Synergies between resource sustainability and energy performance of cloud servers: The role of virtual machine repacking approach

Computers & Electrical Engineering, Journal Year: 2023, Volume and Issue: 106, P. 108568 - 108568

Published: Jan. 6, 2023

Language: Английский

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An Integrated Technique for Securing Large Virtual Machine Migration

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 31, 2024

Maintaining data confidentiality and integrity during the large VM migration is quite challenging. Simultaneously, use of complex encryption or steganography for managing them increases time overheads. These may cause loss. The transportation VMs further consumes significant bandwidth causes page faults. However, these issues aren't dealt with in modern literature, despite many research attempts. Moreover, unlawful intrusions various transmission errors make matters worse. Hence, this work proposes an efficient technique that addresses such outstanding a unified way. suggested solution has special compression method reduces big sizes to 53.9%, new enhance integrity, smart split stop faults as well lower loss 0.0009%. results show it cuts down on downtime by 10% more than existing methods. obtained justify its efficiencies over other ones distinct dimensions.

Language: Английский

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COMPARISON AND EVALUATION OF ENERGY-EFFICIENT CLOUD COMPUTING TECHNIQUES WITH LOAD BALANCING APPROACHES

ASEAN Engineering Journal, Journal Year: 2024, Volume and Issue: 14(2), P. 121 - 133

Published: May 31, 2024

The advent of Cloud Computing has revolutionized the IT landscape by offering computing resources as a service, similar to conventional utilities like electricity. This paradigm shift made cloud cornerstone contemporary digital economy, attracting substantial focus from both academic and industrial sectors. Its unique pay-as-you-go model provides customers with on-demand resource availability, enhancing operational flexibility. However, this convenience is offset growing energy demands data centers, which not only escalate expenses but also contribute environmental degradation through increased carbon footprints. To combat these issues, Green been introduced, striving for energy-efficient sustainable operations. involves employing strategies that minimize consumption utilization application energy-conscious algorithms. Although numerous algorithms based on server consolidation have proposed optimize use in environments, they often lack uniform evaluative comparisons vary performance due differing experimental conditions. variance presents challenge selecting most effective algorithm tailored specific needs. study aims provide nuanced analysis existing algorithms, assisting researchers identifying best suits their requirements. We undertake an exhaustive comparison various examining architecture, modelling approaches, metrics. These are then implemented tested under conditions using CloudSim toolkit. Our findings offer in-depth comparative shedding light respective advantages shortcomings. Additionally, we delve into thorough discussion each algorithm's features implications environments.

Language: Английский

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Optimizing pre-copy live virtual machine migration in cloud computing using machine learning-based prediction model

Computing, Journal Year: 2024, Volume and Issue: 106(9), P. 3031 - 3062

Published: July 8, 2024

Abstract One of the preconditions for efficient cloud computing services is continuous availability to clients. However, there are various reasons temporary service unavailability due routine maintenance, load balancing, cyber-attacks, power management, fault tolerance, emergency incident response, and resource usage. Live Virtual Machine Migration (LVM) an option address by moving virtual machines between hosts without disrupting running services. Pre-copy memory migration a common LVM approach used in systems, but it faces challenges high rate frequently updated pages known as dirty pages. Transferring these during pre-copy prolongs overall time. If large numbers remaining after predefined iteration page transfer, stop-and-copy phase initiated, which significantly increases downtime negatively impacts availability. To mitigate this issue, we introduce prediction-based that optimizes process dynamically halting when predicted falls below threshold. Our proposed machine learning method was rigorously evaluated through experiments conducted on dedicated testbed using KVM/QEMU technology, involving different VM sizes memory-intensive workloads. A comparative analysis against methods default reveals remarkable improvement, with average 64.91% reduction RAM configurations high-write-intensive workloads, along total time approximately 85.81%. These findings underscore practical advantages our reducing disruptions live systems.

Language: Английский

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Multi-objective optimization of virtual machine migration among cloud data centers

Soft Computing, Journal Year: 2024, Volume and Issue: 28(20), P. 12043 - 12060

Published: July 24, 2024

Abstract Workload migration among cloud data centers is currently an evolving task that requires substantial advancements. The incorporation of fuzzy systems holds potential for enhancing performance and efficiency within computing. This study addresses a multi-objective problem wherein the goal to maximize interpretability percentage renewable energy consumed by meta-scheduler system in scenarios. To accomplish this objective, present research proposes novel approach utilizing Knowledge Acquisition with Swarm Intelligence Approach algorithm. Additionally, it takes advantage framework built on CloudSim, which includes virtual machine capabilities based expert system. Furthermore, hierarchical employed assess rule base interpretability, along another algorithm, named Non-dominated Sorting Genetic Algorithm II. are perform various simulation results concerning while algorithms aim enhance system’s interpretability. Empirical demonstrate possible improve improving corresponding rule-based proposed algorithm shows comparable or superior genetic across diverse indicate improvements center can be achieved average improvement index ranges from 0.6 6%, increase utilization ranging 5 6%.

