Conference Papers
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Item RPRDC: Reliable Proliferation Routing with low Duty-cycle in Wireless Sensor Networks(Elsevier, 2015) Venkatesha, n.; Ashwini, T.N.; Akshay, A.L.; Tejaswi, V.; Venugopal, K.R.; Iyengar, S.S.; Patnaik, L.M.Ensuring reliable energy efficient data communication in resource constrained Wireless Sensor Networks (WSNs) is of primary concern. Traditionally, two types of re-transmission have been proposed for the data-loss, namely, End-to-End loss recovery (E2E) and per hop. In these mechanisms, lost packets are re-transmitted from a source node or an intermediate node with a low success rate. The proliferation routing1 for QoS provisioning in WSNs low End-to-End reliability, not energy efficient and works only for transmissions from sensors to sink. This paper proposes a Reliable Proliferation Routing with low Duty Cycle [RPRDC] in WSNs that integrates three core concepts namely, (i) reliable path finder, (ii) a randomized dispersity, and (iii) forwarding. Simulation results demonstrates that packet successful delivery rate can be maintained upto 93% in RPRDC and outperform Proliferation Routing1. © 2015 The Authors.Item FIVDL: Fingerprint Image Verification using Dictionary Learning(Elsevier, 2015) Arunalatha, J.S.; Tejaswi, V.; Shaila, K.; Anvekar, D.; Venugopal, K.R.; Iyengar, S.S.; Patnaik, L.M.Fingerprints are used for identification in forensics and are classified into Manual and Automatic. Automatic fingerprint identification system is classified into Latent and Exemplar. A novel Exemplar technique of Fingerprint Image Verification using Dictionary Learning (FIVDL) is proposed to improve the performance of low quality fingerprints, where Dictionary learning method reduces the time complexity by using block processing instead of pixel processing. The dynamic range of an image is adjusted by using Successive Mean Quantization Transform (SMQT) technique and the frequency domain noise is reduced using spectral frequency Histogram Equalization. Then, an adaptive nonlinear dynamic range adjustment technique is utilized to determine the local spectral features on corresponding fingerprint ridge frequency and orientation. The dictionary is constructed using spatial fundamental frequency that is determined from the spectral features. These dictionaries help in removing the spurious noise present in fingerprints and reduce the time complexity by using block processing instead of pixel processing. Further, dictionaries are used to reconstruct the image for matching. The proposed FIVDL is verified on FVC database sets and Experimental result shows an improvement over the state-of-the-art techniques. © 2015 The Authors.Item Query click and text similarity graph for query suggestions(Springer Verlag service@springer.de, 2015) Sejal, D.; Shailesh, K.G.; Tejaswi, V.; Anvekar, D.; Venugopa, K.R.; Iyengar, S.S.; Patnaik, L.M.Query suggestion is an important feature of the search engine with the explosive and diverse growth of web contents. Different kind of suggestions like query, image, movies, music and book etc. are used every day. Various types of data sources are used for the suggestions. If we model the data into various kinds of graphs then we can build a general method for any suggestions. In this paper, we have proposed a general method for query suggestion by combining two graphs: (1) query click graph which captures the relationship between queries frequently clicked on common URLs and (2) query text similarity graph which finds the similarity between two queries using Jaccard similarity. The proposed method provides literally as well as semantically relevant queries for users’ need. Simulation results show that the proposed algorithm outperforms heat diffusion method by providing more number of relevant queries. It can be used for recommendation tasks like query, image, and product suggestion. © Springer International Publishing Switzerland 2015.Item SGR: Secure geographical routing in Wireless Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2015) Lata, B.T.; Tejaswi, V.; Shaila, K.; Raghavendra, M.; Venugopal, K.R.; Iyengar, S.S.; Patnaik, L.M.Geographical Routing Technique is a new trend in Wireless Sensor Networks in which the sensor nodes are enabled using Global Positioning Systems(GPS). This helps to easily detect the position of their neighboring nodes. The power consumption is more in the existing routing algorithms, since the nodes build the routing tables and the neighboring node IDs are determined by searching the routing table. In this paper, we have proposed Secure Geographical Routing (SGR) algorithm in which the data traffic and energy consumption is minimized using single copy data transfer. In SGR, initially one copy is transmitted to the next node using greedy approach and another copy is preserved in the sending station. If acknowledgment is not received even after timeout then the second copy is transmitted. This dynamic single copy scheme reduces the data traffic in Wireless Sensor Networks. Security algorithms are incorporated in every sensor node to prevent any malicious node attack that disturb the normal functioning of the network. Simulation result shows that the performance of the proposed algorithm is better in terms of packet delivery probability and energy consumption in comparison with existing algorithms. © 2014 IEEE.Item Time stamp based set covering greedy algorithm(Association for Computing Machinery acmhelp@acm.org, 2015) Vasanthi, P.; Tejaswi, V.; Santhi Thilagam, P.Influence maximization deals with finding a small set of target nodes that can be initially activated, such that the influence spread beginning with this causes maximum number of expected activated nodes in the network. Most of the existing algorithms for choosing the seed set concentrate only on the structural properties of the network. We would like to emphasize that it is equally important that a user should be actively involved with his neighbours in order to successfully influence them. Hence a novel measure termed as 'Activeness' of a user which is based on timestamp of the user's recent communication with his neighbours is considered. On the same lines, we propose time stamp based set covering greedy (TSCG) algorithm