Faculty Publications
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Item Virtual machine migration—a perspective study(Springer Verlag service@springer.de, 2018) Joseph, C.; Martin, J.P.; Chandrasekaran, K.; Kandasamy, A.The technology of Cloud computing has been ruling the IT world for the past few decades. One of the most notable tools that helped in prolonging the reign of Cloud computing is virtualization. While virtualization continues to be a boon for the Cloud technology, it is not short of its own pitfalls. One such pitfall results from the migration of virtual machines. Though migration incurs an overhead on the system, an efficient system cannot neglect migrating the virtual machines. This work attempts to carry out a perspective study on virtual machine migration. The various migration techniques proposed in the literature have been classified based on the aspects of migration that they consider. A survey of the various metrics that characterize the performance of a migration technique is also done. © 2018, Springer Nature Singapore Pte Ltd.Item Unraveling the challenges for the application of fog computing in different realms: A multifaceted study(Springer Verlag service@springer.de, 2019) Martin, J.P.; Kandasamy, A.; Chandrasekaran, K.Fog computing is an emerging paradigm that deals with distributing data and computation at intermediate layers between the cloud and the edge. Cloud computing was introduced to support the increasing computing requirements of users. Later, it was observed that end users experienced a delay involved in uploading the large amounts of data to the cloud for processing. Such a seemingly centralized approach did not provide a good user experience. To overcome this limitation, processing capability was incorporated in devices at the edge. This led to the rise of edge computing. This paradigm suffered because edge devices had limited capability in terms of computing resources and storage requirements. Relying on these edge devices alone was not sufficient. Thus, a paradigm was needed without the delay in uploading to the cloud and without the resource availability constraints. This is where fog computing came into existence. This abstract paradigm involves the establishment of fog nodes at different levels between the edge and the cloud. Fog nodes can be different entities, such as personal computers (PCs). There are different realms where fog computing may be applied, such as vehicular networks and the Internet of Things. In all realms, resource management decisions will vary based on the environmental conditions. This chapter attempts to classify the various approaches for managing resources in the fog environment based on their application realm, and to identify future research directions. © Springer Nature Singapore Pte Ltd. 2019.Item A comprehensive survey on federated cloud computing and its future research directions(Springer Science and Business Media Deutschland GmbH, 2021) Shishira, S.R.; Kandasamy, A.The cloud computing paradigm is popular due to its pay-as-you-go model. Due to its increasing demand for service, the user has a huge advantage in paying for the service currently needed. In a federated cloud environment, there is one or more number of cloud service providers who share their servers to service the user request. It improves minimizing cost, utilization of services and improves performance. Clients will get benefited as there is a Service Level Agreement between both. In the present paper, survey is provided on the benefits of the federated environment, its architecture, provision of resources and future research directions. Paper also gives the comparative study on the above aspects. © Springer Nature Singapore Pte Ltd 2021.Item Explicating fog computing key research challenges and solutions(CRC Press, 2021) Martin, J.P.; Singh, V.; Chandrasekaran, K.; Kandasamy, A.[No abstract available]Item A phenomic approach to genetic algorithms for reconstruction of gene networks(2010) D'Souza, R.G.L.; Chandra Sekaran, K.C.; Kandasamy, A.Genetic algorithms require a fitness function to evaluate individuals in a population. The fitness function essentially captures the dependence of the phenotype on the genotype. In the Phenomic approach we represent the phenotype of each individual in a simulated environment where phenotypic interactions are enforced. In reconstruction type of problems, the model is reconstructed from the data that maps the input to the output. In the phenomic algorithm, we use this data to replace the fitness function. Thus we achieve survival-of-the- fittest without the need for a fitness function. Though limited to reconstruction type problems where such mapping data is available, this novel approach nonetheless overcomes the daunting task of providing the elusive fitness function, which has been a stumbling block so far to the widespread use of genetic algorithms. We present an algorithm