An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing

Han, Guangjie; Que, Wenhui; Jia, Gangyong; Shu, Lei

doi:10.3390/s16020246

Cited by 87 publications

(50 citation statements)

References 19 publications

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“…Most of the previous works [19,28,29] did not consider the disk space as well. Moreover, we only regard these resources as a constraint in this paper and they are not the main discussed contents of this paper.…”

Section: Remarkmentioning

confidence: 99%

“…Han et al [19] consider energy consumption and propose a remaining utilization-aware (RUA) algorithm for virtual machine (VM) placement. Besides a power-aware algorithm (PA) is proposed to find proper hosts to shut down for energy saving.…”

Section: Related Workmentioning

confidence: 99%

“…Remaining utilization-aware (RUA) algorithm [19]: RUA intends to place VMs on less PMs to improve resource utilization. Moreover, RUA could avoid placing VMs that have a large resource requests on the same PMs for reducing resource competition between VMs.…”

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confidence: 99%

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An RTT-Aware Virtual Machine Placement Method

Wang

Ren

2017

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Virtualization is a key technology for mobile cloud computing (MCC) and the virtual machine (VM) is a core component of virtualization. VM provides a relatively independent running environment for different applications. Therefore, the VM placement problem focuses on how to place VMs on optimal physical machines, which ensures efficient use of resources and the quality of service, etc. Most previous work focuses on energy consumption, network traffic between VMs and so on and rarely consider the delay for end users' requests. In contrast, the latency between requests and VMs is considered in this paper for the scenario of optimal VM placement in MCC. In order to minimize average RTT for all requests, the round-trip time (RTT) is first used as the metric for the latency of requests. Based on our proposed RTT metric, an RTT-Aware VM placement algorithm is then proposed to minimize the average RTT. Furthermore, the case in which one of the core switches does not work is considered. A VM rescheduling algorithm is proposed to keep the average RTT lower and reduce the fluctuation of the average RTT. Finally, in the simulation study, our algorithm shows its advantage over existing methods, including random placement, the traffic-aware VM placement algorithm and the remaining utilization-aware algorithm.

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Section: Remarkmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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An RTT-Aware Virtual Machine Placement Method

Wang

Ren

2017

Information

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“…Preserved the QoS requirements Han, G. et al [16] Remaining Utilization-Aware (RUA)algorithm, Power-Aware (PA) algorithm…”

Section: )mentioning

confidence: 99%

Analysis of Cloud Sim Toolkit for Implementing Energy Efficient Green Cloud Data Centers

Sajitha¹

2018

IJRASET

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Cloud computing is an emerging technology which emphasis on delivering software, platform, infrastructure to the user, based on demand by cloud services providers through general internet-based applications. Consumer can pay for using these resources on the basis of pay as you go model. Cloud Computing is facing many challenges from its seedling stage to yet. Energy management, Load balancing, Server consolidation, Resource utilization, VM Migration cost and time modeling, Security and Network throughput achievements are various known issues. Out of this energy consumption awarding the first position because of the number of energy hungry data centres are growing rapidly due to the increasing popularity of the Cloud Computing among all levels of organizations. But running the applications in the real cloud for testing are much more expensive and researchers often cannot attain the real cloud environment. To conquer these challenges, a test bed of cloud simulator is necessary. Simulation is the act of imitating or pretending like real environment. This paper introduces the characteristics and working of a cloud simulator framework named CloudSim which provides simulation, supremacy to manage cloud services as well as modeling of cloud infrastructure. Keywords: Cloud Computing, Data Centre, Energy Efficiency, Cloud Sim, Simulation, Green Cloud. I.INTRODUCTION Cloud computing is a versatile technology which can bear the wide spectrum of resources as well as applications. It is gaining its esteem in the midst of different types of organizations that have the aspirations to eliminate the strain of managing their own IT infrastructure via outsourcing the computational resources. It is a technological framework which supplies computing resources as a utility like electricity on a metered basis that authorizes the operations of the workloads similar to grid computing [1]. It provides high reliability, broad network access, fault tolerance, on demand services etc as compared to traditional computing Cloud provides Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) as service models. Amazon EC2 is an eminent IaaS provider, Google App is a well known PaaS provider and Salesforce.com is a prominent SaaS provider.. Cloud Computing distributes its resources, such as, software, storage, databases and network in reliable, economical and secure manner to a wide number of users via conventional internet protocols and these resources are accumulated in geographically dispersed energy hungry data centers. The conventional cloud applications are social networking, content delivery, web hosting, real time processing of data etc. These kinds of applications have dissimilar requirements for their set up and organization. The system volume, power performance and unreliable loads are the various issues of these applications' deployment under cloud federation. The amount of energy consumption of data centers is doubling in every four years. In 2015, U.S. data centers consumed around...

