Framework for Ranking Service Providers of Federated Cloud Architecture using Fuzzy Sets
Federated Cloud Architecture is a heterogeneous and distributed model that provides infrastructures related to the cloud by aggregating different Infrastructure-as-a-Service (IaaS) providers. In this case, it is an exciting task to select the optimal service cloud provider for the customer and the...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Indonesia
2016-04-01
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| Series: | International Journal of Technology |
| Subjects: | |
| Online Access: | http://ijtech.eng.ui.ac.id/article/view/1679 |
| _version_ | 1797969891818471424 |
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| author | L. Aruna M. Aramudhan |
| author_facet | L. Aruna M. Aramudhan |
| author_sort | L. Aruna |
| collection | DOAJ |
| description | Federated Cloud Architecture is a heterogeneous and distributed model that provides
infrastructures related to the cloud by aggregating different Infrastructure-as-a-Service (IaaS) providers. In this case, it is an exciting task to
select the optimal service cloud provider for the customer and then deploy it. In this paper,
a new provider discovery
algorithm and fuzzy sets ranking model is proposed in the modified federated
architecture and then
the performance is
evaluated. The proposed
discovery method shortlists the provider based on the Quality of Service (QoS)
indicators suggested by the Service Measurement Index (SMI) with the Service Level
Agreement (SLA) that
provides improved performance. In addition to that, the cost is also included that
represents the
fulfillment at the level of the end user. The ranking mechanism is based on a Fuzzy set approach, having three general phases, such as problem decomposition, judgment of
priorities and an aggregation
of these priorities. With some simple rules, the fuzzy set may be combined with the QoS indicators. The Weighted
Tuned Queuing Scheduling (WTOS) Algorithm is proposed to resolve the issue of starvation in the
existing architecture and manage the requests effectively. Experimental results
show that the proposed
architecture has a
better successful selection rate, average response time and less overhead,
compared to the existing architecture that had supported the Cloud environment. |
| first_indexed | 2024-04-11T03:08:20Z |
| format | Article |
| id | doaj.art-6bb50b65deee43098cf0fcf79729f8bc |
| institution | Directory Open Access Journal |
| issn | 2086-9614 2087-2100 |
| language | English |
| last_indexed | 2024-04-11T03:08:20Z |
| publishDate | 2016-04-01 |
| publisher | Universitas Indonesia |
| record_format | Article |
| series | International Journal of Technology |
| spelling | doaj.art-6bb50b65deee43098cf0fcf79729f8bc2023-01-02T12:15:42ZengUniversitas IndonesiaInternational Journal of Technology2086-96142087-21002016-04-017464365310.14716/ijtech.v7i4.16791679Framework for Ranking Service Providers of Federated Cloud Architecture using Fuzzy SetsL. Aruna0M. Aramudhan1Department of Computer Science, School of Mathematics, Periyar University, Salem 636011, Tamil Nadu, IndiaDepartment of Information Technology, Perunthalaivar Kamarajar Institute of Engineering and Technology (PKIET), Karaikal 609603, Puducherry, IndiaFederated Cloud Architecture is a heterogeneous and distributed model that provides infrastructures related to the cloud by aggregating different Infrastructure-as-a-Service (IaaS) providers. In this case, it is an exciting task to select the optimal service cloud provider for the customer and then deploy it. In this paper, a new provider discovery algorithm and fuzzy sets ranking model is proposed in the modified federated architecture and then the performance is evaluated. The proposed discovery method shortlists the provider based on the Quality of Service (QoS) indicators suggested by the Service Measurement Index (SMI) with the Service Level Agreement (SLA) that provides improved performance. In addition to that, the cost is also included that represents the fulfillment at the level of the end user. The ranking mechanism is based on a Fuzzy set approach, having three general phases, such as problem decomposition, judgment of priorities and an aggregation of these priorities. With some simple rules, the fuzzy set may be combined with the QoS indicators. The Weighted Tuned Queuing Scheduling (WTOS) Algorithm is proposed to resolve the issue of starvation in the existing architecture and manage the requests effectively. Experimental results show that the proposed architecture has a better successful selection rate, average response time and less overhead, compared to the existing architecture that had supported the Cloud environment.http://ijtech.eng.ui.ac.id/article/view/1679Cloud ranking, Differentiated scheduling, Federated cloud architecture, Provider discovery |
| spellingShingle | L. Aruna M. Aramudhan Framework for Ranking Service Providers of Federated Cloud Architecture using Fuzzy Sets International Journal of Technology Cloud ranking, Differentiated scheduling, Federated cloud architecture, Provider discovery |
| title | Framework for Ranking Service Providers of Federated Cloud Architecture using Fuzzy Sets |
| title_full | Framework for Ranking Service Providers of Federated Cloud Architecture using Fuzzy Sets |
| title_fullStr | Framework for Ranking Service Providers of Federated Cloud Architecture using Fuzzy Sets |
| title_full_unstemmed | Framework for Ranking Service Providers of Federated Cloud Architecture using Fuzzy Sets |
| title_short | Framework for Ranking Service Providers of Federated Cloud Architecture using Fuzzy Sets |
| title_sort | framework for ranking service providers of federated cloud architecture using fuzzy sets |
| topic | Cloud ranking, Differentiated scheduling, Federated cloud architecture, Provider discovery |
| url | http://ijtech.eng.ui.ac.id/article/view/1679 |
| work_keys_str_mv | AT laruna frameworkforrankingserviceprovidersoffederatedcloudarchitectureusingfuzzysets AT maramudhan frameworkforrankingserviceprovidersoffederatedcloudarchitectureusingfuzzysets |