1. Ph.D Theses
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/1/11
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Item Cloud Service Selection and Workflow Scheduling Using P System(National Institute of Technology Karnataka, Surathkal, 2021) Raghavan, Santhanam.; Chandrasekaran, K.Cloud Computing is a decade old technology that has changed the landscape of the internet based business model. This technology manifested itself unheralded, a decade ago and has been growing since. It now stands with several inherent complex problems, as a result of its expansion. Out of several issues being researched, service selection in cloud is one of the prime issues which is getting primary attention. Service selection is a process of selecting (ranking) services from a pool of available cloud services which is often based on multiple Quality of Service (QoS) attributes. Our work is divided into two major components. The first part of our work is solving the problem of cloud service selection. This study proposes inherently parallel, robust models for service selection in cloud based on a natural computing model called membrane computing. Membrane Computing, which is realised using P Systems, is an inherently parallel model that is based on the concept of animal cell interaction. There are several variants of P Systems and here Enzymatic Numerical P System (ENPS) is used, based on its suitability to the problem being solved. Multiple approaches have been proposed and the results are analysed. Additionally, two new software tools required for ENPS execution are proposed. The second part involves designing and implementing the algorithm for workflow scheduling in cloud. Workflow is a group of tasks that are collectively aimed at doing a single work. Cloud workflows consist of tasks to be mapped to Virtual Machines (VMs) that are part of the cloud. The process of assigning limited number of VMs to the tasks in a particular manner to optimize certain quality factor, is referred to as workflow scheduling in cloud. In this study the effort is to minimise makespan, which is the net time taken by the workflow to get executed. The ENPS model is used to obtain the sequence of the schedule, based on which the makespan is calculated and compared with other standard methods.Item Adaptive Resource Management in SLA Aware Elastic Clouds(National Institute of Technology Karnataka, Surathkal, 2019) S, Anithakumari; Chandrasekaran, K.In recent years, there has been an increasing interest in solving the over-provisioning and under-provisioning of elastic cloud resources because of the Service Level Agreement (SLA) violation problem. The recent studies have reported that federated cloud services may serve as a better elastic cloud model over a single provider model. A major problem with the federated cloud is the interoperability between multiple cloud service providers. Therefore in this thesis, a proactive SLA aware adaptive resource management approach is proposed for elastic cloud services. Aim of this thesis is to develop a suitable SLA monitoring framework to predict the SLA violations and adaptively allocate the cloud resources to improve the elasticity. It achieves the mutual benefits for cloud consumers and service providers by means of calculating and reducing penalty cost. Our framework has been implemented and validated on a private cloud using OpenNebula 4.0. The results have shown that the proposed proactive approach has significantly reduced the SLA violations compared to a reactive approach. As an additional contribution, the presented work solves the interoperability issues of the federated cloud using an innovative SLA matching algorithm. The simulation results of this work show that the said approach performs better than its counterparts.Item A Trust Based Security of Resources in Cloud Environment(National Institute of Technology Karnataka, Surathkal, 2018) D, Usha; Chandrasekaran, K.Cloud computing has been attracting the attention of several researchers both in the academia and the industry as it provides many opportunities for organizations by offering a range of computing services. Before cloud computing to become acceptable to everybody both the enterprises and individuals, several issues have to be solved. One of the most important aspects that need to be paid special attention is the cloud security. Trust management is one of the important components in the cloud security that needs special attention. The trust management systems proposed for cloud computing by various researchers have been studied with special emphasis towards their capability and applicability in a practical heterogeneous cloud environment besides implementabilty. An effective trust management system helps cloud service providers and consumers to reap the benefits brought about by cloud computing technologies. Despite the benefits of trust management, several issues related to general trust assessment mechanisms, distrusted feedbacks, poor identification of feedbacks, privacy of participants and the lack of feedbacks integration still need to be addressed. Traditional trust management approaches such as the use of Service Level Agreement are inadequate for complex cloud environments. Due to the multiple vulnerabilities like identification, privacy, personalization, integration, security, and scalability in the existing models, it is proposed for a strong trust model which would create a strong trust between the entities or resources of the cloud. To build a strong trust a strong trust path is necessary between the entities where all the entities in cloud and cloud computing environment would trust each other and the entities that have communication would have valid trust on each other. A mathematical model was proposed to calculate basic trust, dynamic trust and trust for migration.Basic trust was calculated using entropy. Based on the initial trust of the isystem, a new trust for successful transactions was calculated as dynamic trust.The trust models proposed were implemented using Family Gene Genetic Algorithm. The algorithm gives an optimal solution for a large set of data. The implementation of proposed model using this adapted algorithm showed that the resources on a cloud with a strong trust value would always be available for performing any successful transaction. We have proposed a end-to-end trust model which calculates trust based on four parameters namely: utilization, saturation, failure rate and availability. In this model we simulated the results using Monte Carlo method to check with the trust decision making policy. We found from the results that the trust decision is high or low based on the availability of the resources. Based on the trust model and the adapted algorithm the performance of the system using perceived factors were evaluated. The implementation on two different cloud platforms, namely Aneka and Opennebula showed that the model would give better results in terms of Process Time, System Time and Compute Time. Thus we conclude that our model proposes a strong trust path between the entities or resources of the cloud.