Towards tenant demand-aware bandwidth allocation strategy in cloud datacenter

Cao, Jiuxin; Ma, Zhuo; Xie, Jue; Zhu, Xiangying; Dong, Fang; Liu, Bo

doi:10.1016/j.future.2017.06.005

Cited by 13 publications

(3 citation statements)

References 15 publications

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“…In recent years, SDN has been employed in CDCs since SDN provides central control of the network. SDN-based Data Center Network (DCN) is preferred to the traditional DCN since it can improve DCN efficiency [22]. Furthermore, hypervisors are used in CDC to enable the deployment of virtual resources, so functions such as traffic control and isolation are crucial for providing efficient services.…”

Section: Characteristics Of Cloud Data Centermentioning

confidence: 99%

A Comparative and Analytical Study for Choosing the Best Suited SDN Network Operating System for Cloud Data Center

Zaher

Molnár

2022

AETiC

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The growing deployment of Software Defined Network (SDN) paradigm in the academic and commercial sectors resulted in many different Network Operating Systems (NOS). As a result, adopting the right NOS requires an analytical study of the available alternatives according to the target use case. This study aims to determine the best NOS according to the requirements of Cloud Data Center (CDC). This paper evaluates the specifications of the most common open-source NOSs. The studied features have been classified into two groups, i.e., non-functional features such as availability, scalability, ease of use, maturity, security and interoperability, and functional features, such as virtualization, fault verification and troubleshooting, packet forwarding techniques and traffic protection solutions. A Decision support system, Analytical Hierarchy Process (AHP) has been applied for assessing specifications of the inspected NOSs, namely, ONOS, Opendaylight (ODL), Floodlight, Ryu, POX and Tungsten. Our investigation revealed that ODL is the most suitable NOS for CDC compared to the rest studied NOSs. However, ODL and ONOS have almost similar scores compared to the rest NOSs.

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Section: Characteristics Of Cloud Data Centermentioning

confidence: 99%

A Comparative and Analytical Study for Choosing the Best Suited SDN Network Operating System for Cloud Data Center

Zaher

Molnár

2022

AETiC

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“…Fahmideh, et al [12] proposes an interactive target reasoning method, which is supported by probability layer, and is used to analyze cloud migration risk accurately to improve the reliability of risk control. Cao, et al [13] proposes an automatic pre-allocation strategy to solve the problem of bandwidth over subscription in CDC. Alsarhan, et al [14] is the rst attempt to promote this integration to improve the pro ts of cloud service providers and avoid SLA violations.…”

Section: Research Based On Optimization E Ciencymentioning

confidence: 99%

Dynamic nearest neighbor resources classification algorithm for multiple cloud data center based on natural clustering rule

Liang

2022

Preprint

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Cloud service providers need to reduce the operating costs and energy consumption of cloud data center (CDC) by optimizing scheduling algorithms, and ultimately reduce the cost of cloud users. However, the existing scheduling algorithms are less effective in dealing with the scheduling problems of multi-cloud data center (MDC). This paper systematically analyzes the MDC model and physical machine (PM) utilization. Secondly, using the idea of K-means clustering algorithm in machine learning, natural clustering rules are proposed to complete automatic clustering of PMs. Then, the supervised learning KNN classification algorithm is extended and the dynamic KNN classification rules are established accordingly. Finally, a dynamic nearest neighbor resources classification algorithm for multiple CDC based on natural clustering rule (DNSC) is proposed. Comparing the algorithm with the comparison algorithm shows that the algorithm comprehensively considers the resource parameters of the MDC and ultimately reduces the energy consumption of the MDC.

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“…In [24], the authors proposed an algorithm for dynamic bandwidth shaping while still maintaining the limitations on network resources. In [25], "Towards a Tenant Demand-aware bandwidth allocation strategy in the cloud data center" is discussed. The authors propose a strategy to handle the issue of over bandwidth subscription cloud datacenter.…”

Section: Related Workmentioning

confidence: 99%

Virtualization in Cloud Environment: Bandwidth Management

Odun-Ayo¹,

Idoko²,

Abayomi-Zannu³

2019

Adv. sci. technol. eng. syst. j.

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Cloud computing recently emerged as an interesting model that enables computing and other related internet activities to take place anywhere, anytime. Cloud service providers centralize all servers, networks, and applications to allow their users' access at any time and from any location. Cloud computing uses already existing resources like server, CPU and storage memory but runs on a new technology known as virtualization. The core idea of virtualization is to create several virtual versions of one single computing device or resource. This enables many user operating systems to work on such a single underlying piece of device. Network bandwidth is one of the critical resources in a cloud environment. Bandwidth management involves the use of techniques, technologies, tools, and policies to help avoid network congestion and ensure optimal use of the subscribed bandwidth resources while also being a bedrock of any subscription-based access network. Bandwidth management is being utilized by organizations to allow them to efficiently utilize their subscribed bandwidth resources. Bandwidth management deals with the measurement and control of packets or traffic on a network link in order to refrain from overburdening or overloading the link which can lead to poor performance and network congestion. In this paper, the highest development with respect to virtualization in cloud computing is presented. This study review papers available on cloud computing and relevant published literature in multiple areas like conferences, journals etc. This paper examined present mechanisms that enable cloud service providers to distribute bandwidth more effectively. This paper is therefore a study of virtualization in cloud computing, and the identification of bandwidth management mechanisms in the cloud environment. This will benefit forthcoming cloud providers and even cloud users..

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Towards tenant demand-aware bandwidth allocation strategy in cloud datacenter

Cited by 13 publications

References 15 publications

A Comparative and Analytical Study for Choosing the Best Suited SDN Network Operating System for Cloud Data Center

A Comparative and Analytical Study for Choosing the Best Suited SDN Network Operating System for Cloud Data Center

Dynamic nearest neighbor resources classification algorithm for multiple cloud data center based on natural clustering rule

Virtualization in Cloud Environment: Bandwidth Management

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