Volume-4 , Issue-7 , Jul - 2016 Go Back

Web based applications play a major role in people day to day activities. Monitoring the users actions are really an interesting and necessary job of the website forecaster to familiarize about their performance, classify the likeminded users, understand the website visitor’s browsing history, reconstruct the website, web recommendation and web personalization. Web logs are the main source to provide sufficient information about the users and achieve the above requirements. Pattern discovery algorithms are applied to the web logs to extract the desirable information. It is mandatory for website analyst to understand the user behavior and interest for many analytical purposes. Web logs take an important role to know about the user behavior. Several pattern mining techniques were developed to understand the user behavior. But, there are no special preprocessing techniques to identify the user interest level and understand their browsing patterns. A special kind of preprocessing technique is needed to improve the quality and efficiency of the pattern mining algorithms. The proposed preprocessing technique performs the preprocessing activities on web logs and also identifies the similar kind of users. The user similarity helps for efficient web page recommendation technique.

Web logs; Preprocessing; Data Cleaning; User Identification; Session Identification; Web page recommendation

[1] Chhavi, R, 2012, “A Study of Web Usage Mining Research Tool”, International Journal of Advanced Networking and Applications, vol. 3, no. 6, pp. (1422-1429), 2012.
[2] Raju, GT & Sathyanarayana, PS, “Knowledge Discovery from Web Usage Data: Complete Preprocessing Methodology”, International Journal of Computer Science and Network Security, vol. 8, no.1, pp.(179-186), 2008.
[3] Sanjay, BT & Sangram, ZG, “An Effective and Complete Preprocessing for Web Usage Mining”, International Journal on Computer Science and Engineering, vol. 2, no. 3, pp. (848-851), 2010.
[4] Srivastava, J, Desikan, P & Kumar, V, “Web Mining - Concepts, Applications and Research Directions”, AHPCRC Technical Report, pp. (51-70), 2003.
[5] Ramya, C & Shreedhara, KS, “Clustering of Web Users using ART1 NN based Clustering Approach with a Complete Preprocessing Methodology”, International Journal of Emerging Technology and Advanced Engineering, vol. 2, no. 1, pp. (71-77), 2012.
[6] Sheetal, AR & Shailendra, J, “Efficient Preprocessing Technique using Web Log Mining”, International Journal of Advancements in Research & Technology, vol. 1, no. 6, pp.(418-422), 2012.
[7] Malarvizhi, M & Sahaaya, AM, “Preprocessing of Educational Institution Web Log Data for Finding Frequent Patterns using Weighted Association Rule Mining Technique”, European Journal of Scientific Research, vol. 74, no. 4, pp. (617-633), 2012.
[8] Cooley, R, “Web Usage Mining: Discovery and Application of Interesting Patterns from Web Data”, Ph.D. thesis, University of Minnesota, 2000.
[9] Chitraa, V & Antony, SD, “A Novel Technique for Sessions Identification in Web Usage Mining Preprocessing”, International Journal of Computer Applications, vol. 34, no. 9, pp. (78-83), 2011.
[10] Tasawar, H, Sohail, A & Nayyer, M, “Web Usage Mining: A Survey on Preprocessing of Web Log File”, IEEE Conference on Information and Emerging Technologies, pp. (1-6), 2010.
[11] Mohd, HW, Mohd, NM, Hafizul, FH, Mohamad, F & Mohamad, M , “Data Pre-processing on Web Server Logs for Generalized Association Rules Mining Algorithm”, Proceedings of World Academy of Science, Engineering and Technology, vol. 36, pp. (970-977), 2010.
[12] Vijayashri, L & Madhuri, J, “Data Preprocessing in Web Usage Mining”, Proceeding in International Conference on Artificial Intelligence and Embedded Systems, pp. (1-5), 2012.
[13] Suguna, R & Sharmila, D, “User Interest Level based Preprocessing Algorithms using Web Usage Mining”, International Journal of Computer Science and Engineering (IJCSE), vol. 5, no. 9, pp. (815-822), 2013.

R. Suguna, "Enhanced User Interest Level Preprocessing Technique for Efficient Web Page Recommendation," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.66-71, 2016.

