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Major objective of cloud provider is to maximize the resource utilization of cloud servers as well as to reduce the energy consumption and operative cost of the datacenter. However, the servers in many existing datacenters are underutilized in practice due to over-provisioning of peak demand. Many times, the datacenter come across situations wherein large number of application requests simultaneously demand multidimensional resources such as CPU, memory, bandwidth. In such situations it is highly impractical for the cloud service provider to satisfy the application requests of all the users within stipulated time, especially when sufficient resources are not available with them. In order to address this problem, we designed a system which measures the resource utilization of all servers before allocating the application requests to server and then dynamically allocate the application requests to the server which is underutilized. This yields in improving the overall utilization of servers. Our system initially checks the server utilization in terms of CPU, Memory and Bandwidth resource utilization against predefined threshold value. If resource of any server goes beyond its threshold value, then application request will not be allocated to that server to avoid the server overloading. That means our system redirect the application request to the underutilized server so as to improve the server resource utilization in the face of multidimensional resource constraints. The experimental results demonstrate that our system improves the overall server resource utilization by 10%.

Cloud Service Provider, User Request, Resource utilization, Resource constraints

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S.K. Sonkar, M. U. Kharat, "Improving Overall usage of Servers by Measuring Uneven Utiliztion of a Server and allocating the Applications in the Face of Multidimensional Resource Constraints," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.300-307, 2018.

A web service is a software system designed to support interoperable machine-to-machine interaction over a network. In today’s date, web services are becoming widespread to utilize the web as a business opportunity for offering their own services and using existing services from others. A web service is a service offered by an electronic device to another electronic device, communicating with each other via the World Wide Web. A web service registry UDDI (Universal Description, Discovery, and Integration) provides interoperable, standards based approach for methodically documenting and publishing web services. Since various services are available, it becomes difficult to find the most appropriate service for an exact application. Faced with the increasing numbers of Web services and service users, researchers in the services computing field have attempted to address a challenging issue, i.e. how to quickly find the suitable ones according to user queries. Many previous studies have been reported towards this direction. This paper presents a study on different web service discovery approaches.

Web Mining, Web Service Discovery

[1] G. Senthil Kumar, Dr. C. Lakshmi, “A Literature Survey on Web Service Discovery”, International Journal of Engineering and Technology (IJET), May 2016
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[6] Jaber K Walid C Khaled G, “Binding Web Services: an Optimizing Approach” Proceedings of the 2012 International Conference on Cloud Computing and Service Computing, CSC. Shanghai. 2012 Nov 22-24, pp .64-71
[7] Zhou J, Zhang T, Meng H, Xiao L , Chen G, Li D, “Web Service Discovery based on Keyword clustering and ontology” , IEEE International Conference on Granular Computing, Hangzhou . 2008 Aug 26-28, pp. 844-48.
[8] Dmytro S. Pukhkaiev, Oleksii Oleksenko, Tetiana M. Kot, Larysa S. Globa Alexander Schill, “Advanced Approach To Web Service Discovery And Selection”, Information and Telecommunication Sciences, 2014
[9] Debajyoti Mukhopadhyay, Archana Chougule, “A Survey on Web Service Discovery Approaches”
[10] Rajendran and Dr. P. Balasubramanie, “Analysis on the Study of QoS-Aware Web Services Discovery”, JOURNAL OF COMPUTING, Dec 2009
[11] Jian Wang, Member, IEEE, Panpan Gao, Yutao Ma, Member, IEEE, Kequing He, Senior Member, IEEE and Patrick C.K. Hung, Member, IEEE “A Web Service Discovery Approach Based on Common Topic Groups Extraction” 2016
[12] Shrija Madhu, Deptof CSE, GIET “An Approach to Analyze suicidal tendancy in blogs and tweets using Sentimental Analysis”, Internationa Journal of Scientific Research in Computer Science and Engineering, Vol 6, Issue 4, pp-34-36, 2018
[13] Yogesh Pant, Dept of CIS, HSET, SRHU, “A Novel Approcah to Minimize DFA State Machine Using Linked List”, Internationa Journal of Scientific Research in Computer Science and Engineering, Vol 6, Issue 4, pp-41-55, 2018
[14] S.G. Kamble, K.T. Jadhao, Dept. of ETE, ARIET, “CSI Based Key Generation Technique”, Internationa Journal of Scientific Research in Network Security and Communication, Vol 5, Issue 2, 2017
[15] G. Kant, V. Gogate, V. Kotak, Dept. of Electronics, SAKEC, Mumbai, “Li-Fi Need of 21st Century”, Internationa Journal of Scientific Research in Network Security and Communication, Vol 5, Issue 2, 2017

Rahul P. Mirajkar, Nikhil D. Karande, Surendra Yadav, "A Study on Different Web Service Discovery Approaches," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.311-314, 2018.

