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Cloud computing offers a utility based service by sharing resources for its clients through using Internet. Because of well advantage features, the popularity of such cloud computing growing very rapidly. As a result, power consumption by cloud data center also increase continuously. Data centers consume lot of electrical power that effects indirectly to the carbon dioxide emission in environment. Beside this, there have many other factors which also effect the power consumption of cloud environment-communication equipments which act as a bridge between users to cloud data center, user devices that are also contribute a small amount of consumption in cloud network. This paper offers a theoretical model that brings down the energy by proper maintenance of overall cloud network.

Data center; Energy Consumption; Virtual Machines

[1] Q. Zhang, L. Cheng, R. Boutaba, “Cloud Computing: state of – the-art and research challenges”, Journal of Internet Services and Applications, Vol.1, Issue.1, pp. 7-18, 2010.
[2] A. Jain, M. Mishra, S. K. Peddoju, N. Jain, "Energy efficient computing-green cloud computing," in Energy Efficient Technologies for Sustainability (ICEETS), International Conference on 2013, pp. 978-982, 2013.
[3] J. Koomey, “Estimating Total Power Consumption by Servers in the U.S. and the World”
Analytics Press, 2007.
[4] J. Baliga, Robert W. A. Ayre, K Hinton, Rodney S. Tucker, “Green Cloud Computing: Balancing Energy in Processing, Storage, and Transport” , IEEE, Vol.99, Issue. 1, 2011.
[5] A. Beloglazov, J. Abawajy and R. Buyya, “Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing,” Journal of Future Generation Computer Systems, Vol. 28, Issue 5, pp. 755–768, 2012
[6] A. Dhingra, S. Paul, “A Survey of Energy Efficient Data Centres in a Cloud Computing Environment”, International Journal of Advanced Research in Computer and Communication Engineering, Vol.2, Issue.10, pp. 4033-4041, 2013.
[7] M. Lagwal, N. Bhardwaj, “A Survey On Load Balancing Methods and Algorithms in Cloud Computing”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.4,
pp. 46-51, 2017.
[8] A. M. Aslam, M.kaur, “A Review on Energy Efficient techniques in Green cloud: Open Research Challenges and Issues”, International Journal of Scientific Research in Computer Sciences and Engineering, Vol.6, Issue.3, pp. 44-50, 2018.
[9] T. Agarwal, N. Sharma, “Efficient Load Balancing Using Restful Web Services in Cloud Computing: A Review”, International Journal of Scientific Research in Computer Sciences and Engineering, Vol.6, Issue.3, pp. 67-70, 2018

Arjun Ghosh, "Theoretical Model for Energy Efficient Cloud Network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.708-711, 2018.

In digital world, there is a drastic increase of the websites that encouraged users to give their reviews on products, services, policies. This task of different data gathering and analysis of review is known as Opinion Mining. It analyses the text written in a natural language and classify them as positive or negative based on the human’s sentiments, emotions, opinions expressed on any product. Nowadays user reviews and comments are very important for further evaluating and making decision for new products or policies. This gave the chance to spammers to spread malicious reviews with a target to misguide users. Spam is the unwanted similar content flooded on the internet. There is a need to detect spam efficiently. This work focused on training words and finding out whether further sentences are spam or not spam to improve accuracy. This paper discuss and implements naive bayes classifier to detect spam reviews.

Opinion mining, naive bayes, spam

[1] Sharma K, Jatana N, "Bayesian Spam Classification: Time Efficient Radix Encoded Fragmented Database Approach". IEEE 2014 pp. 939-942.
[2] Sandeep Negi, Rekha, "A Review on Different Spam Detection Approaches" International Journal of Engineering Trends and Technology (IJETT) – Volume 11 Number 6 - May 2014.
[3] P.Kalarani, Dr.S. Selva Brunda, "An Overview on Research Challenges in Opinion Mining and Sentiment Analysis" International Journal of Innovative Research in Computer and Communication Engineering (An ISO 3297: 2007 Certified Organization) Vol. 3, Issue 10, October 2015.
[4] Nidhi R. Sharma , Prof. Vidya D. Chitre, "Opinion Mining, Analysis and its Challenges" International Journal of Innovations & Advancement in Computer Science IJIACS ISSN 2347 – 8616 Volume 3, Issue 1 April 2014.
[5] Ayesha Rashid, Naveed Anwer, Dr. Muddaser Iqbal, Dr. Muhammad Sher, "A Survey Paper:Areas, Techniques and Challenges of Opinion Mining" International Journal of Computer Science Issues, Vol. 10, Issue 6, No 2, November 2013.
[6] Ali M. et al, "Multiple Classifications for Detecting Spam email by Novel Consultation Algorithm" CCECE 2014, IEEE 2014, pp. 1-5.
[7] Jindal Nitin, Liu Bing, "Opinion spam and analysis" Proceedings of the 2008 International Conference on Web Search and Data Mining. New York: ACM Press , 2008:219-230.
[8] Xie Sihong, WANG Guan, LIN Shuyang, et al, "Review spam detection via temporal pattern discovery" Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery And Data Mining. New York: ACM Press , 2012:823-831.

