Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Binu, A.Subject: search.filters.subject.Cloud computing

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    Energy Aware SLA with Classification of Jobs for Cloud Environment
    (Elsevier B.V., 2015) Joy, N.; Chandrasekaran, K.; Binu, A.
    The accelerated growth of the cloud eco-system is leading to the progress of new services, innovative ideas for the service replen- ishing and the newest interaction models both among the cloud providers and the customers which take advantage of the cloud resources. SLAs are one of the factors which allow for different interactions by keeping the objectives over privacy,QoS attributes and security constraints driving towards QoP attributes, the description of actions is needed in order to deliver the services ac- cording to the QoS attributes as expected by the customers. Energy aware SLAs extends the existing SLA agreements in order to include energy and carbon aware parameters. In this paper we propose an approach in order to relax certain jobs in a standardized way to obtain high energy consumption without disturbing the efficiency and availability of the system especially during the peak load times. The results for the above proposal are being discussed in this paper and were able to find that it is energy efficient. © 2015 The Authors.
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    Optimization-Aware scheduling in cloud computing
    (Association for Computing Machinery acmhelp@acm.org, 2016) Binu, A.; George, N.; Chandrasekaran, K.
    Cloud computing allows delivery of computational resources via internet. Some of the computational resources include signals, codes and physical resources. Cloud users require computational resources for execution of their tasks. The computational elements, when thoroughly assigned to the cloud users according to requirement facilitate an efficient scheduling mechanism. The efficiency is dependent on the parameters chosen to promote the assignment of task to resources. Here, computational cost is chosen as the optimization factor, and the solution with the least cost is selected as the best assignment. A Cuckoo Search inspired technique is used, and task assignment to resources is done by validating the solution with the least value of cost. © 2016 ACM.