An attempt has been made to study the DWT (Discrete Wavelet Transform) based K-Means (KM) clustering and DWT based Fuzzy C-Means (FCM) clustering methods for the segmentation of digital images. The segmentation results of Wavelet KM clustering and Wavelet FCM clustering are compared with the conventional KM clustering and FCM clustering techniques used for the segmentation. The images are split-up into identical areas using KM, FCM, wavelet KM and wavelet FCM algorithms. The algorithms are tested on different image formats available in the literature. The proposed methods are analyzed using discrete wavelet transform (DWT) for enhancing the digital images and various image features like regions, colors and shapes are considered to validate the proposed work. The segmentation results exhibit that the objects in various image clusters of wavelet KM and wavelet FCM performs better as compared to traditional KM and FCM clustering algorithm with respect to CPU execution time, sensitivity analysis, segmentation accuracy and PSNR(Peak Signal to Noise Ratio).

Image segmentation, Clustering, K-Means (KM), Fuzzy C-Means (FCM), Wavelet KM, Wavelet FCM, Discrete Wavelet Transform (DWT), CPU execution time, sensitivity analysis and segmentation accuracy

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A.H.M. Jaffar Iqbal Barbhuiya, K. Hemachandran, "Hybrid Image Segmentation Model using KM, FCM, Wavelet KM and Wavelet FCM Techniques," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.315-323, 2018.

Bioinformatics research is an active area of research that employs DNA microarray technology as a very important tool. Microarray gene expression is acquired through microarray technology in order to monitor the expression of genes under different conditions. Denoising is a major pre-processing step in DNA microarray images. This paper proposes a new spatial denoising technique in spatial domain for DNA microarray image. The method exploits Markov Random Field (MRF) model to reduce the noise in microarray images. Two algorithms developed in this work are Denoising using MRF (DMRF) and Determination of Optimized Values (DOV).Different experimental results and analysis demonstrate the performance of the proposed method with existing methods using various performance metrics.

Spatial Filtering, Markov Random Field, Energy function, Non-linear Optimization, Performance Metrics

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Priya Nandihal, Vandana S.Bhat, Jagadeesh D. Pujari, "Markov Random Field Based Model In Spatial Domain for Denoising of Microarray Images," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.324-328, 2018.

This paper proposes a novel technique, based on distributional approaches with distance measure, i.e. Chernoff distance measure. Since the proposed system is automatic retrieval, it is difficult to understand the nature of the query and target images and which distribution they follow. The Chernoff distance measure overcome this problem, because it adapts itself accordingly the nature of the images, viz. the Chernoff distance could be adapted though the query and target images do no distributed to Gaussian or mixed or even if they are distribution free. This is the main advantage of the proposed technique. In order to examine the proposed technique, an image database is constructed, which contains variety of images such as texture, structure, blurred, noise, artifacts images and their features.

Color Image, Retrival, Chernoff Distance Measure

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S.Selvaraj, K. Seetharaman, "Color Image Retrieval Based on Chernoff Distance Measure," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.329-333, 2018.

The shared wireless medium, wireless networks are vulnerable to jamming attacks. These types of attacks can easily be accomplished by an adversary by either bypassing MAC layer protocol or by emitting RF signals. The failure of data transmission in internet of things is due to corruption of packets by jammers. In existing no of defense techniques have been proposed in recent years to deal with these jammer attacks. However, each defense technique is suitable for only a limited network range and consumption energy. The propose jamming detection algorithm based on two problem solving, first one is to improve the energy efficient routing based on power allocation and second one avoids the jamming node using ecliptic curve cryptography to route the secure packet between source to destination. The simulation result shows the better throughput and delay minimization compare with existing routing algorithms.