[9] Jindal Nitin, Liu Bing, Lim Ee-peng, et al, "Finding unusual review patterns using unexpected rules" Proceedings of the 19th ACM International Conference on Information and Knowledge Management. New York: ACM Press , 2010:1549-1552.
[10] Lim Ee-Peng, Nguyen Viet-An, Jindal Nitin, et al, "Detecting product review spammers using rating behaviors" Proceedings of the 19th ACM international conference on Information and knowledge management. New York: ACM Press , 2010:939-948.
[11] Nasira Perveen, Malik M. Saad Missen, Qaisar Rasool, Nadeem Akhtar, "Sentiment Based Twitter Spam Detection" (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 7, No. 7, 2016.
[12] Swati N. Manke, Nitin Shivale, "A Review on: Opinion Mining and Sentiment Analysis based on Natural Language Processing" International Journal of Computer Applications (0975 – 8887) Volume 109 – No. 4, January 2015.
[13] Anchal, Abhilash Sharma, "SMS Spam Detection Using Neural Network Classifier" International Journal of Advanced Research in Computer Science and Software Engineering Research Paper, Volume 4, Issue 6, June 2014.
[14] Behrouz Minaei-Bidgoli, Saeedeh Sadat Sadidpour, Hossein Shirazi, Nurfadhlina Mohd Sharef, Mohammad Ebrahim Sanjaghi, "Context-Sensitive Opinion Mining using Polarity Patterns" International Journal of Advanced Computer Science and Applications, Vol. 7, No. 9, 2016.
[15] Nidhi Mishra and C K Jha, "Classification of Opinion Mining Techniques" International Journal of Computer Applications 56 (13):1-6, October 2012, Published by Foundation of Computer Science, New York, USA.
[16] Oded Z. Maimon, Lior Rokach, "Data Mining and Knowledge Discovery Handbook" Springer, 2005.
[17] Bo Pang, Lillian Lee, and Shivakumar Vaithyanathan, "Sentiment classification using machine learning techniques." In Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 79–86.
[18] Myle Ott, Yejin Choi, Claire Cardie, et al. Hancock, "Finding deceptive opinion spam by any stretch of the imagination" Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1, 2011: 309-319.
[19] Haseena Rahmath P, "Opinion Mining and Sentiment Analysis - Challenges and Applications" International Journal of Application or Innovation in Engineering & Management (IJAIEM). Volume 3, Issue 5, May 2014.
[20]https://en.wikipedia.org/wiki/Naive_Bayes_classifier
[21] Nikhila Zalpuri, Meena Arora, "An Efficient Model for S.M.S Security and SPAM Detection: A Review", International Journal of Computer Sciences and Engineering, volume - 3, Issue - 12,Dec2015.
[22] S. Nagaparameshwara Chary, B.Rama, "Analysis of Classification Technique Algorithms in Data Mining" International Journal of Computer Sciences and Engineering, volume-4, Issue - 6, june 2016.

Pooja, Komal Kumar Bhatia, "Spam Detection using Naive Bayes Classifier," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.712-716, 2018.

In this paper, we prove some common fixed point theorems for variants of R-weakly commuting mappings in parametric S-metric spaces. Our proved results extend and generalized my known results in the area of fixed point theory. At the end of the paper, we give example to prove the validity of proved results. Our proved results have many applications in area of Non linear programming, fuzziness and intuitionistic fuzziness.

