NORA: Network oriented resource allocation for data intensive applications in the cloud environment

Adeniyi Abdul; Rahat Iqbal; Anne James; Michael Odetayo; Nazaraf Shah

doi:10.1109/CSCWD.2014.6846858

NORA: Network oriented resource allocation for data intensive applications in the cloud environment

Adeniyi Abdul, Rahat Iqbal, Anne James, Michael Odetayo, Nazaraf Shah

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

1 Citation (Scopus)

Abstract

Optimization of data intensive applications is affected greatly by the nature of the platform, the distributed file system, the co-location of data and programs, and the proximity of resources. Data intensive applications running on a public cloud have been shown to exhibit degraded performance compared to a private cluster. This performance degradation is as a result of the inefficient resource allocation adopted in a virtualized, volatile and multi-tenancy environment such as a cloud. The placement of virtual machines is critical for improving performance in geo-clouds environment. We address degradation in performance by designing a scheduling algorithm that dynamically distributes virtual machines based on the characteristics of the job, the network characteristics and the real time performance of the data centers. Our algorithm also finds the best node(s) to host virtual machines that will yield maximum resource utilization and minimize bandwidth consumption. Our results show that incorporating these characteristics in a resource scheduling algorithm increases the performance of data intensive application than known traditional scheduling.

Original language	English
Title of host publication	Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014
Publisher	IEEE Computer Society
Pages	295-300
Number of pages	6
ISBN (Electronic)	978-1-4799-3776-9, 978-1-4799-3775-2
ISBN (Print)	978-1-4799-3776-9
DOIs	https://doi.org/10.1109/CSCWD.2014.6846858
Publication status	Published - 8 Jul 2014
Event	IEEE International Conference on Computer Supported Cooperative Work in Design - Hsinchu, Taiwan, Province of China Duration: 21 May 2014 → 23 May 2014 Conference number: 18

Conference

Conference	IEEE International Conference on Computer Supported Cooperative Work in Design
Abbreviated title	CSCWD 2014
Country/Territory	Taiwan, Province of China
City	Hsinchu
Period	21/05/14 → 23/05/14

Keywords

Virtual machining
Scheduling
Processor scheduling
Resource management
Distributed databases
Data models
Cloud computing
virtual machines
data handling
distributed processing
operating systems (computers)
optimisation
resource allocation
data centers
network oriented resource allocation
NORA
data intensive applications
cloud environment
optimization
distributed file system
public cloud
private cluster
geoclouds environment
scheduling algorithm
network characteristics
Hadoop MapReduce
Grid Computing
Distributed Application

ASJC Scopus subject areas

Software

Access to Document

10.1109/CSCWD.2014.6846858

Cite this

Abdul, A., Iqbal, R., James, A., Odetayo, M., & Shah, N. (2014). NORA: Network oriented resource allocation for data intensive applications in the cloud environment. In Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014 (pp. 295-300). Article 6839905 IEEE Computer Society. https://doi.org/10.1109/CSCWD.2014.6846858

NORA: Network oriented resource allocation for data intensive applications in the cloud environment. / Abdul, Adeniyi; Iqbal, Rahat; James, Anne et al.
Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014. IEEE Computer Society, 2014. p. 295-300 6839905.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Abdul, A, Iqbal, R, James, A, Odetayo, M & Shah, N 2014, NORA: Network oriented resource allocation for data intensive applications in the cloud environment. in Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014., 6839905, IEEE Computer Society, pp. 295-300, IEEE International Conference on Computer Supported Cooperative Work in Design, Hsinchu, Taiwan, Province of China, 21/05/14. https://doi.org/10.1109/CSCWD.2014.6846858

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abstract = "Optimization of data intensive applications is affected greatly by the nature of the platform, the distributed file system, the co-location of data and programs, and the proximity of resources. Data intensive applications running on a public cloud have been shown to exhibit degraded performance compared to a private cluster. This performance degradation is as a result of the inefficient resource allocation adopted in a virtualized, volatile and multi-tenancy environment such as a cloud. The placement of virtual machines is critical for improving performance in geo-clouds environment. We address degradation in performance by designing a scheduling algorithm that dynamically distributes virtual machines based on the characteristics of the job, the network characteristics and the real time performance of the data centers. Our algorithm also finds the best node(s) to host virtual machines that will yield maximum resource utilization and minimize bandwidth consumption. Our results show that incorporating these characteristics in a resource scheduling algorithm increases the performance of data intensive application than known traditional scheduling.",

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AB - Optimization of data intensive applications is affected greatly by the nature of the platform, the distributed file system, the co-location of data and programs, and the proximity of resources. Data intensive applications running on a public cloud have been shown to exhibit degraded performance compared to a private cluster. This performance degradation is as a result of the inefficient resource allocation adopted in a virtualized, volatile and multi-tenancy environment such as a cloud. The placement of virtual machines is critical for improving performance in geo-clouds environment. We address degradation in performance by designing a scheduling algorithm that dynamically distributes virtual machines based on the characteristics of the job, the network characteristics and the real time performance of the data centers. Our algorithm also finds the best node(s) to host virtual machines that will yield maximum resource utilization and minimize bandwidth consumption. Our results show that incorporating these characteristics in a resource scheduling algorithm increases the performance of data intensive application than known traditional scheduling.

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KW - Scheduling

KW - Processor scheduling

KW - Resource management

KW - Distributed databases

KW - Data models

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KW - data handling

KW - distributed processing

KW - operating systems (computers)

KW - optimisation

KW - resource allocation

KW - data centers

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KW - optimization

KW - distributed file system

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KW - private cluster

KW - geoclouds environment

KW - scheduling algorithm

KW - network characteristics

KW - Hadoop MapReduce

KW - Grid Computing

KW - Distributed Application

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ER -

NORA: Network oriented resource allocation for data intensive applications in the cloud environment

Abstract

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Keywords

ASJC Scopus subject areas

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