IoT, Wi-Fi Sensor devices, Energy routing, Security, Jamming node, Power allocation

[1] L. Hu, H. Wen, B. Wu, J. Tang, and F. Pan, “Adaptive secure transmission for physical layer security in cooperative wireless networks,” IEEE Commun. Lett., vol. 21, no. 3, pp. 524–527, Mar. 2017.
[2] A. Behnad, M. B. Shahbaz, T. J. Willink, and X. Wang, “Statistical analysis and minimization of security vulnerability region in amplify-and-forward cooperative systems,” IEEE Trans. Wireless Commun., vol. 16, no. 4, pp. 2534–2547, Apr. 2017.
[3] Q. Xu, P. Ren, H. Song, and Q. Du, “Security enhancement for IoT communications exposed to eavesdroppers with uncertain locations,” IEEE Access, vol. 4, pp. 2840–2853, 2016
[4] X. Hu, P. Mu, B. Wang, and Z. Li, “On the secrecy rate maximization with uncoordinated cooperative jamming by single-antenna helpers,” IEEE Trans. Veh. Technol., vol. 66, no. 5, pp. 4457–4462, May 2017.
[5] P. Mu, X. Hu, B. Wang, and Z. Li, “Secrecy rate maximization with uncoordinated cooperative jamming by single-antenna helpers under secrecy outage probability constraint,” IEEE Commun. Lett., vol. 19,no. 12, pp. 2174–2177, Dec. 2015.
[6] L. Hu, B. Wu, J. Tang, F. Pan, and H. Wen, “Outage constrained secrecy rate maximization using artificial-noise aided beamforming and cooperative jamming,” in Proc. IEEE ICC, Kuala Lumpur, Malaysia, May 2016, pp. 1–5.
[7] H.-M. Wang, F. Liu, and M. Yang, “Joint cooperative beamforming, jamming, and power allocation to secure AF relay systems,” IEEE Trans. Veh. Technol., vol. 64, no. 10, pp. 4893–4898, Oct. 2015.
[8] Y. Zhang, Y. Shen, H. Wang, J. Yong, and X. Jiang, “On secure wireless communications for IoT under eavesdropper collusion,” IEEE Trans. Autom. Sci. Eng., vol. 13, no. 3, pp. 1281–1293, Jul. 2016.
[9] J. Mo, M. Tao, and Y. Liu, “Relay placement for physical layer security: A secure connection perspective,” IEEE Commun. Lett., vol. 16, no. 6, pp. 878-881, Jun. 2012.
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[11] J. Chen, R. Zhang, L. Song, Z. Han, and B. Jiao, “Joint relay and jammer selection for secure two-way relay networks,” IEEE Trans. Inf. Forensics Security, vol. 7, no. 1, pp. 310-320, Feb. 2012.
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[13] Y. Zou, X.Wang, andW. Shen, “Optimal relay selection for physical-layer security in cooperative wireless networks,” IEEE J. Sel. Areas Commun., vol. 31, no. 10, pp. 2099-2111, Oct. 2013.
[14] A. Mukherjee, S. A. A. Fakoorian, J. Huang, and A. L. Swindlehurst, “Principles of physical layer security in multiuser wireless networks: A survey,” IEEE Commun. Surveys Tuts., vol. 16, no. 3, pp. 1550-1573, Aug. 2014.
[15] Y. Zhang, Y. Shen, H. Wang, J. Yong, and X. Jiang, “On secure wireless communications for IoT under eavesdropper collusion,” IEEE Trans. Autom. Sci. Eng., vol. PP, no. 99, pp. 1-13, Dec. 2015.

E. Selvi, K. Renuka, "An Efficient Jamming Node Avoid Secure Routing In Internet of Things," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.334-341, 2018.

This study evaluates research output on Gout carried out in different parts of the world during 1970–2017 using different bibliometric indicators. Data have been downloaded from Scopus database for the period 1970–2017 using the keywords Gout in the title and abstract fields. The study examined the pattern of growth of the output, its geographical distribution. The study Gout research output is gradually increasing. The USA, followed by the UK and German contributed the highest number of papers. The majority of the prolific institutions were located in the USA, the UK, France and Australia. The last two decades have witnessed considerable growth in research output in this field. Interestingly, the countries like the USA, the UK and Australia

Gout research, Bibliometric analysis, Research output on Gout, Gout Disease

[1]. Almind, T.C. and Ingwersen, P. (1997). Informatic analysis on the World Wide Web, Methodological approaches to “Webometrics”. Journal of Documentation, 53(4): 404-426.
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[3]. Pritchard, A. (1969). Statistical Bibliography or Bibliometrics? Journal of Documentation, 25(4), 348-349.
[4]. Rahman, M., Haque, T.L., and Fukui, T. (2005). Research articles published in clinical radiology journals: Trend of contribution from different countries, Academic Radiology, 12(7), 825-829.
[5]. Rajendran, P., Ramesh Babu, B, and Gopalakrishnan, S. (2005). Bibliometric analysis of “Fiber Optics” literature. Annals of Library and Information Studies, 52(3), 82-85
[6]. Nagarajan, M (2016) ‘Scientrometric Analysis of Research output in Science in Tamil Nadu Universities’. Journal of Advances in Library and Information Science, Vol.5, No.4, 348-352.