Parametric S-metric space, variants of R-weakly commuting mappings, fixed point

[1] Sedghi S., Shobe N. and Aliouche A., “ A generalization of fixed point theorems in S-metric spaces,” Matematicki Veshik, Vol. 64, Issue 3, pp. 258-266, 2012.
[2] Hieu N.T., Thanh N.T. and Dung N.V., “A generalization of ciric quasi-contraction for maps on S-metric spaces,” Thai journal of Mathematics, Vol. 13, Issue 2, pp. 369-380, 2015.
[3] Rao K.P.R., Babu D.V. and Ramudu E.T., “Some unique common fixed point theorems in parametric S-metric spaces,” International journal of Innovative Research in Science, Engineering and Technology, Vol. 3, Issue. 7, pp.14375-14387, 2014.
[4] Sedghi S. and Dung N.V., “ Fixed point theorems on S-metric spaces,” Matematicki Vesnik, Vol. 66, Issue1, pp. 113-124, 2014.
[5] Sintunavarat W. and Kumam P., “ Common fixed points for R-weakly commuting in fuzzy metric spaces,” Ann. University Ferrara, Vol. 58, pp. 389-406, 2012.
[6] Manro S., Kumar S., Bhatia S.S. and Kang S.M., “Common fixed point theorems of weak reciprocal continuity in metric spaces”, International Journal of Pure and Applied Mathematics, Vol. 88, Issue. 2, pp 297-304, 2013.
[7] Jungck G., “Commuting mappings and fixed points,” Amer. Math. Monthly, Vol.83, pp.261-263, 1976.
[8] Bhajantri L.B., “Fuzzy logic based fault detection in distributed sensor networks”, International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.2, pp.27-32, 2018.
[9] Hussain N., Khaleghizadeh S., Salimi P. and Abdou A.A.N., “A new approach to fixed point results in triangular intuitionistic fuzzy metric spaces,” Abstract and Applied Analysis, Vol. 2014, Article ID 690139, 16 pages, 2014.
[10] Manro S., Bhatia S.S. and Virk S., “A fixed point theorem satisfying general contractive condition of integral type using two pair of converse commuting mappings in metric spaces”, International Journal of Mathematical Archive, Vol. 2, Issue. 10, pp. 2051-2054 2011.
[11] Manro S., “Some common fixed point theorems in complex valued metric spaces using implicit relation”, International Journal of Analysis and Applications, Vol. 2, Issue 1, pp. 62-70, 2013.
[12] Loganathan C. and Lalitha M., “A new approach on solving intuitionistic fuzzy nonlinear programming problem” , International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.5, pp.1-9, 2017.
[13] Kumar S., Dhable S.S. and Potgantwar D., “Optimizes NP Problem with integration of GPU based parallel computing”, Int. J. Sc. Res. in Network Security and Communication, Vol.5 , Issue.3 , pp.61-67, 2017.
[14] Shah D.D. and Selokar M.S., “Introduction of complex laplacian to multi-agent systems”, Int. J. Sc. Res. in Network Security and Communication, Vol.5, Issue.2 , pp.30-36, 2017.

R. Rani, "Fixed-Point Theorems for R-Weakly Commuting Mappings on Parametric S-Metric Spaces," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.717-720, 2018.

Immediately Automatic video analysis from traffic surveillance cameras is a fast-emerging field based on computer vision techniques. It is a key technology to public safety, intelligent transport system (ITS) and for efficient management of traffic. An accurate and efficient tracking capability at the heart of such a system is essential for building higher level vision-based intelligence. Tracking is not a trivial task given the non-deterministic nature of the subjects, their motion, and the image capture process itself. The task of reliably detecting and tracking moving objects in surveillance video, which forms a basis for higher level intelligence applications, has many open questions. In this paper, we present an overview of the state of vehicle detection and tracking techniques and describes the different terminology to produce specification according need of current generation.

Vehicle Detection, Video Surveillance, Object Recognition, Intelligent Traffic, Object Tracking

