Conference Papers

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    Use of impedance spectroscopy to study the integrity of the aluminium oxide films in mercury embrittled aluminium
    (2010) Clegg, R.E.; Srivastava, A.; Mahadevegowda, M.
    Mercury embrittlement is a significant issue in the gas processing industry, where the precipitation of mercury from the gas stream in cryogenic heat exchangers can lead to embrittlement of the aluminium structure and it has been the cause of several significant failures. This paper studies the use of impedance spectroscopy to examine the interface between mercury droplets and 5083 aluminium. As-received, mechanically polished and artificially aged samples were examined using a two electrode mode with a zero bias. The Nyquist results indicated that as-received and polished and aged samples behaved as an R s-C-R p type circuit, indicating that the oxide film could be modelled as a capacitor and resistor in parallel. Using the dielectric constant of alumina, the capacitance results yielded oxide films of thickness between 2.2 and 50 nm, depending on the degree of aging of the sample. By gradually increasing the voltage amplitude, it was found that the interface broke down at a field strength of approximately 10MV/m, which is similar to the dielectric field strength of alumina. Immediately after polishing, however, no film was found and the interface appeared to be a simple short circuit. A series of bend tests coupled with the frequency response analyser were used to demonstrate that the film remained continuous beyond the point at which plastic deformation occurred and in many cases up until the point at which embrittlement occurred. These results have confirmed that the oxide film on aluminium can effectively separate mercury from the underlying aluminium alloy and that impedance spectroscopy is a useful tool for studying the stability of the interface.
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    Inconsistency in DNA computing and it's use in cryptography
    (2013) Srivastava, A.; Pandey, V.
    The computational and storage limitations with silicon computers have propelled computer scientists to search for new dimensions in computer science. DNA computing emerges out to be a very promising field. The use of DNA strands would enable us to do complex calculations in seconds, which would have otherwise needed years. The volumes of data that can be stored have reached a new limit. Recently researchers of Harvard crack DNA storage and have been able to cram 700 terabytes of data into a single gram of DNA strand While developing any system a lot of design issues have to be taken into consideration and same is applicable for DNA computers. The paper makes an effort to deal with the consistency issue of DNA computers. A proof of inconsistency is provided and ground rules to a few DNA based cryptosystems are indexed which take advantage of the inconsistency and make use of it for data security. © 2013 IEEE.
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    Classification of multi-genomic data using MapReduce paradigm
    (Institute of Electrical and Electronics Engineers Inc., 2015) Pahadia, M.; Srivastava, A.; Srivastava, D.; Patil, N.
    Counting the number of occurences of a substring in a string is a problem in many applications. This paper suggests a fast and efficient solution for the field of bioinformatics. A k-mer is a k-length substring of a biological sequence. k-mer counting is defined as counting the number of occurences of all the possible k-mers in a biological sequence. k-mer counting has uses in applications ranging from error correction of sequencing reads, genome assembly, disease prediction and feature extraction. We provide a Hadoop based solution to solve the k-mer counting problem and then use this for classification of multi-genomic data. The classification is done using classifiers like Naive Bayes, Decision Tree and Support Vector Machine(SVM). Accuracy of more than 99% is observed. © 2015 IEEE.
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    Genome Data Analysis Using MapReduce Paradigm
    (Institute of Electrical and Electronics Engineers Inc., 2015) Pahadia, M.; Srivastava, A.; Srivastava, D.; Patil, N.
    Counting the number of occurences of a substringin a string is a problem in many applications. This paper suggests a fast and efficient solution for the field of bioinformatics. Ak-mer is a k-length sub string of a biological sequence. K-mercounting is defined as counting the number of occurences of all the possible k-mers in a biological sequence. K-mer counting has uses in applications ranging from error correction of sequencing reads, genome assembly, disease prediction and feature extraction. The current k-mer counting tools are both time and space costly. We provide a solution which uses MapReduce and Hadoop to reduce the time complexity. After applying the algorithms on real genome datasets, we concluded that the algorithm using Hadoopand MapReduce Paradigm runs more efficiently and reduces the time complexity significantly. © 2015 IEEE.
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    MatchVNE: A Stable Virtual Network Embedding Strategy Based on Matching Theory
    (Institute of Electrical and Electronics Engineers Inc., 2023) Keerthan Kumar, T.G.K.; Srivastava, A.; Satpathy, A.; Addya, S.K.; Koolagudi, S.G.
    Network virtualization (NV) can provide greater flexibility, better control, and improved quality of service (QoS) for the existing Internet architecture by enabling heterogeneous virtual network requests (VNRs) to share the substrate network (SN) resources. The efficient assignment of the SN resources catering to the demands of virtual machines (VMs) and virtual links (VLs) of the VNRs is known as virtual network embedding (VNE) and is proven to be NP-Hard. Deviating from the literature, this paper proposes a framework MatchVNE that is focused on maximizing the revenue-to-cost ratio of VNRs by considering a blend of system and topological attributes that better capture the inherent dependencies among the VMs. MatchVNE performs a stable VM embedding using the deferred acceptance algorithm (DAA). The preference of the VMs and servers are generated using a hybrid entropy, and the technique for order of preference by similarity to ideal solution (TOPSIS) based ranking strategy for VMs and servers. The attribute weights are determined using entropy, whereas the server and VM ranking are obtained via TOPSIS. The shortest path, VL-embedding, follows VM-embedding. The simulation results show that MatchVNE outperforms the baselines by achieving a 23% boost in the average revenue-to-cost-ratio and 44% improvement in the average acceptance ratio. © 2023 IEEE.