S. Manimekalai, M. Nagarajan, "Literature Output on Gout: A Bibliographic Study," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.342-348, 2018.

Video and video types are changing day by day; due to which, video processing is becoming complex time to time. There is a lack of particular algorithm for automatic detection and tracking of human faces in video, to overcome the challenges that are being faced nowadays. This paper describes a model for detection and tracking of human faces in different background video sequence using OpenCV platform. Both positive and negative image samples are trained and saved as xml file. With the help of trained samples, LBPH algorithm clarifies whether the video frame contain faces or not. Further, HOG descriptor is fed to SVM detector to compute the coefficients that are stored in the xml file. Based on this, face regions are tracked until the last frame is reached. We have tested our proposed algorithm on the videos of a technically challenging dataset. Standard metrics helped to judge the success of the proposed algorithm. Test results indicate the superiority of our proposed model, compared to other similar algorithms.

Detection, Tracking of human faces, Different background, Video sequence, OpenCV, LBPH, HOG, SVM

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[19] M. Kim, S. Kumar, V. Pavlovic, H. Rowley, “Face Tracking and Recognition with Visual Constraints in Real-World Videos”, in the Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1-8, 2008.
[20] Ranganatha S, Y P Gowramma, “Development of Robust Multiple Face Tracking Algorithm and Novel Performance Evaluation Metrics for Different Background Video Sequences”, International Journal of Intelligent Systems and Applications, Vol.10, Issue.8, pp.19-35, 2018.
[21] Stefan Leutenegger, Margarita Chli, Roland Y. Siegwart, “BRISK: Binary Robust Invariant Scalable Keypoints”, in the Proceedings of the IEEE International Conference on Computer Vision, pp.2548-2555, 2011.
[22] Ranganatha S, Y P Gowramma, “Eigen and HOG Features Algorithm for Face Tracking in Different Background Challenging Video Sequences”, International Journal of Computing, in press.
[23] Ranganatha S, Y P Gowramma, “Image Training, Corner and FAST Features based Algorithm for Face Tracking in Low Resolution Different Background Challenging Video Sequences”, International Journal of Image, Graphics and Signal Processing Vol.10, Issue.8, pp.39-53, 2018.
[24] E. Rosten, T. Drummond, “Fusing Points and Lines for High Performance Tracking”, in the Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp.1508-1515, 2005.
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[28] Ranganatha S, Y P Gowramma, “Selected Single Face Tracking in Technically Challenging Different Background Video Sequences Using Combined Features”, ICTACT Journal on Image and Video Processing, in press.
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[35] Li Fei-Fei, R. Fergus, P. Perona, “Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories”, in the Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2004.
[36] Li Fei-Fei, R. Fergus, P. Perona, “One-Shot Learning of Object Categories”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.28, Issue.4, pp.594-611, 2006.
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Ranganatha S, Y P Gowramma, "Image Training and LBPH Based Algorithm for Face Tracking in Different Background Video Sequence," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.349-354, 2018.

Sandhi is a technique in which joining of two or more words happens. Sandhi viccheda means splitting of word or sentences into its constituents. Languages like Hindi, Urdu, Marathi, Kannada, and Malayalam are used to implement the sandhi viccheda concept. Sanskrit is a language in which rules are used to form a word. These rules play an important role in sandhi viccheda process. So, to split the word or sentence rules are used in the system. As everyone knows BHAGWAT GEETA is a religious book which contains more complex words, sentences, which user can’t understand. The proposed system uses those words, sentences from BHAGWAT GEETA for splitting purpose. For this, rules of sandhi viccheda like (vowels, consonant, and visarga) are used. The representation of the splits is shown using the directed acyclic graph to get a number of possible outputs.