In this paper we are studied cloud computing techniques. The Homomorphic property of various cryptosystems can be used to create secure voting systems, collision-resistant hash functions, and private information retrieval schemes and enable widespread use of cloud computing by ensuring the confidentiality of processed data.

Encryptions, security, compression, validate data integrity

[1] Ahmed DheyaaBasha, Irfan Naufal Umar, and Merza Abbas, Member, IACSIT “Mobile Applications as Cloud Computing: Implementation and Challenge”, 2011 IEEE International Conference on Cloud Computing and Intelligence Systems, pp 467 – 471, 2013.
[2] Alabbadi, M.M “Cloud computing for education and learning: Education and learning as a service (ELaaS)”, IEEE Conf. on Interactive Collaborative Learning (ICL), vol.134 , PP 589 – 594, 2011.
[3] Cong Wang, Qian Wang, Kui Ren and Wenjing Lou “Ensuring Data Storage Security in Cloud Computing”, IEEE conf. on Parallel Distributed and Grid Computing (PDGC), pp.1-9, 2009.
[4] Farzad Sabahi, “Cloud Computing Security Threats and Responses”, IEEE Trans. on Cloud Computing., vol. 11, no. 6, pp. 670 - 684, 2002.
[5] Gaurav Raj, Dheerendra Singh, Abhay Bansal, “Load balancing for resource provisioning using Batch Mode Heuristic Priority in Round Robin (PBRR) Scheduling”, Confluence 2013: The Next Generation Information Technology Summit (4th International Conference), pp. 308 – 314, 2012.
[6] Jianfeng Yang, Zhibin Chen “Cloud Computing Research and Security Issues” Computational Intelligence and Software Engineering (CiSE), Vol. 978-1-4244-5392, pp 1 – 3, 2010.
[7] Jaber, A.N. “Use of cryptography in cloud computing”, IEEE Control System, Computing and Engineering (ICCSCE), PP 179 – 184, 2013.
[8] Kalagiakos, P. Karampelas, P “Cloud computing learning” IEEE Application of Information and Communication Technologies (AICT), pp. 1 – 4, 2011.
[9] Mehmet Yildiz, Jemal Abawajy, Tuncay Ercan and Andrew Bernoth “A Layered Security Approach for Cloud Computing Infrastructure” 2009 10th International Symposium on Pervasive Systems, pp 763 – 767, 2009.
[10] Md. Imrul Kayeset al. “Test Case Prioritization for Regression Testing Based on Fault Dependency” 2009 10th International Symposium on Pervasive Systems,pp.3-11, 2013
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[12] Sravan Kumar R, AshutoshSaxena “Data Integrity Proofs in Cloud Storage”, 2011 Third International Conference on Communication Systems and Networks, Vol. 978-0-7695-4355,pp.03/11, 2011.
[13] Qiang Guan, Chi-Chen Chiu, Song Fu “A Cloud Dependability Analysis Framework for Characterizing System Dependability in Cloud Computing Infrastructures”IEEE International Conference on Dependable Computing, pp. 11 – 20, 2012.
[14] RuWei Huang, Si Yu, Wei Zhuang and Xiao Lin Gui, “Design of Privacy-Preserving Cloud Storage Framework" IEEE Ninth International Conference on Grid and Cloud Computing, pp. 128 – 132,2010,
[15] RuWei Huang, Si Yu, Wei Zhuang and Xiao Lin Gui, “Research on Privacy-Preserving Cloud Storage Framework Supporting Cipher text Retrieval"IEEE Ninth International Conference on Grid and Cloud Computing,pp.6-10,2011.
[16] Ranjita Mishra, Sanjit Kumar Dash “A Privacy Preserving Repository for Securing Data across the Cloud” IEEE International Conference, Vol 978-1-4244-8679, pp.6-10, 2011.
[17] Ryan K. L. Ko, Markus Kirch berg, Bu Sung Lee “From System-centric to Data-centric Logging –Accountability, Trust & Security in Cloud Computing” IEEE International Conference on Computer Society,pp. 1 – 4, 2011.
[18] Sang-Ho Na, Jun-Young Park, Eui-Nam Huh “Personal Cloud Computing Security Framework” IEEE Asia-Pacific Services Computing Conference,pp. 671 - 675 ,2010.
[19] Shucheng Yu, CongWang, Kui Ren and Wenjing Lou “Achieving Secure, Scalable, and Fine-grained Data Access Control in Cloud Computing” at IEEE INFOCOM ,pp. 1 - 9 ,2010.
[20] Sravan Kumar R, AshutoshSaxena “Data Integrity Proofs in Cloud Storage” IEEE International Conference on Communication Systems and Networks,Vol. 978-0-7695-4355,pp. 1 – 4, 2011.
[21] Sheikh, F.B., Haider, S., “Security threats in cloud computing”, IEEE International Conference Internet Technology and Secured Transactions, pp.214 – 219, 2011.
[22] Sabahi, F., Shahrekord, “Cloud computing security threats and responses”, IEEE International Conference on Communication Software and Networks, pp.245 – 249, 2011.
[23] Uma Somani, “Implementing Digital Signature with RSA Encryption Algorithm to Enhance the Data Security of Cloud in Cloud Computing," IEEE 1st International Conference on Parallel, Distributed and Grid Computing,pp.234-238 ,2010.
[24] Victor Echeverr´ıa, Lorie M. Liebrock, and Dongwan Shin “Permission Management System: Permission as a Service in Cloud Computing” IEEE Computer Software and Applications Conference Workshops,pp. 371 – 375, 2010.
[25] Wang En Dong “Oriented Monitoring Model of Cloud Computing Resources Availability”, IEEE International Conference on Computational and Information Sciences, vol. 13874396, pp.1537 – 1540, 2013.
[26] Wentao Liu, Wuhan Poly tech., “Research on cloud computing security problem and strategy”, IEEE International Conference on Consumer Electronics, Communications and Networks, pp.1216 – 1219, 2012.
[27] Xiao Zhang, Hong-tao Du ,Jian-quan Chen, Yi Lin, Lei-jie Zeng “Ensure Data Security in Cloud Storage” IEEE International Conference on Network Computing and Information Security vol.978-0-7695-4355pp.284-287,2011.