for seed set selection and a Time stamp based threshold model to map the information diffusion in the network. As a part of our experiments, we compare and analyse the results with degree centrality measure and set covering greedy(SCG) algorithm and cite that the spread achieved by our proposed algorithm though lesser in some cases, is more accurate. © 2015 ACM.Item SALR: Secure adaptive load-balancing routing in service oriented wireless sensor networks(Institute of Electrical and Electronics Engineers Inc., 2015) Lata, B.T.; Sumukha, T.V.; Suhas, H.; Tejaswi, V.; Shaila, K.; Venugopal, K.R.; Anvekar, D.; Patnaik, L.M.Congestion control and secure data transfer are the major factors that enhance the efficiency of Service Oriented Wireless Sensor Networks. It is desirable to modify the routing and security schemes adaptively in order to respond effectively to the rapidly changing Network State. Adding more complexities to the routing and security schemes increases the end-to-end delay which is not acceptable in Service Oriented WSNs which are mostly in real time. We propose an algorithm Secure Adaptive Load-Balancing Routing (SALR) protocol, in which the routing decision is taken at every hop considering the unforeseen changes in the network. Multipath selection based on Node Strength is done at every hop to decide the most secure and least congested route. The system predicts the best route rather than running the congestion detection and security schemes repeatedly. Simulation results show that security and latency performance is better than reported protocols. © 2015 IEEE.Item QRGQR: Query relevance graph for query recommendation(Institute of Electrical and Electronics Engineers Inc., 2015) Sejal, D.; Shailesh, K.G.; Tejaswi, V.; Anvekar, D.; Venugopal, K.R.; Iyengar, S.S.; Patnaik, L.M.Query recommendation is an important feature of the search engine with the explosive and diverse growth of web contents. Different kind of recommendation like query, image, movies, music and book etc. Are used every day. Various types of data sources are used for the recommendations. If we model the data into various kinds of graphs then we can build a general method for any recommendation. In this paper, we have proposed a general method for query recommendation by combining two graphs: 1) query click graph which captures the relationship between queries frequently clicked on common URLs and 2) query text similarity graph which finds the similarity between two queries using Jaccard similarity. The proposed method provides literally as well as semantically relevant queries for users' need. Simulation results show that the proposed algorithm outperforms heat diffusion method by providing more number of relevant queries. It can be used for recommendation tasks like query, image, and product recommendation. © 2015 IEEE.Item PCVOS: Principal component variances based off-line signature verification(Institute of Electrical and Electronics Engineers Inc., 2015) Arunalatha, J.S.; Prashanth, C.R.; Tejaswi, V.; Shaila, K.; Raja, K.B.; Anvekar, D.; Venugopal, K.R.; Iyengar, S.S.; Patnaik, L.M.Offline signature verification system is widely used as a behavioral biometric for identifying a person. This behavioral biometric trait is a challenge in designing the system that has to counter intrapersonal and interpersonal variations. In this paper, we propose a novel technique PCVOS: Principal Component Variances based Off-line Signature Verification on two critical parameters viz., the Pixel Density (PD) and the Centre of Gravity (CoG) distance. It consists of two parallel processes, namely Signature training which involves extraction of features from the samples of database and Test signature analysis which performs extraction of features from the test samples. The trained values from the database are compared with the features of the test signature using Principal Component Analysis (PCA). The PCVOS algorithm shows a notable improvement over the algorithms in [21], [22] and [23]. © 2015 IEEE.Item WNPWR: Web navigation prediction framework for webpage recommendation(Institute of Electrical and Electronics Engineers Inc., 2015) Sejal, D.; Kamalakant, T.; Tejaswi, V.; Anvekar, D.; Venugopal, K.R.; Iyengar, S.S.; Patnaik, L.M.Huge amount of user request data is generated in web-log. Predicting users' future requests based on previously visited pages is important for web page recommendation, reduction of latency, on-line advertising etc. These applications compromise with prediction accuracy and modelling complexity. we propose a Web Navigation Prediction Framework for webpage Recommendation(WNPWR) which creates and generates a classifier based on sessions as training examples. As sessions are used as training examples, they are created by calculating average time on visiting web pages rather than traditional method which uses 30 minutes as default timeout. This paper uses standard benchmark datasets to analyze and compare our framework with two-tier prediction framework. Simulation results shows that our generated classifier framework WNPWR outperforms two-tier prediction framework in prediction accuracy and time. © 2015 IEEE.Item Diffusion models and approaches for influence maximization in social networks(Institute of Electrical and Electronics Engineers Inc., 2016) Tejaswi, V.; Bindu, P.V.; Santhi Thilagam, P.S.Social Network Analysis (SNA) deals with studying the structure, relationship and other attributes of social networks, and provides solutions to real world problems. Influence maximization is one of the significant areas in SNA as it helps in finding influential entities in online social networks which can be used in marketing, election campaigns, outbreak detection, and so on. It deals with the problem of finding a subset of nodes called seeds such that it will eventually spread maximum influence in the network. This paper focuses on providing a complete survey on the influence maximization problem and covers three major aspects: i) different types of input required ii) influence propagation models that map the spread of influence in the network, and iii) the approximation algorithms suggested for seed set selection. We also provide the state of the art and describe the open problems in this domain. © 2016 IEEE.