[1] Matthews, N. D., P. E. An, and C. J. Harris. "Vehicle detection and recognition for autonomous intelligent cruise control", Image. Speech and Intelligent Systems. 1995/ Research 6 Journal (1995).
[2] Suvarna Nandyal and Pushpalata Patil, “Vehicle Detection and Traffic Assessment Using Images”, International Journal of Computer Science and Mobile Computing, IJCSMC, Vol. 2, Issue. 9, September 2013, pp.8 – 17.
[3] Daniel Ponsa, Joan Serrat and Antonio M. Lo´pez, “On-board image-based vehicle detection and tracking”, Transactions of the Institute of Measurement and Control, Volume 33, Issue 7, 2011, pp. 783–805.
[4] Selvanayaki, K.S. and Rm. SomaSundaram, “Hybrid Approach for Detection and Recognition of Vehicles”, Journal of Computer Science, 2015, Volume 11, Issue 2, pp. 304-314.
[5] Raad Ahmed Hadi, Ghazali Sulong and Loay Edwar George, “Vehicle Detection and Tracking Techniques: A Concise Review”, Signal & Image Processing: An International Journal (SIPIJ) Volume 5, No.1, February 2014.
[6] Alper Yilmaz, Omar Javed, and Mubarak Shah. Object tracking: A survey. ACM Computing Surveys (CSUR), 38(4):13, 2006
[7] Bertozzi, Massimo, Alberto Broggi, Massimo Cellario, Alessandra Fascioli, Paolo Lombardi, and Marco Porta, "Artificial vision in road vehicles." Proceedings of the IEEE 90, no. 7 (2002): 1258-1271.
[8] N. Buch, S. A. Velastin, and J. Orwell, A review of computer vision techniques for the analysis of urban traffic. IEEE Transactions on Intelligent Transportation Systems, 12(3):920–939, 2011.
[9] Gupta, R. K. "Object detection and tracking in video image", PhD dissertation 2014.
[10] Ovseník, Ľuboš, Anna Kažimírová Kolesárová, and Ján Turán, "A System for Video Surveillance".
[11] Bojković, Zoran, Dragorad Milovanović, and Andreja Samčović, "Multimedia Communication Systems: Techniques, Standards, and Networks." (2002).
[12] Hannan, Mahammad Abdul, Chew Teik Gee, and Mohammad Saleh Javadi, "Automatic vehicle classification using fast neural network and classical neural network for traffic monitoring", Turkish Journal of Electrical Engineering & Computer Sciences 23, no. Sup. 1 (2015): 2031-2042.
[13] Khalid, Zebbara, Abdenbi Mazoul, and Mohamed El Ansari, "A new vehicle detection method." International Journal of Advanced Computer Science and Applications (IJACSA), Special Issue on Artificial Intelligence 2, no. 8 (2011).
[14] Psyllos, A., Christos-Nikolaos Anagnostopoulos, and Eleftherios Kayafas, "Vehicle model recognition from frontal view image measurements", Computer Standards & Interfaces 33, no. 2 (2011): 142-151.
[15] Kong, Qing-Jie, Lucidus Zhou, Gang Xiong, and Fenghua Zhu, "Automatic road detection for highway surveillance using frequency-domain information", In Service Operations and Logistics, and Informatics (SOLI), 2013 IEEE International Conference on, pp. 24-28, IEEE, 2013.
[16] Chen, Yiling, and GuoFeng Qin, "Video-Based Vehicle Detection And Classification In Challenging Scenarios", International Journal on Smart Sensing & Intelligent Systems 7, Number 3 (2014).
[17] Hargude, Sonali, and S. R. Idate. "i-surveillance: Intelligent surveillance system using background subtraction technique." In Computing Communication Control and automation (ICCUBEA), 2016 International Conference on, pp. 1-5. IEEE, 2016.
[18] Jitendra Oza , Zunnun Narmawala , Sudeep Tanwar, Pradeep Kr Singh ”Public Transport Tracking and its Issues”, International Journal of Computer Sciences and Engineering, Vol. 5, Issue 11, nov 2017

Anshul Vishwakarma, Amit Khare, "Vehicle Detection and Tracking for Traffic Surveillance Applications: A Review Paper," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.721-724, 2018.

Mobile Ad-hoc Network (MANET) is a rapidly changing network having collection of mobile nodes. The connection links between pair nodes are not certain because the nature of changing topology and infrastructure less in MANETs and Thereby there are various issues and restrictions which influence the performance of the network like mobility, overhead, battery drainage, delay and interference.; so MANET is subjected to recurrent link failures that will lead the network to route failure. It is in demand for the routing protocols to decide routes imperishable connectivity supplying persistent data transition without compromising quality of service and load balancing. All the routing protocols are utilized to manage the process of routing through the connection of nodes in the Mobile Ad-Hoc Network. Reactive routing protocols are used, when the source needs to send a packet to destination so the process of searching route will initialize, till it discovers the optimal path. The reactive routing protocols flood in the network for discovering the route of destination and they are not perfect in the term of bandwidth, but the reactive protocols are scalable in the change of network topology. Ad-hoc on-demand distance vector (AODV) and Dynamic routing Protocol (DSR) are reactive routing protocols which predominantly utilized in MANET for making routing resolutions because of their performance in terms of throughput, packet delivery ratio, delay, and number of hops when compared to other protocols, but AODV is shown better performance because it often concentrates to less reliable routes leading to high control overhead and packet loss. In this paper we discuss a general review of modified reactive routing protocol based on optimization algorithms for mobile Ad hoc networks.