Gurbachan Singh, Khushboo Bansal, "A Result Base Various Approaches of Data Security in Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.72-75, 2016.

Vehicular Ad-Hoc Networks are growing field of research. In this network most promising task is provide safety or other application to driver and passenger. It became key component of transportation. In this paper different routing protocol like AODV, DSR and M-DART are studied. At the end of paper outcomes of these protocols are discussed.

AODV; VANET; DSR RREQ; RREP.; M-DART

[1] Chaoyi Bian, Tong Zhao, Xiaoming Li, Wei Yan, “Boosting Named Data Networking For Data Dissemination In Urban VANET Scenarios”, Elsevier Vehicular Communications 2 (2015) 195-207.
[1] Rawa Adla, Nizar Al-Holou, Mohannad Murad, Youssef A. Bazzi, “Automotive Collision Avoidance Methodologies”, 978-1-4799-0792-2/13 IEEE, 2013.
[2] Moez Jerbi, Sidi-Mohammed Senouci, Rabah Meraihi and Yacine Ghamri-Doudane, “An Improved Vehicular Ad Hoc Routing Protocol for City Environments”, IEEE ICC 2007.
[3] Tajinder Kaur, A.K Verma, “Simulation and Analysis of AODV routing protocol in VANETs”, IJSCE International Journal of Soft Computing and Engineering ISSN: 2231-2307, vol-2, Issue-3, July 2012.
[4] Evjola Spaho, Makoto Ikeda, Leonard Barolli, Fatos Xhafa, Vladi Kolici and Makoto Takizawa, “Sixth International Conference on Complex, Intelligent and Software Intensive Systems”, 2012.
[5] Narendra Mohan Mittal, Dr. Prem Chand Vashist, “Performance Evaluation of AODV and DSR Routing Protocols for Vehicular Ad-hoc Networks (VANETs)”, International Journal of Emerging Technology and Advanced Engineering, vol-4, Issue-6, June 2014.
[6] Rohit Jain, Ramprasad Kumawat, Sandeep Mandliya, Mukesh Patidar, “Performance evaluation of table driven multipath routing protocols in MANET under varying nodes, Traffic load & Pause time”, International journal of innovative research in electrical, electronics, instrumentations and controlengineering, vol-2, issue-2, February 2014.
[7] Avinash Giri, Jitendra Prithviraj and Ashol Verma, “Analysis of unipath amd multipath routing protocols in MANETs”, nternational journal of smart sensord and adhoc networks(IJSSAN), ISSN NO. 2248-9738, vol-2, Issue-1,2, 2012.

