Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item CAD tools for antennas(2008) Bhavatharini, S.; Raghavan, S.; Sriram Kumar, D.S.There are a number of CAD tools available in the market today for microwave designs. They enable the designer to try his hand at even very complex design very easily and quickly. They optimize MEMS designs prior to fabrication, which reduces prototype development cycle time and cuts manufacturing costs. This paper attempts to list a few of the popular CAD tools that are available in the market today and highlights on their special features that makes each tool unique. © 2008 IEEE.Item Antenna gain determination using a microwave CAD tool-HFSS(2008) Bojja Venkatakrishnan, B.V.; Srivatsan, R.; Raghavan, S.; Sriram Kumar, D.S.Antennas have been increasingly studied in recent years. Different antennas have been designed for different applications based on the characteristics of the receiving side. Antennas cannot be fabricated as such and then be studied on. This leads to waste of material and requires a lot of iterations until we get the final design. In order to study the characteristics of an antenna without fabricating it, we need a special tool called a "SIMULATOR TOOL". It can determine all possible characteristics of an antenna under test. In this paper we'll be simulate few of the antennas using HFSS simulator tool. © 2008 IEEE.Item Bat algorithm for scheduling workflow applications in cloud(Institute of Electrical and Electronics Engineers Inc., 2015) Raghavan, S.; Sarwesh, P.; Marimuthu, C.; Chandrasekaran, K.Workflow is one of the important aspects of cloud computing today. Cloud computing is one of the fastest growing technologies in the world. Workflows can be used in cloud as we use them in grid. Many operations in the cloud are based on workflow execution. Workflow systems are now becoming more complex and for such kind of systems efficient workflow management is important. Workflow scheduling is an important part of workflow management. Scheduling in general is NP-hard problem. To solve such kind of problems exhaustive methods cannot be used. Only non-exhaustive techniques can be used. In this paper we have used a metaheuristic approach called bat algorithm. Bat algorithm is specifically designed for optimizing hard problems. Here, bat algorithm with the help of binary bat algorithm is used for scheduling workflow in a cloud. Specifically the mapping of tasks and resources is done using this method. The optimal resources are selected such that the overall cost of the workflow is minimal. © 2015 IEEE.Item Tools and simulators for membrane computing-a literature review(Springer Verlag service@springer.de, 2016) Raghavan, S.; Chandrasekaran, K.Membrane Computing comes under the field of Natural Computing. This was introduced by Gheorghe Paun. This field has been there from a decade. To realize Membrane Computing it is important to have tools that can be used either to process or simulate membrane computing. There have been several attempts in this area. This paper is an attempt to provide the details of the tools that are available for membrane computing. Primarily the tools are classified into two components. On one hand we have tools that are being used for specific type of P Systems or the tools which have a specific application. On the other hand there are tools which are comparatively generic in nature. Further this paper lists the tools that have been designed and developed to be used for the biological applications of P Systems. After classification, a brief description of the tools is given in this paper. Finally a brief quantitative analysis of the tools is done. Though there have been few surveys of P System tools, this is a slightly different paper which tries to classify and tries to a give review of the tools. © Springer Nature Singapore Pte Ltd. 2016.Item Analysis of emerging workflow scheduling algorithms in cloud(Institute of Electrical and Electronics Engineers Inc., 2016) Raghavan, S.; Chandrasekaran, K.Workflow has a great impact on several diverse fields of science such as Physics, Bioinformatics, Astronomy etc. The computational requirements of the world is increasing exponentially and so the use of workflows. These requirements are expected to increase by many folds. Thus workflow can be considered as one of the important areas to be explored. Workflow is used extensively by the scientific community for automation. Similarly these workflows have a significant impact on grid computing, cloud computing and other distributed environments. Moreover it is because of grid computing technology that power of workflow is realizable. Similarly cloud computing also supports workflows. Workflow scheduling is considered to be the core when it comes to workflow thus it is highly important to know what are workflow scheduling algorithms available for scheduling workflow in cloud. This paper gives an overview about workflow, the impact of workflows on cloud and other important issues related to it are presented. This paper primarily focuses on Workflow scheduling algorithms in cloud and analysis of the same is presented. © 2015 IEEE.Item 3d nano capacitors using electrodeposited nickel nanowires in porous anodic alumina template(Springer Science and Business Media, LLC, 2019) Viegas, A.E.; Dutta, S.; Rekha, S.; Bobji, M.S.; Raghavan, S.; Bhat, N.We report the fabrication and characterization of a new design of 3D nano Capacitors using Alumina nanopores as the dielectric material. Nickel nanowires grown inside the nanopores act as high surface area electrodes. These wires are combined together in the form interdigitated capacitor structure, to achieve very high capacitance density. © Springer Nature Switzerland AG 2019.Item Singlow: Simulator for General Network Flow Problems(Institute of Electrical and Electronics Engineers Inc., 2020) Raghavan, S.; Bhagtya, P.; Chandrasekaran, K.Simulation is an important process and an inevitable part of engineering. There are several applications of simulation with one of the important being visualization of complex methods and processes. This paper aims at creating a simulator for general network flow optimization problems. This work uses a modular approach for creating a simulator. A simulator in this area is necessary for several reasons. The main reason for requirement is its usefulness in explaining the problems to the people/students who might use these kinds of network optimization methods to solve several variety of problems. This simulator can simulate standard problems namely transportation problems with various methods, network flow problem and some popular problems in that area. This simulator will be helpful for educational institutions to teach the students about the standard problems on network flow optimization. Here this paper proposes a framework i.e. Singlow for the above mentioned purpose. This paper explains the framework with the flow of execution by keeping in mind a general simulation software. The Simulator has been designed and implemented using Processing 3.4, a software which facilitates designing graphical user interfaces. © 2020 IEEE.Item Workload classification in multi-vm cloud environment using deep neural network model(Association for Computing Machinery, 2021) Bhagtya, P.; Raghavan, S.; Chandrasekaran, K.; Divakarla, U.In this competitive world, everyone needs to be prepared for future risks and emergency conditions. In a multi-cloud environment users can easily shift from one cloud to another cloud because of the available data and application transfer technologies. Therefore a strong forecast system is mandatory for such conditions and to stop user migration to other clouds. Virtual Machine (VM) plays an important role in effective resource management and cost reduction in cloud infrastructure. Workload prediction in multi-VM is very useful to handle uncertain situations. In this paper, we propose a promising workload prediction technique that can handle the workload from multiple virtual machines. It has a pre-processing and feature selection engine that handles direct data from these virtual machines and the model is strong enough in classifying data based on historical workloads. This classification enables extra knowledge for the cloud vendor to optimize resource usage. This strategy can be used for producing an alarm whenever there is continuously high utilization of resources in the future. Here, our prediction methodology is experimented with a popular real-world Grid Workload Archive (GWA) dataset and it achieves more than 85% prediction accuracy for CPU, Memory and Disk Utilization. © 2021 Owner/Author.