Computer Science and Information Engineering Hefei University of TechnologyHefeiAnhui230000China

Reliability,QoS and energy consumption are three important concerns of cloud service *** of the current research on reliable task deployment in cloud computing focuses on only one or two of the three ***,these three factors have intrinsic trade-off *** existing studies show that load concentration can reduce the number of servers and hence save *** this paper,we deal with the problem of reliable task deployment in data centers,with the goal of minimizing the number of servers used in cloud data centers under the constraint that the job execution deadline can be met upon single server *** propose a QoS-Constrained,Reliable and Energy-efficient task replica deployment(QSRE)algorithm for the problem by combining task replication and *** each task in a job that cannot finish executing by re-execution within deadline,we initiate two replicas for the task:main task and task *** main task runs on an individual *** associated task replica is deployed on a backup server and completes part of the whole task load before the main task *** from the main tasks,multiple task replicas can be allocated to the same backup server to reduce the energy consumption of cloud data centers by minimizing the number of servers required for running the task ***,QSRE assigns the task replicas with the longest and the shortest execution time to the backup servers in turn,such that the task replicas can meet the QoS-specified job execution deadline under the main task *** conduct experiments through *** experimental results show that QSRE can effectively reduce the number of servers used,while ensuring the reliability and QoS of job execution.

关键词： cloud computing Task Deployment Reliability Quality of Service Energy Consumption

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Secure and Efficient Outsourced Computation in cloud computing Environments

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Journal of Software Engineering and Applications 2024年第9期17卷 750-762页

作者： Varun Dixit Davinderjit Kaur Omnissa LLC Palo Alto CA USA MedROAD Lab University of Alberta Edmonton Canada

Secure and efficient outsourced computation in cloud computing environments is crucial for ensuring data confidentiality, integrity, and resource optimization. In this research, we propose novel algorithms and methodologies to address these challenges. Through a series of experiments, we evaluate the performance, security, and efficiency of the proposed algorithms in real-world cloud environments. Our results demonstrate the effectiveness of homomorphic encryption-based secure computation, secure multiparty computation, and trusted execution environment-based approaches in mitigating security threats while ensuring efficient resource utilization. Specifically, our homomorphic encryption-based algorithm exhibits encryption times ranging from 20 to 1000 milliseconds and decryption times ranging from 25 to 1250 milliseconds for payload sizes varying from 100 KB to 5000 KB. Furthermore, our comparative analysis against state-of-the-art solutions reveals the strengths of our proposed algorithms in terms of security guarantees, encryption overhead, and communication latency.

关键词： Secure Computation cloud computing Homomorphic Encryption Secure Multiparty Computation Resource Optimization

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