Vaishali Jain, Rajendra Singh Kushwah, "Review of Various VANET Protocols Using NS-2 Simulator," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.76-80, 2016.

This paper proposes an improved method for steganography using reversible texture synthesis. Texture synthesis mechanism is the construction of large texture by using the input texture which is smaller in size. Combination of texture synthesis and steganography can provide better security and high embedding capacity than the existing method. Proposed method use location patch or header block to store the location of the embedded data. In the existing method the secret data was placed in source patches where as in the improved method the secret data is kept in blocks. Length of the embedding message is calculated which determines the required number of blocks needed for placing the message securely.

Texture synthesis, Steganography, patch, Synthetic image, Header block, Data block

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[7] Lexing Ying, Aaron Hertzmann, Henning Biermann, Denis Zorin, Texture and Shape Synthesis on Surfaces, Springer-Verlag London .
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[11] ] Z. Ni, Y.-Q. Shi, N. Ansari, and W. Su, “Reversible data hiding,” IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 3, pp. 354–362.
[12] X. Li, B. Li, B. Yang, and T. Zeng, General framework to histogram shifting-based reversible data hiding, IEEE Trans. Image Process., vol. 22, no. 6, pp. 2181–2191, Jun. 2013 .
[13] Kuo-Chen Wu and Chung-Ming Wang, Member, IEEE,S Steganography Using Reversible Texture Synthesis IEEE Transactions on Image processing Volume 24,January 2015.

Akhila Sreenivas K. and Pretty Babu , "An Approach for Data Hiding Technique Based on Reversible Texture Synthesis," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.81-85, 2016.

In cognitive radio networks (CRN) an efficient spectrum allocation is a very big issues because of its lack of spectrum demand. Resources in CRN should be allocated based on dynamic access methods with respected to sensed radio atmosphere. A primary research challenge is that how should be allocated or assigned available unused spectrum to unlicensed users. The fitting portion of unmoving recurrence range existing together intellectual radios while amplifying all out transmission capacity utilization what's more, minimizing impedance is required for the productive range use in CRN. The technique for settled range portion came about to less range usage over the whole range. In this article we study the different fitting algorithms and present comprehensive analysis of each method used to improve the effective utilization of unused spectrum in CRN.

Cognitive Radio; Energy; OFDM; Resource Allocation; Spectrum sensing

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S.Tamilarasan, P.Kumar, "A Survey on Dynamic Resource Allocation in Cognitive Radio Networks," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.86-93, 2016.

Search-based Software Engineering is use number of software engineering models. In domain Search-Based Software Engineering many application is test data generation. We propose many methods for automating results bottleneck finding using search-based input-sensitive application profiling. Our key idea is to use a genetic algorithm as a search heuristic for obtaining combinations of input functions values that maximizes number of function to represents the elapsed execution time of the application. We present TAO tool is a software testing tool result automated test and oracle generation based on a semantic model. TAO is worked grammar-based test generation with automated semantics evaluation using a denotation semantics framework. The quality of web application is a broad review of recent Web testing advances model and discuss their goals, targets, techniques employed, inputs/outputs and stopping criteria. This research paper presents result testing of web application using reactive-based framework for reducing the cost and increasing efficiency of the performance testing. Finally test case can be generated automatically by solving and modify the problem using evolutionary algorithm. This model is attractive because it take a suite of adaptive automated and semi-automated solutions in situations many large complex problem spaces with multiple competing and conflicting objectives.

Search-based Software Engineering, Evolutionary Algorithms, Optimization Problem, Evolutionary Testing, Heuristic Search Techniques. Web applications, World Wide Web, Web testing, Survey, Performance

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N.Sudheer, V.Sharma and S.Hrushikesava Raju, "A Process Web Application Testing Using TAO Tool Search Based Genetic Algorithm," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.94-100, 2016.