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“…Kostoska, M, Gusev, M, and Ristov, S (2014) describe a new cloud protability platform (PaaS) as a service which can accept and exchange from one cloud platform to another platform and installed completely automatically. Han, G et al (2016) have proposed an energy-aware VM consolidation based on remaining utilisation-aware algorithm (RUA). Xu (2013) has proposed an interoperable cloud manufacturing system (ICMS) which shares encapsulated resources into a cloud service for manufacturing where manufacturing capabilities and business opportunities are integrated and broadcasted in a larger resource pool.…”

Section: Introductionmentioning

confidence: 99%

Software security requirements management as an emerging cloud computing service

Ramachandran

2016

International Journal of Information Management

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Emerging cloud applications are growing rapidly and the need for identifying and managing service requirements is also highly important and critical at present. Software Engineering and Information Systems has established techniques, methods and technology over two decades to help achieve cloud service requirements, design, development, and testing. However, due to the lack of understanding of software security vulnerabilities that should have been identified and managed during the requirements engineering phase, we have not been so successful in applying software engineering, information management, and requirements management principles that have been established for the past at least 25 years, when developing secure software systems. Therefore, software security cannot just be added after a system has been built and delivered to customers as seen in today's software applications. This paper provides concise methods, techniques, and best practice requirements management guidelines for software security and also discusses an Integrated-Secure SDLC model (IS-SDLC), which will benefit practitioners, researchers, learners, and educators. This paper illustrates our approach for a large cloud system Amazon EC2 service.Keywords: Emerging cloud services, Software Security Engineering, Software security requirements engineering, Secured Software Development, SQUARE method, BSI, Touchpoint, SDL, Requirements Management IntroductionThere is no doubt that the cloud computing has revolutionised human lives, communications, digital economy, socialisation, and entertainment. At the same time demands for internet enabled applications grows rapidly. Almost all businesses, applications, entertainment devices, mobile devices, robots, large scale systems (aircrafts, mission control systems), safety-critical systems, medical systems, internet of things devices are internet enabled for various reasons such as online upgrade, distributed applications, team projects, and server connectivity. Therefore, there is ever growing demand for secured applications and trust. Cyber attacks are increasing continuously From spam, phishing, identify theft, and others in much larger scale attacks such as money laundering and cyber terrorism. There is a real possibility that a cyber attack could disable command systems, bring down power grids, open dam floodgates, paralyses communications and transport systems, creating mass hysteria: Any or all of which could be the precursor to terrorist or military attack. These are some of the threats since we (personal, govt. organisations, companies, and business) mostly depend on computers and mobiles for communications and management. Emerging cloud services are on the increase including eHealth Cloud, E-Learning, E-Manufacturing, etc. Kostoska, M, Gusev, M, and Ristov, S (2014) describe a new cloud protability platform (PaaS) as a service which can accept and exchange from one cloud platform to another platform and installed completely automatically. Han, G et al (2016) have proposed an energy-awar...

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An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing

Cited by 87 publications

References 19 publications

An RTT-Aware Virtual Machine Placement Method

An RTT-Aware Virtual Machine Placement Method

Analysis of Cloud Sim Toolkit for Implementing Energy Efficient Green Cloud Data Centers

Software security requirements management as an emerging cloud computing service

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