MANET, Reactive routing protocols, Optimization techniques

[1] Meenakshi Yadav, Nisha Uparosiya, (2014) “Survey on MANET: Routing Protocols, Advantages, Problems and Security” International Journal of Innovative Computer Science & Engineering Volume 1 Issue 2; Page No. 12-17.
[2] Deepti Badal, Rajendra Singh Kushwah, (2015) “A Energy Efficient Approach to DSR based Routing Protocol for Ad Hoc Network” International Journal of Computer Applications (0975 – 8887) Volume 118 – No. 4.
[3] S. Mueller, R. P. Tsang, and D. Ghosal, Multipath Routing in Mobile Ad Hoc Networks: Issues and Challenges.
[4] Perkins CE, Royer EM, Das SR. (2000) Ad Hoc on Demand Distance Vector (AODV) routing. Available from: http://www.ietf.org/ internetdrafts/draft-ietfmanet-aodv-06.txt, IETF Internet Draft, work in progress,.
[5] Perkins C, Belding-Royer E, Das S, (2003) Ad hoc On-Demand Distance Vector (AODV) routing. Network working group, IETF RFC, RFC 3561.
[6] Gallissot M. Routing on ad hoc networks, Project, Supervisor, Maurice Mitchell Date, 2007.
[7] Mistry N, Jinwala DC, Zaveri M. Improving AODV protocol against black hole attacks. Proceeding of international multiconference of engineers and computer scientists 2010;II.
[8] Jaisankar N, Saravanan R. An extended AODV protocol for multipath routing in MANETs. Int J Eng Technol 2010;2(40).
[9] Nimpal Patel, el at, (2014)“A Survey Paper on Dynamic Source Routing Protocol (DSR) in Ad-Hoc Network”International Journal for Scientific Research & Development| Vol. 2, Issue 10.
[10] Rohini Sharma, (2015) “Proficiency Analysis of AODV, DSR and TORA Ad-hoc Routing Protocols for Energy Holes Problem in Wireless Sensor Networks”, 3rd International Conference on Recent Trends in Computing, Published by Elsevier.
[11] Chrispen Mafirabadza, el at, (2015), “Comparative Analysis of AODV and DSR Scalability In MANET” IEEE International Conference on Communication Networks.
[12] Kamaldeep Kaur, Lokesh Pawar, (2015) “Review of Various Optimization techniques in MANET Routing Protocols”, International Journal of Science, Engineering and Technology Research (IJSETR), Volume 4, Issue 8.
[13] S. Corson, J. Macker., “Mobile Ad hoc Networking (MANET): Routing Protocol Performance Issues and Evaluation Considerations,” IETF RFC2501, 1999.
[14] David B. Johnson, el at, (2004) “The Dynamic Source Routing for Mobile Ad Hoc Wireless Networks.
[15] AM Abdel-Moniem, et al “(2010) an Ant Colony Optimization Algorithm for the Mobile Ad Hoc Network Routing Problem Based on AODV Protocol” 10th International Conference on Intelligent Systems Design and Applications,IEEE.
[16] Nadilma C. V. N. Pereira (2012) “Improving AODV Route Recovery Mechanisms with Connectivity and Particle Swarm Optimization” Journal Of Communications And Information Systems, VOL. 1, NO. 27.
[17] Richa Kalucha et al, (2014) “ ABC_AODV: Artificial Bee Colony Based Aodv Routing In Manet” nternational Journal of Computer Science and Mobile Computing, Vol.3 Issue.8.
[18] Jinil Persis Devarajan, et al (2015 ) “Modified AODV routing protocol for MANET using firefly algorithm” International Journal of Applied Engineering Research10 (34):27176-27182.
[19] Hua Yang, et al (2016)“A Genetic-Algorithm-Based Optimized AODV Routing Protocol” 4th International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 18-20, Hong Kong, China.
[20] Hong Tang, et al (2016)” Research on AODV Routing Protocol based on Improved Genetic Algorithm and Ant Colony Algorithm” IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 3 Issue 5.
[21] Subhrapratim Nath, et al, (2016) “Optimizing MANET routing in AODV : An Hybridization approach of ACO and Firefly Algorithm” second international conference on research in computational intelligence and communication network,IEEE.
[22] Clodomir J. Santana Jr, et al,, (2017) “Improving AODV Routing Protocol For Mobile Ad-HocNetworks Using Swarm-Based Algorithms” University of Pernambuco, Recife-PE, Brazil.
[23] Prasath. N, et al () “AFSA DSR- Artificial Fish Swarm Algorithm Dynamic Source Routing Protocol For MANET”Emerging Technologies in Networking and Security (ETNS), Vol. 7 , 9 , 394-403.
[24] Mustafa Tareq, el at. (2017) “Mobile Ad Hoc Network Energy Cost Algorithm Based on Artificial Bee Colony” Wireless Communications and Mobile Computing, Wiley.
[25] N. Prasath, (2018) “Optimized dynamic source routing protocol for MANETs” published in Springer.