called Integrated Pheneto-Genetic Algorithm (IPGA), wherein the genetic algorithm is used to process genotypic information and the phenomic algorithm is used to process phenotypic information, thereby providing a holistic approach which completes the evolutionary cycle. We apply this novel evolutionary algorithm to the problem of elucidation of gene networks from microarray data. The algorithm performs well and provides stable and accurate results when compared to some other existing algorithms. © 2010 Springer-Verlag Berlin Heidelberg.Item Inference of Gene Networks from Microarray Data through a Phenomic Approach(2010) D'Souza, R.G.L.; Chandra Sekaran, K.C.; Kandasamy, A.The reconstruction of gene networks is crucial to the understanding of cellular processes which are studied in Systems Biology. The success of computational methods of drug discovery and disease diagnosis is dependent upon our understanding of the biological basis of the interaction networks between the genes. Better modelling of biological processes and powerful evolutionary methods are proving to be a key factor in the solution of such problems. However, most of these methods are based on processing of genotypic information. We present an evolutionary algorithm for inferring gene networks from expression data using phenotypic interactions. The benefit of this is that we avoid the need for an explicit objective function in the optimization process. In order to realize this, we have implemented a method called as the Phenomic algorithm and validated it for stability and accuracy in the reconstruction of gene networks. © Springer-Verlag Berlin Heidelberg 2010.Item LES of flow over a circular cylinder at high Reynolds number(Indian Institute of Technology, IIT, Kanpur, 2011) Rajani, B.N.; Kandasamy, A.; Majumdar, S.Turbulent flow past a circular cylinder at Re = 1.4 × 105 has been analysed using Large Eddy Simulation (LES) approach solving filtered unsteady 3D NS equations coupled to Smagorinsky and dynamic subgrid scale (SGS) models. These simulations have been carried out using a parallel multiblock structured code which employs an implicit second-order accurate pressure-based finite volume method for solving Navier-Stokes equations for unsteady turbulent incompressible flow situations. The predictions are validated against detailed measurement data for mean as well as turbulence quantities. © IUTAM Symposium on Bluff Body Flows, Blubof 2011.Item Entrance region flow of casson fluid in a circular tube(2012) Kandasamy, A.; Pai, R.G.The entrance region flow of a Casson fluid in a tube has been investigated numerically without making prior assumptions on the form of velocity profile within the boundary layer region, which is determined by a cross sectional integration of the momentum differential equation for a given distance from the channel entrance. Using the macroscopic mass and momentum balance equations, the thickness of the core, the entrance length, and the pressure drop have been obtained at each cross section of the entrance region of the tube for specific values of Casson number. © (2012) Trans Tech Publications, Switzerland.Item Node - Link disjoint multipath routing protocols for wireless sensor networks - A survey and conceptual modeling(2012) Muni Venkateswarlu, K.; Chandra Sekaran, K.C.; Kandasamy, A.There are different ways to classify the routing protocols that are available. The paper presented here discusses different types of multipath routing protocols for Wireless sensor networks based on the parameter "Disjointedness". In this paper, First, WSN routing issues are discussed then listed the advantages of Multipath routing. Further, comprehensive study of different types of WSN Disjoint-multipath routing protocols is given. Finally, some of the WSN multipath routing on-going research issues are listed. © 2012 Springer-Verlag.Item A multiobjective phenomic algorithm for inference of gene networks(2012) D'Souza, R.G.L.; Chandra Sekaran, K.C.; Kandasamy, A.Reconstruction of gene networks has become an important activity in Systems Biology. The potential for better methods of drug discovery and of disease diagnosis hinge upon our understanding of the interaction networks between the genes. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However, all these methods are based on processing of genotypic information. We have presented an evolutionary algorithm for reconstructing gene networks from expression data using phenotypic interactions, thereby avoiding the need for an explicit objective function. Specifically, we have also extended the basic phenomic algorithm to perform multiobjective optimization for gene network reconstruction. We have applied this novel algorithm to the yeast sporulation dataset and validated it by comparing the results to the links found between genes of the yeast genome at the SGD database. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.