Language: Английский

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vDefender: An explainable and introspection-based approach for identifying emerging malware behaviour at hypervisor-layer in virtualization environment

Computers & Electrical Engineering, Journal Year: 2024, Volume and Issue: 120, P. 109742 - 109742

Published: Oct. 18, 2024

Language: Английский

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Democratizing Container Live Migration for Enhanced Future Networks - A Survey

ACM Computing Surveys, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 14, 2024

Emerging cloud-centric networks span from edge clouds to large-scale datacenters with shared infrastructure among multiple tenants and applications high availability, isolation, fault tolerance, security, energy efficiency demands. Live migration (LiMi) plays an increasingly critical role in these environments by enabling seamless application mobility covering the edge-to-cloud continuum maintaining requirements. This survey presents a comprehensive of recent advancements that democratize LiMi, making it more applicable broader range scenarios network both for virtual machines (VMs) containers, analyzes LiMi’s technical underpinnings optimization techniques. It also delves into issue connections handover, presenting taxonomy categorize methods traffic redirection synthesized existing literature. Finally, identifies challenges paves way future research directions this key technology.

Language: Английский

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An optimal solution to reduce virtual machine migration SLA using host power

Measurement Sensors, Journal Year: 2022, Volume and Issue: 25, P. 100628 - 100628

Published: Dec. 27, 2022

The growing demand for cloud services from users, organizations are planning to build more and data centers meet the demand. This is expected increase energy consumption, which in turn will lead an operating costs CO2 emissions. Virtual machine live migration technology can be used reduce amount of consumed by virtual machines. By doing so, machines migrated one server another therefore cause a delay delivering users. Service Level Agreement (SLA) violation important parameters considered better utilization services. applying proposed algorithm, SLA violations reduced through process selecting host Machine according remaining power host, thus SLAs enforced long run. algorithm has been implemented CloudSim. In comparison results achieved with existing algorithms it found that capable reducing 13.6% when compared algorithms.

Language: Английский

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Amended Hybrid Scheduling for Cloud Computing with Real-Time Reliability Forecasting

International Journal of Computer Networks And Applications, Journal Year: 2023, Volume and Issue: 10(3), P. 310 - 310

Published: June 30, 2023

Cloud computing has emerged as the feasible paradigm to satisfy requirements of highperformance applications by an ideal distribution tasks resources.But, it is problematic when attaining multiple scheduling objectives such throughput, makespan, and resource use.To resolve this problem, many Task Scheduling Algorithms (TSAs) are recently developed using single or multiobjective metaheuristic strategies.Amongst, TS based on a Multi-objective Grey Wolf Optimizer (TSMGWO) handles discover assign resources tasks.However, only maximizes use throughput reducing whereas also crucial optimize other parameters like utilization memory, bandwidth.Hence, article proposes hybrid TSA depending linear matching method backfilling, which uses memory bandwidth for effective TS.Initially, Long Short-Term Memory (LSTM) network adopted meta-learner predict task runtime reliability.Then, divided into predictable unpredictable queues.The with higher expected scheduled plan-based approach Tuna Swarm Optimization (TSO).The remaining backfilled VIKOR technique.To reduce use, particular fraction CPU cores kept modified dynamically Resource Use Ratio (RUR) among freshly submitted tasks.Finally, general simulation reveals that proposed algorithm outperforms earlier metaheuristic, plan-based, backfilling TSAs.

Language: Английский

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Security Context Migration in MEC: Challenges and Use Cases

Electronics, Journal Year: 2022, Volume and Issue: 11(21), P. 3512 - 3512

Published: Oct. 28, 2022

Modern and future services require ultra-reliable mobile connections with high bandwidth parameters proper security protection. It is possible to ensure such conditions by provisioning in the Multi-Access Edge Computing system integrated fifth-generation networks. However, main challenge mentioned architecture providing a secure service migration all related data requirements another edge computing host area when user changes its physical location. This article aims present state of research on context between instances Edge/MEC servers, specify steps procedure, identify new challenges inspired use cases 5G vertical industries. For this purpose, analysis context’s structure basic concept Security Service Level Agreement was performed presented document. Next, further investigation conducted, including for reliable serves instances. The study mainly focused crucial solutions resolve them. Finally, authors how proposed solution can be used protect industries based several cases.

Language: Английский

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