Sulaiman A.M Ghaleb, V. Vasanthi, "An Empirical Study of Reactive Routing Protocols Based Optimization Techniques for MANET," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.725-730, 2018.

Big data analytics in security involves the ability to gather massive amounts of digital information to analyze, visualize and draw insights that can make it possible to predict and stop cyber attacks. Along with security technologies, it gives us stronger cyber defence posture. They allow organizations to recognize patterns of activity that represent network threats. In this paper, we focus on how Big Data can improve information security best practices.

Big Data, Cyber Security, Privacy, Database

[1] CLOUD SECURITY ALLIANCE Big Data Analytics for Security Intelligence
[2] Bryant R, Katz RH, Lazowska ED. Big-data computing: creating revolutionary breakthroughs in commerce, science and society. December 22, 2008, 1-8.
[3] Big Data Analytics for Detection of Frauds in Matrimonial Websites VemulaGeeta et al | International Journal of Computer Science Engineering and Technology (IJCSET) | March 2015 | Vol 5, Issue 3, 57-61
[4] Big Data and Specific Analysis Methods for Insurance Fraud Detection
Ana-Ramona BOLOGA, Razvan BOLOGA, Alexandra FLOREA University of Economic Studies, Bucharest, Romania
[5] Big Data Cyber security Analytics Research Report - Ponemon Institute© Research Report Date: August 2016
[6] Richard A.Derrig,”Insurance Fraud”, The Journal of Risk and Insurance”,2002,Vol.69,No.3,271-287
[7] Bresfelean, Vasile Paul, MihaelaBresfelean, NicolaeGhisoiu, and Calin-Adrian Comes. 2007. "Data Mining Clustering Techniques in Academia." In ICEIS (2), pp. 407-410.
[8] Bresfelean, V. P., Bresfelean, M., Ghisoiu, N., & Comes, C. A. 2008. Determining students’ academic failure profile founded on data mining methods. In Information Technology Interfaces, IEEE, pp. 317-322.
[9]Data electronically available at http://www.ey.com/Publication/vwLUAssets/EY_Big_data:_changing_the_way_businesses_operate/%24FILE/EY-Insights-on-GRC-Big-data.pdf

Ashish Bajpai, Dayanand, Arushi Arya, "Big Data Analytics in Cyber Security," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.731-734, 2018.

As the espousal pace of Web Service technology has increased, so does the requirement for efficient Web Service development such as competent mechanism for discovery, monitoring, and composition etc. are obvious. In our opinion, the efficacy of Web Service development can be achieved only if the potency of two facets i.e. 1) Quality Attributes along with the functional requirements of Web Services and 2) advantages of the foundational architecture of Web Services i.e. Service-Oriented Architecture are recognized at their peak. For Web Services operated over the heterogeneous widespread network, the Quality Attributes are of principal importance, especially, when selecting one service out of many similar services. Till date, several Quality Attribute and their measuring methods have been published in the literature for SOA-based Web Services but none of them have discussed the Quality Attributes, their available different system of measurements, tradeoffs, tools, and standards altogether. Here, this paper presents a Systematic Literature Review on Quality-of-Service for Service-Oriented Architecture-based Web Services by addressing six significant research questions using a fine review protocol. This paper reviews the varied definitions, metrics, issues and challenges, standards and future directions of Quality-of-Service attributes for SOA based Web Services.

