Design and test bed experiments of server operation system using virtualization technology

IntroductionCloud computing is being used for innumerable applications these days. The end-users vary from naive clients to expertised technicians. Cloud is a pool of resources shared among number of users [1]. Presently, in the world of cloud computing, it is the era of XaaS (Anything-as-a-Service) which means that the providers offer a wide variety of services [2,3]. One of the most recent services provided through the cloud is high performance computing (HPC) environments for the complex applications. Virtualization is the technology which enables users to share a single entity among a group of users. AbstractCloud computing is the driving power behind the current technological era. Virtualization is rightly referred to as the backbone of cloud computing. Impacts of virtualization employed in high performance computing (HPC) has been much reviewed by researchers. The overhead in the virtualization layer was one of the reasons which hindered its application in the HPC environment. Recent developments in virtualization, especially the OS container based virtualization provides a solution that employs a lightweight virtualization layer and promises lesser overhead. Containers are advantageous over virtual machines in terms of performance overhead which is a major concern in the case of both data intensive applications and compute intensive applications. Currently, several industries have adopted container technologies such as Docker. While Docker is widely used, it has certain pitfalls such as security issues. The recently introduced CoreOS Rkt container technology overcomes these shortcomings of Docker. There has not been much research on how the Rkt environment is suited for high performance applications. The differences in the stack of the Rkt containers suggest better support for high performance applications. High performance applications consist of CPU-intensive and data-intensive applications. The High Performance Linpack Library and the Graph500 are the commonly used computation intensive and data-intensive benchmark applications respectively. In this work, we explore the feasibility of this inter-operable Rkt container in high performance applications by running the HPL and Graph500 applications and compare its performance with the commonly used container technologies such as LXC and Docker containers. Martin et al. Hum. Cent. Comput. Inf. Sci. (2018) Hum. Cent. Comput. Inf. Sci. (2018) 8:1 Based on the position of the virtualization layer, virtualization can be of different types like full virtualization, paravirtualization and OS level virtualization. RESEARCHTraditional HPC clusters are composed of many separate dedicated servers called nodes and may be shared among different organizations. The requirements of each user or organization will be different, which demands the creation of customized environments without affecting others. This is not an easy task in traditional HPC systems. As a solution for this, virtualization was adopted for HPC. Virtualization materializes the task by creating s...

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“…There exists different kinds of virtualization techniques [4]. One of the popular techniques involves a Hypervisor (Virtual Machine Manager).…”

Section: Researchmentioning

confidence: 99%

Exploring the support for high performance applications in the container runtime environment

Martin

Kandasamy

Chandrasekaran

2018

Hum. Cent. Comput. Inf. Sci.

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“…Since cloud computing environments adapt virtualization technology [20], scalability should be considered enabling large-scale distribution [21]. Table 2 shows the experimental settings.…”

Section: Performance Evaluationmentioning

confidence: 99%

A slave ants based ant colony optimization algorithm for task scheduling in cloud computing environments

Moon

Gil

et al. 2017

Hum. Cent. Comput. Inf. Sci.

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Since cloud computing provides computing resources on a pay per use basis, a task scheduling algorithm directly affects the cost for users. In this paper, we propose a novel cloud task scheduling algorithm based on ant colony optimization that allocates tasks of cloud users to virtual machines in cloud computing environments in an efficient manner. To enhance the performance of the task scheduler in cloud computing environments with ant colony optimization, we adapt diversification and reinforcement strategies with slave ants. The proposed algorithm solves the global optimization problem with slave ants by avoiding long paths whose pheromones are wrongly accumulated by leading ants.

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“…Shodan has an update interval of 1 month as it collects port information more than Censys, and Censys updates its major port information in 2 weeks. Censys, on the other hand, can check the "alive" condition of devices in 1:09:45 s when scanning devices in all IPv4 address bands, about 4.3 billion using a single probe (Huh and Seo 2016).…”

Section: Scan Technology For Internet Devicesmentioning

confidence: 99%

Management platform of threats information in IoT environment

Kim

2017

J Ambient Intell Human Comput

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Design and test bed experiments of server operation system using virtualization technology

Cited by 51 publications

References 18 publications

Exploring the support for high performance applications in the container runtime environment

Exploring the support for high performance applications in the container runtime environment

A slave ants based ant colony optimization algorithm for task scheduling in cloud computing environments

Management platform of threats information in IoT environment

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