Sandhi splitting, lexical analysis, rules, sandhi viccheda algorithm, DAG

[1] Rupali Deshmukh and Varunakshi Bhojane, “Building Vowel Sandhi Viccheda System for Sanskrit”, International Journal of Innovations and Advancement in Computer Science, Vol. 4, December 2015.
[2] Mrs. Namrata Tapaswi, Dr. Suresh Jain and Mrs. Vaishali Chourey, “Parsing Sanskrit Sentences Using Lexical Functional Grammar”, Proceedings of the International Conference on Systems and Informatics, IEEE, pp 2636-2640, 2012.
[3] Priyanka Gupta, Vishal Goyal, “Implementation of Rule-Based Algorithm for Sandhi-Viccheda of Compound Hindi Words”, IJCSI International Journal of Computer Science Issues, Vol. 3, 2009.
[4] Joshi Shripad S., “Sandhi Splitting of Marathi Compound Words”, International Journal on Advanced Computer Theory and Engineering (IJACTE), Vol. 2, no. 02, 2012.
[5] Latha R. Nair, S. David Peter, “Development of a Rule-Based Learning System for Splitting Compound Words in Malayalam Language”, Proceedings of the Recent Advances in Intelligent Computational Systems, IEEE, pp 751-755, 2011.
[6] Devadath V V, Litton J Kurisinkel, Dipti Misra Sharma, and Vasudeva Varma, “A Sandhi Splitter for Malayalam”, Proceedings of the 11th International Conference on Natural Language Processing, 2014.
[7] M. Rajani Shree, Sowmya Lakshmi, “A novel approach to Sandhi splitting at Character level for Kannada Language”, Proceedings of the 2016 International Conference on Computational Systems and Information Systems for Sustainable Solutions, IEEE, pp 17-20, 2016.
[8] Sachin Kumar, “Sandhi Splitter and Analyzer for Sanskrit”, With Special Reference to aC Sandhi, Special Centre for Sanskrit Studies, Jawaharlal Nehru University, New Delhi, 2007.
[9] Shubham Bhardwaj, Neelamadhav Gantayat, Nikhil Chaturvedi, Rahul Garg, Sumeet Agarwal, “SandhiKosh: A Benchmark Corpus for Evaluating Sanskrit Sandhi Tools”, Language Resources and Evaluation Conference, 2018.
[10] Amba Kulkarni, Sheetal Pokar and Devanand Shukl, “Designing a Constraint-Based Parser for Sanskrit”, Proceedings of the International Sanskrit Computational Linguistics Symposium, SpringerLink, vol. 6465, pp 70-90, 2010.
[11] Vaishali Gupta, Nisheeth Joshi, Iti Mathur, “Rule-Based Stemmer in Urdu”, Proceedings of the 2013 4th International Conference on Computer and Communication Technology, IEEE, pp 129-132, 2013.
[12] Anil Kumar, V.Sheebasudheer, Amba Kulkarni, “Sanskrit Compound Paraphrase Generator”, Proceedings of the ICON, 2009.
[13] Pawan Goyal, Vipul Arora, and Laxmidhar Behera, “Analysis of Sanskrit Text: parsing and Semantic Nets”, Springerlink, Proceedings of the Sanskrit Computational Linguistics, Vol. 5402, pp 200-218, 2009.
[14] Bhagyashree D. Patil and Manoj E. Patil, “A Review on Implementation of Sandhi Viccheda for Sanskrit Words”, Proceedings of the International Conference in ICGTETM, IJCRT, vol.5, no. 12, pp 489-493, December 2017.

Bhagyashree Patil, Manoj Patil, "Implementation of Sandhi Viccheda for Sanskrit Words/Sentences/Paragraphs," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.355-360, 2018.

Location aided routing is an emerging approach in mobile ad-hoc networks. Location based routing propagates the packet toward the destination on the basis of location information of transmitting node and destination node. Many algorithms are devised to forward the packet in location based environment among them greedy forwarding is simplest one. In this a transmitting node forwards the packet to next node which is closer to destination than itself. Most forwarding within r and nearest within forwarding progress are the examples of greedy forwarding. With the simple and straight forward method greedy forwarding may suffers from local maxima problem where a node itself is closest to destination, therefore unable to construct the path nevertheless it exist. Many solutions were made to encounter the local maxima problem but suffers with other problem such as packet looping. In this work an efficient solution to local maxima “back tracking with exclusion” is proposed and compared with existing solutions.

local maxima, Greedy forwarding, adhoc network, Styling, mobile node

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Prashant Dixit, Anuradha Pillai, Rahul Rishi, "Back tracking with exclusion: A solution for local maxima problem in greedy location based packet forwarding for MANETs," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.361-364, 2018.