Quality Attribute; Quality Metric; Quality-of-Service (QoS); Service-Oriented Architecture (SOA); Web Services

[1] Lewis, G. (2010). Getting Started with Service-Oriented Architecture (SOA) Terminology. Retrieved from http://www.w3c.or.kr/kr-office/TR/2003/NOTE-ws-qos-20031125/.
[2] Newcomer, E., & Lomow, G. (2004). Understanding SOA with web services (independent technology guides). Addison-Wesley Professional.
[3] Haas, H., & Brown, A. (2004, Feburary). Web services glossary. Retrieved from https://www.w3.org/TR/ws-arch/.
[4] International Tele Communication Union (2008). E.800: Definitions of terms related with quality of service. Retrieved from http://www.itu.int/rec/T-REC-E.800-200809-I.
[5] Microsoft (2009). Quality Attributes: Microsoft Application Architecture Guide. Retrieved from https://msdn.microsoft.com/en-us/library/ee658094.aspx.
[6] Kitchenham, B., Brereton, O. P., Budgen, D., Turner, M., Bailey, J., & Linkman, S. (2009). Systematic Literature Reviews in Software Engineering–A Systematic Literature Review. Information and software technology, 51(1), 7-15.
[7] Cruz, R. L. (1995). Quality of Service guarantees in Virtual Circuit Switched Networks. IEEE Journal on Selected areas in Communications, 13(6), 1048-1056.
[8] Le Tien, D., Villin, O., & Bac, C. (2000). CORBA application tailored manager for quality of service support. In Proceedings of the Object-Oriented Real-Time Distributed Computing. Newport, CA:IEEE.
[9] Oriol, M. (2015). Monitoring the Quality of Service to support the Service Based System lifecycle. (Doctoral dissertation). Retrieved from http://upcommons.upc.edu/handle/2117/95669. (Accession Number B 13211-2015)
[10] Angelov, S., & Grefen, P. (2004). The business case for B2B e-contracting. In Proceedings of the Sixth International Conference on Electronic Commerce. Delft, The Netherlands:ACM.
[11] Allenotor, D., & Thulasiram, R. K. (2008). A fuzzy grid-QoS framework for obtaining higher grid resources availability. In Proceedings of the International Conference on Grid and Pervasive Computing. Kunming, China: Springer Berlin Heidelberg.
[12] Ran, S. (2003). A model for web services discovery with QoS. ACM Sigecom exchanges, 4(1), 1-10.
[13] Kaewbanjong, K., & Intakosum, S. (2015). QoS Attributes of Web Services: A Systematic Review and Classification. Journal of Advanced Management Science, 3(3). 194-202.
[14] Mani, A., & Nagarajan, A. (2002). Understanding quality of service for Web services. Retrieved from http://www.ibm.com/developerworks/library/ws-quality/ws-quality-pdf.pdf
[15] Chung, L., & do Prado Leite, J. C. S. (2009). On non-functional requirements in software engineering. In Borgida, A. T., Chaudhri, V. K., Giorgini, P., & Yu, E. S. (Ed.), Conceptual modeling: Foundations and Applications (pp. 363-379). Springer Berlin Heidelberg.
[16] Rajendran, T., & Balasubramanie, P. (2009). Analysis on the study of QoS-aware Web Services discovery. Journal of Computing, 1(1), 119-130.
[17] Makhlughian, M., Hashemi, S. M., Rastegari, Y., & Pejman, E. (2012). Web service Selection based on Ranking of QoS using Associative Classification. International Journal on Web Service Computing, 3(1), 1-14.
[18] Rathore, M., & Suman, U. (2011). Quality of Service Broker Based Process Model for Dynamic Web Service Composition. Journal of Computer Science. 7(8), 1267-1274.
[19] O`Brien, L., Merson, P., & Bass, L. (2007). Quality attributes for service-oriented architectures. In Proceedings of the International Workshop on Systems Development in SOA Environments. Minneapolis, MN:IEEE Computer Society.
[20] Priya, N. H., Priya, A. S., & Chandramathi, S. (2014). QoS based Selection and Composition of Web Services-A Fuzzy Approach. Journal of Computer Science, 10(5), 861-868.
[21] Menascé, D. A. (2002). QoS issues in Web Services. IEEE internet computing, 6(6), 72-75.
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A. Negi, P. Kaur, "A Systematic Literature Review on QoS for SOA-based Web Services," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.735-444, 2018.

