Dynamic resource management in Cloud datacenters for Server consolidation

Ngenzi, Alexander; Selvarani, R; Nair, Suchithra R.

doi:10.48550/arxiv.1505.00577

Cited by 2 publications

(2 citation statements)

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“…Here, we considered different resource management techniques based on parameters like monetary parameters (service cost), application performance parameters (response time, execution time, delay, SLA violation, task type, number of processors needed to run tasks, throughput, resource availability, resource utlization, etc), security, and energy-efficiency parameters (overall power, energy consumption) [25]. The algorithms such as load balancing, Round Robin, Bin packing algorithm and gradient search algorithm were mentioned as the optimization methods to improve the performance, reduce the cost, and minimize the energy consumption in IaaS resources [26][27][28][29]. The research in [30] considered a stochastic model based on load balancing and scheduling in cloud computing clusters [31,32].…”

Section: Resource Management Techniquesmentioning

confidence: 99%

A Literature Survey on Resource Management Techniques, Issues and Challenges in Cloud Computing

Nzanywayingoma

Yang

2017

TELKOMNIKA

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Cloud computing is a large scale distributed computing which provides on demand services for clients. Cloud Clients use web browsers, mobile apps, thin clients, or terminal emulators to request and control their cloud resources at any time and anywhere through the network. As many companies are shifting their data to cloud and as many people are being aware of the advantages of storing data to cloud, there is increasing number of cloud computing infrastructure and large amount of data which lead to the complexity management for cloud providers. We surveyed the state-of-the-art resource management techniques for IaaS (infrastructure as a service) in cloud computing. Then we put forward different major issues in the deployment of the cloud infrastructure in order to avoid poor service delivery in cloud computing.

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Section: Resource Management Techniquesmentioning

confidence: 99%

A Literature Survey on Resource Management Techniques, Issues and Challenges in Cloud Computing

Nzanywayingoma

Yang

2017

TELKOMNIKA

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“…In addition, previous studies lack an analysis of the resource usage such as the CPU in each runtime when performing file I/O processing. In edge computing, it is important to utilize computing resources efficiently [22,23] so that the resource usage analysis is essential for the container runtimes to properly provision computing resources. For a better understanding of the secure runtimes, the goal of this paper is to present a comprehensive and detailed analysis on the file I/O processing and CPU usage of the runtimes and find out how their architectures impact the file I/O performance (explained in Section 5).…”

Section: Introductionmentioning

confidence: 99%

Impact of Secure Container Runtimes on File I/O Performance in Edge Computing

Lee,

Kim,

Kwon

et al. 2023

Applied Sciences

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Containers enable high performance and easy deployment due to their lightweight architecture, thus facilitating resource utilization in edge computing nodes. Secure container runtimes have attracted significant attention because of the necessity for overcoming the security vulnerabilities of containers. As the runtimes adopt an additional layer such as virtual machines and user-space kernels to enforce isolation, the container performance can be degraded. Even though previous studies presented experimental results on performance evaluations of secure container runtimes, they lack a detailed analysis of the root causes that affect the performance of the runtimes. This paper explores the architecture of three secure container runtimes in detail: Kata containers, gVisor, and Firecracker. We focus on file I/O, which is one of the key aspects of container performance. In addition, we present the results of the user- and kernel-level profiling and reveal the major factors that impact the file I/O performance of the runtimes. As a result, we observe three key findings: (1) Firecracker shows the highest file I/O performance as it allows for utilizing the page cache inside VMs, and (2) Kata containers offer the lowest file I/O performance by consuming the largest amount of CPU resources. Also, we observe that gVisor scales well as the block size increases because the file I/O requests are mainly handled by the host OS similar to native applications.

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Dynamic resource management in Cloud datacenters for Server consolidation

Cited by 2 publications

References 0 publications

A Literature Survey on Resource Management Techniques, Issues and Challenges in Cloud Computing

A Literature Survey on Resource Management Techniques, Issues and Challenges in Cloud Computing

Impact of Secure Container Runtimes on File I/O Performance in Edge Computing

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