Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item A parallel dynamic programming approach for data analysis(Institute of Electrical and Electronics Engineers Inc., 2016) Deepak, A.; Shravya, K.S.; Chandrasekaran, K.In spite of presence of many classical and modified data analysis techniques, data analysis in the field of software engineering still remains a challenge because of the presence of large number of both continuous and discreet explanatory variables judging the outcome of one and more than one dependant variables. Requirement for an efficient multivariate data analysis technique which fulfils the constraints associated with software data led to the design of OSR (optimized set reduction) which uses a greedy algorithm for data analysis using both the principles of machine learning and conventional statistics. With the incoming of big data and other increasing dimensions of data set, we, through this paper, try to propose a new algorithm, based on the similar lines of optimised set reduction, using its strength to extract subsets. As the current trend of programming demands an algorithm to execute in parallel, we also propose a modification to our algorithm for it to run in a multicore platform with good efficiency. © 2015 IEEE.Item Using genetic algorithm for process migration in multicore kernels(Springer Verlag service@springer.de, 2017) Shravya, K.S.; Deepak, A.; Chandrasekaran, K.Process migration is used in multicore operating systems to improve their performance. The implementation of the migration event contributes largely to the performance of the scheduling algorithm and hence decides how effective a multicore kernel is. There have been several effective algorithms which decide how a process can be migrated from one core to another in a multicore operating system. This paper looks further into the mechanism of process migration in multicore operating systems. The main aim of this paper is not to answer how the process migration should take place but it aims to answer when process migration should take place and to decide the site of process migration. For this, an artificial intelligence concept called genetic algorithm is used. Genetic algorithm works on the theory of survival of the fittest to find an optimally good solution during decision making phase. © Springer Nature Singapore Pte Ltd. 2017.Item Image processing approach to diagnose eye diseases(Springer Verlag service@springer.de, 2017) Prashasthi, P.; Shravya, K.S.; Deepak, A.; Mulimani, M.; Shashidhar, K.G.Image processing and machine learning techniques are used for automatic detection of abnormalities in eye. The proposed methodology requires a clear photograph of eye (not necessarily a fundoscopic image) from which the chromatic and spatial property of the sclera and iris is extracted. These features are used in the diagnosis of various diseases considered. The changes in the colour of iris is a symptom for corneal infections and cataract, the spatial distribution of different colours distinguishes diseases like subconjunctival haemorrhage and conjunctivitis, and the spatial arrangement of iris and sclera is an indicator of palsy. We used various classifiers of which adaboost classifier which was found to give a substantially high accuracy i.e., about 95% accuracy when compared to others (k-NN and naive-Bayes). To enumerate the accuracy of the method proposed, we used 150 samples in which 23% were used for testing and 77% were used for training. © Springer International Publishing AG 2017.Item Design and implementation of AQM evaluation suite for ns-3(Association for Computing Machinery acmhelp@acm.org, 2017) Deepak, A.; Shravya, K.S.; Tahiliani, M.P.Excessive buffering in network devices should be avoided because it leads to a series of performance issues such as high queuing latency and variations in delay. Active Queue Management (AQM) algorithms play a vital role in monitoring and controlling the queue length in these devices. Recently there has been a significant progress in the design and development of new AQM algorithms. However, thoroughly evaluating the performance of AQM algorithms is a nontrivial task. In an effort to simplify this, the Active Queue Management and Packet Scheduling Working Group at IETF have proposed informational guidelines in RFC 7928 to test the applicability, performance and deployment complexity of AQM algorithms. This paper presents the design and implementation of an AQM evaluation framework for ns-3 which helps to quickly study the performance of AQM algorithms based on the guidelines mentioned in RFC 7928. The proposed framework automates simulation setup, topology creation, trafiéc generation, program execution, results collection and their graphical representation using ns-3, based on the scenarios mentioned in the RFC. © 2017 ACM.Item Common TCP evaluation suite for ns-3: Design, implementation and open issues(Association for Computing Machinery acmhelp@acm.org, 2017) Nagori, K.; Balachandran, M.; Deepak, A.; Tahiliani, M.P.; Chandavarkar, B.R.This paper presents the design and implementation of a Common TCP Evaluation Suite for ns-3. The proposed evaluation suite uses Tmix to generate realistic synthetic TCP traéc, and is designed in line with the recommendations from Internet Congestion Control Research Group (ICCRG). We discuss the Tmix integration in ns-3, shu.ing connection vectors of the real traces, architecture and validation of the proposed evaluation suite. The correctness of the evaluation suite is verified by comparing the results obtained from it to those from an existing implementation of such a suite in ns-2. Several open issues discovered with Tmix are also discussed in the paper. © 2017 ACM.Item Smart key generation for smart cities(Institute of Electrical and Electronics Engineers Inc., 2017) Shravya, K.S.; Deepak, A.; Chandrasekaran, K.Statistical results have predicted that 70% of world's population will reside in cities by the year 2050. With the advancement in the field of information and communication technology, the concept of smart cities is gaining more prominence. Smart cities use the ICT technology to improve the functioning of the city and enhance the community services provided. To keep the data in smart city secure, different existing security mechanisms have been deployed directly in smart or have been modified to smart city scale. Most of the security mechanisms today need cryptographic keys, hence, key generation plays a pivotal role in the security of any smart city. In this paper, we proposes a key generation methodology especially designed for smart cities using a random number generator which collects entropy from different user end devices and sensors present in the city and generate secure random keys at a central node. We have also tested our method against NSIT random number test suite and have got acceptable results. © 2017 IEEE.