Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Monitoring and Management of Service Level Agreements in Cloud Computing(Institute of Electrical and Electronics Engineers Inc., 2015) Anithakumari, S.; Chandrasekaran, K.Cloud computing environment consists of various interactive entities like cloud service providers, cloud service brokers, cloud customers and end-users with different objectives and expectations. Service Level Agreements (SLAs) manage the relationship among cloud service providers and cloud consumers by defining the terms of the agreement for the participating entities and provide the basic ground for interactions among both the parties. In this work we proposed a framework to efficiently monitor and analyze the SLA parameters and tried to find out the possibility of occurrence of SLA violations. Also we implemented an adaptive resource allocation system by utilizing the results of predicted SLA violations. Our adaptive resource allocation system allocates computing resources to cloud applications and tries to reduce the occurrence of SLA violations, by allocating additional resources on the detection of possibility of occurrence of a violation. The experimental studies show that our proposed system works well in private cloud computing environment and gives more efficient results. © 2015 IEEE.Item Negotiation and monitoring of service level agreements in cloud computing services(Springer Verlag service@springer.de, 2017) Anithakumari, S.; Chandrasekaran, K.SLAs are so significant in cloud computing because it establishes agreements between the cloud service providers and cloud consumers, about the quality of the providing service. SLA monitoring is the only available provision to check whether the agreed parties are following the agreement terms or not. A multistep SLA negotiation, which contains the selection of apt cloud service provider and the negotiation with the selected provider, is proposed here. An efficient SLA negotiation algorithm is also included in this negotiation method. Experimental evaluation shows that the proposed method is more efficient in resource allocation and it gives more revenue to the cloud providers. © Springer Science+Business Media Singapore 2017.Item Adaptive resource allocation in interoperable cloud services(Springer Verlag, 2019) Anithakumari, S.; Chandrasekaran, K.Interoperable cloud computing is the one in which the services or resources of one cloud can be accessed by another cloud. The implementation of interoperable cloud architecture is a challenging one because various characteristics of the cloud computing environment need to be considered for its achievement. The aim of this work is to implement interoperable cloud computing with the awareness of service-level agreements and to provide adequate resources when shortage of resources occurs at one cloud while providing the agreed services to the user. To achieve this, we proposed a methodology of interoperability-based flexible resource management. Initially, the SLA templates of private and public cloud are mapped using the Soft TF-IDF metric with case-based reasoning (CBR) approach. Then, based on the mapped SLAs, different clusters of cloud providers are formed with the help of K-means clustering technique. And finally, if one of the cloud in a cluster faces the problem of resource shortage, the flexible resource allocation is provided through the adaptive dimensional search algorithm. © Springer Nature Singapore Pte Ltd. 2019.Item Allocation of cloud resources in a dynamic way using an sla-driven approach(Springer Verlag service@springer.de, 2019) Anithakumari, S.; Chandrasekaran, K.Cloud computing provides a wide access to complex applications running on virtualized hardware with its support for elastic resources that are available in an on-demand manner. In cloud environment, multiple users can request resources simultaneously and so it has to be made available to them in an efficient manner. For the efficient utilization, these computing resources can be dynamically configured according to varying workload. Here in this paper, we proposed an efficient resource management system to allocate elastic resources dynamically according to dynamic workload. © 2019, Springer Nature Singapore Pte Ltd.