This document will propose all features and procedures to develop the system. This paper describes details about objectives, future aspects and its limitations, process-model, minimal requirements, team development, possible risk factors, schedule; and finally, monitoring and reporting mechanisms. On-line Exam System is handful for Institutes to conduct exam, less consuming time that will bring to evaluate the answers and prepare mark sheets. It will help the Institute to testing of students and develop their skills. The effective use of "On-line Exam System", any Educational Organization or training center can use it to edit their features for letting the exams, and for getting better output in less time. This book is for software developers who want to understand why C# is designed the way it is and how to use it Effectively [1]. It doesn’t take long to realize how extremely productive you can be with Visual Studio LightSwitch, regardless of your programming skills [2].

Online Examination, Online Evaluation, ASP.NET Project, C#

[1]. Eric Gunnerson, Nick Wienholt, "A Programmer’s Introduction to C# 5.0", Apress Publisher, United States of America, 2012
[2]. Del Sole, Alessandro, “Microsoft Visual Studio LightSwitch Unleashed”, Sams Publishing, Indiana, 2012
[3][4]. Oleg Sych, “ASP.NET Dynamic Data Unleashed”, Sams Publishing, Indiana, 2012.
[5]. Jonathon Goodyear, Brian Peek, Brad Fox, “Designing Microsoft ASP.NET Applications”, Microsoft Press Publisher,
[6]. Bruce Johnson, “Professional Visual Studio 2012”, Wrox Publisher, 2012
[7]. Ben Albahari, Peter Drayton, Brad Merrill, “C# Essentials, 2nd edition”, O`Reilly Media Publisher, 2nd edition (February 4, 2002)
[8]. V. Maniraj, "Excavating Educational Statistics to Investigate Scholars Performance", International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.461-467, 2018.
[9]. S. Rawat, P. Chaturvedi, "Performance Analysis of QoS Parameters in OFDM Based Network", International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.128-132, 2017

Md. Tanjeem Akhtar, Kazi Arafat, Md. Amir Sohel, "Online Examination System," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.745-749, 2018.

Vehicular Adhoc networks (VANETS) really are an stimulating technology which innovates to allow the communication among vehicles utilizing one side as well as among cars and street area devices on the other side. VANETS provide a large quantity of programs without the help from repaired infrastructure. These programs ahead communicate in a multi-hop fashion. Planning an effective routing method for several VANET programs is extremely hard. In this review on routing protocols based on number of parameters of VANET is an essential topic in vehicle-to- vehicle (V2V) and infrastructure-to- vehicle (IVC) communication. This paper shows the overview of various routing protocols in VANETS as well as main classifications. The protocols are also compared based on their important characteristics and tabulated.

VANETS, Routing Protocols, PBRP, TORA, PRP, DSO and HTRP

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Anita, Sunil Kumar Gupta, Rajeev Kumar Bedi, "Review on Various Routing Protocols in VANETS," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.750-755, 2018.

There are a number of epidemic diseases such as Ebola Virus, Zika Virus, Dengue, Malaria etc that are spreading all over the World. It is necessary to provide awareness about these contiguous diseases to the people. To provide this, a thorough analysis is done on all these diseases and analysis is done on the type of people who effected mostly due to certain climatic conditions and country they are living in. For epidemic diseases analysis, R programming plays a vital role in data science and analysis. Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve complex problems analytically. The "Analysis of Epidemic Diseases" is an application which provides an opportunity for various Countries to estimate the severity of occurrence of various diseases, death counts etc in the coming years on the basis of previous Countries statistics, climatic conditions, death rates, confirmed or suspected cases and so on.

Epidemic, Zika, Dengue, Malaria, Ebola Virus, Analysis, Statistics, Prediction

[1] Pressman RS, “Software Engineering”, McGraw Hill Education, India, pp. 366-398, 2000.
[2] Richard E Fairley, “Software engineering concepts”, McGraw Hill Education, India, pp. 456-520, 2001.
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[5] R. K. Bathla, Jitender Nath Srivastva, “An Ethical Approach of Big Data & Machine Learning Using Innovation of Python”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol.8, Issue.6, pp.1-9, 2018.
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Y. Deepthi, A. Radhika, Ch. Praneeth, "Analysis of Epidemic Diseases Using Big Data Analytics," International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.756-761, 2018.