Modelling, Simulation and Design - Publications

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Browsing Modelling, Simulation and Design - Publications by Author "Anjana, Parwat Singh"
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    Cloud service provider evaluation system using fuzzy rough set technique
    ( 2019-05-03) Anjana, Parwat Singh ; Badiwal, Priyanka ; Wankar, Rajeev ; Kallakuri, Swaroop ; Rao, C. Raghavendra
    Cloud Service Provider (CSP) offers a wide variety of scalable, flexible, and cost-efficient services to users on demand and pay-per-utilization basis. However, vast diversity in available services leads to various challenges for a user to determine and select the best suitable service. Further, sometime user needs to hire required services from multiple service providers which leads to account, security, support, interface, and Service Level Agreements (SLAs) associated management difficulties. To avoid such problems having a Cloud Service Broker (CSB) which is aware of service offerings and user's Quality of Service (QoS) requirements will benefit both the service providers and users. We have proposed a cloud service brokerage architecture using fuzzy rough set technique, which facilitates ranking and selecting services, based on users QoS requirements and finally monitor the service execution. We have used fuzzy rough set technique for dimension reduction and weighted Euclidean distance to rank the service providers. To prioritize user QoS request, we suggest to use user assign weights. We also incorporate system assigned weights to give the relative importance to QoS attributes. We compared the proposed ranking technique with an existing technique based on the system response time. With the help of a case study, we have demonstrated the efficiency of the proposed technique. The case study experiment results show that the proposed approach is scalable, resilience, and produce better results with less searching time.
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    Design of a cloud brokerage architecture using fuzzy rough set technique
    ( 2017-01-01) Anjana, Parwat Singh ; Wankar, Rajeev ; Rao, C. Raghavendra
    Cloud computing offers numerous services to the cloud consumers such as infrastructure, platform, software, etc. Due to the vast diversity in available cloud services from the user point of view, it leads to several challenges to rank and select the potential cloud service. One of the plausible solutions for the problem can be obtained with the use of Rough Set Theory (RST) and available in the literature. Unfortunately, Rough Set Theory cannot deal with numerical values. One of the classical solutions to this problem can be obtained by using Fuzzy Rough Set. To the best of our knowledge, there is no working Fuzzy-Rough Set based brokerage architecture available which is used for minimizing attributes, search space and for ranking the service providers. In this paper, we proposed a Fuzzy Rough Set based Cloud Brokerage (FRSCB) architecture, which is responsible for service selection based on consumers Quality of Service (QoS) request. We propose to use Fuzzy Rough Set Theory (FRST) to minimize the number of attributes and searching space. We also did the QoS attribute categorization to identify functional and non-functional requirements and behavior of the attributes (static/dynamic). Finally, we develop an algorithm that recommends potential cloud services to the cloud consumers.