Diabetes Mellitus is one of the real wellbeing challenges everywhere throughout the world. The pervasiveness of diabetes is expanding at a quick pace, falling apart human, financial and social fabric. Aversion and expectation of diabetes mellitus is progressively picking up enthusiasm for social insurance group. Albeit a few clinical choice emotionally supportive networks have been commended that fuse a few information digging methods for diabetes forecast and course of movement. These ordinary frameworks are ordinarily based either just on a solitary classifier or a plain mix thereof. As of late broad attempts are being made for enhancing the exactness of such frameworks utilizing gathering classifiers. This study takes after the procedures utilizing random forest tree as a base learner alongside standalone information mining procedure scaled conjugate gradient to characterize patients with diabetes mellitus utilizing diabetes hazard variables. This characterization is done crosswise over three diverse ordinal grown-ups bunches in PIMA indian dataset. Test result demonstrates that, general execution of adaboost group strategy is superior to anything sacking and in addition standalone random forest tree.

Diabetes Mellitus, Random Forest Tree, Classification, Prediction,Scaled Conjugate Gradient

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Neha Shukla, Meena Arora, "Prediction of Diabetes Using Neural Network & Random Forest Tree," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.101-104, 2016.

In this paper we are studied cloud computing techniques. The Homomorphic property of various cryptosystems can be used to create secure voting systems, collision-resistant hash functions, and private information retrieval schemes and enable widespread use of cloud computing by ensuring the confidentiality of processed data.

job scheduling, Directed Acyclic Graph, implement Min-Min, Shortest Job First.

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Charanjeet Singh, Khushboo Bansal, "A Result Base on Various Approaches of Load Balancing in Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.105-110, 2016.

This paper focuses on SAN protocols and their various topologies, protocol layers, addresses. This article gives the description of rules and regulation of SAN that work in networks of storage. This study paper deals with the study of SAN and DAS, how they work in the open industrial network. This paper surveys on protocols and their working in storage. DAS have SATA, SCSI and SAN have uses FC, FCOE protocols.

Department of Computer Engineering, Bharati Vidyapeeth University, Pune, India

[1] Raval, K.S., Suryawanshi, R.S., Naveenkumar, J. and Thakore, D.M., 2011. The Anatomy of a Small-Scale Document Search Engine Tool: Incorporating a new Ranking Algorithm. International Journal of Engineering Science and Technology, 1(3), pp.5802-5808.
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Ashutosh Kumar Singh, "A Study on Merits and Demerits of SAN Protocols," International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.111-114, 2016.

This study paper revolves around the impact of virtualization at the various layers of storage stack. There is a rapid growth in the storage capacity, and hence the processing power in the respective enterprises storage appliances coupled with the requirements for high availability and it needs a Storage Area Network (SAN) architecture for providing the storage and performance elements here. The Storage Virtualization provides us with a combination and management of storage resources for Storage Area Network with multiple servers as well as the storage devices. The main aim for storage virtualization is its necessity to be inexpensive and not affect the performance. Currently, the storage virtualization is displayed at three different architectural levels: (1) the storage device, (2) the host and (3) the SAN fabric hardware as a central management unit. This paper further provides us with more information on the storage virtualization levels that are part of its architecture. Each of these levels that we will see grants us with particular advantages and benefits but is also limited in their capabilities gets considered as their drawbacks or limitations.

Storage, Performance, Virtualization, Network, Storage Virtualization, Storage Area Network (SAN), Network, Attached Storage (NAS), Server, Storage Device (Sub-System), Host, SAN Fabric, Virtual Machine Monitor/ Hypervisor

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[30] Naveenkumar J, Makwana R, Joshi S.D and Thakore D.M, Offloading Compression and Decompression Logic Closer to Video Files Using Remote Procedure Call, Journal Impact Factor, 6(3), pp.37-45, 2015.
[31] Naveenkumar J, Makwana R, Joshi S.D and Thakore D.M, Performance Impact Analysis of Application Implemented on Active Storage Framework. International Journal, 5(2), 2015.
[32] Salunkhe R, Kadam A.D, Jayakumar N and Thakore D, In Search of a Scalable File System State-of-the-art File Systems Review and Map view of new Scalable File system.
[33] Salunkhe R, Kadam A.D, Jayakumar N and Joshi S.D, Luster A Scalable Architecture File System: A Research Implementation on Active Storage Array Framework with Luster File System.
[34] Jayakumar N, Reducts and Discretization Concepts, tools for Predicting Student’s Performance.
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