Volume-5 , Issue-4 , Aug 2017, ISSN 2320-7639 (Online) Go Back

• Open Access   Article

  Dynamic Load Balancing Algorithms for Heterogeneous Web Server Clusters

  Deepti Sharma, Vijay B. Aggarwal

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.4 , pp.56-59, Aug-2017

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Today, the World Wide Web is growing at an increasing rate and occupied a big percentage of the traffic in the Internet. These systems lead to overloaded and congested proxy servers. Load Balancing and Clustering of web servers helps in balancing this load among various web servers. In this paper we have given solution for load balancing Clustering using three different algorithms and frameworks. The objective of this paper is to enhance the execution time of a server, increasing reliability and optimizing the system performance. These are achieved through simulations on the proposed methods.

  Key-Words / Index Term
  Dynamic Load Balancing, Cluster System, load sharing, web traces

  References
  [1] S.Sharma Sandeep, S.Singh and M. Sharma,“Performance Analysis of Load Balancing Algorithms”, World Academy of Science, Engineering and Technology, 2008.
  [2] N. Nehra, R.B. Patel, and V.K. Bhat, “A Framework for Distributed Dynamic Load Balancing in Heterogeneous Cluster”, Journal of Computer Science vol. 3, Issue 1, pp. 14-24, ISSN 1549-3636, 2007.
  [3] Helen D. Karatza and Ralph C. Hilzer, “Load Sharing In Heterogeneous Distributed Systems”, Proceedings of 34th Winter Simulation Conference (WSC’02), ISBN:0-7803-7615-3, 2002.
  [4] J. P. Andrew and J. Thomas Naughton, “Framework for task scheduling in heterogeneous distributed computing using genetic algorithms”, Artificial Intelligence Review, Volume 24, Issue 3, pp 415-429, 2005.
  [5] Kun-Ming V. Yu, and Chih-Hsun Chou “A Fuzzy-Based Dynamic Load-Balancing Algorithm”, JITAS, Vol 2, Issue 4, 2004.
  [6] Z. Lan, V. E. Taylor and G. Bryan, “Dynamic Load Balancing of SAMR Applications on Distributed Systems”, Supercomputing, ACM/IEEE Conference, 2001.
  [7] F. Bonomi, “On job assignment for a parallel system of processor sharing queues”, IEEE Transactions on computers, 39(7), 858-869, 1990.
  [8] E. Bachmat and H. Sarfati, "Analysis of SITA policies”, Performance Evaluation, 67(2), 102-120, 2010.
  [9] A. Riska et al, ”ADAPTLOAD: effective balancing in clustered web servers under transient load conditions”, In Distributed Computing Systems, Proceedings. 22nd International Conference (pp. 104-111), IEEE, 2002
  [10] A. Luis and B. Azer, “Load balancing a cluster of web servers”, In Proceedings of IEEE International Conference on Performance, Computing, and Communications Conference (IPCCC‟ 00), 2000.
  [11]Crescenzi, P., Gambosi, G., Nicosia, G., Penna, P., & Unger, W., “On-line load balancing made simple: Greedy strikes back”, Journal of Discrete Algorithms, Vol 5, Issue 1, pp. 162-175, 2007
  [12]Niu, Y., Chen, H., Hsu, F., Wang, Y. M., & Ma, M. A Quantitative Study of Forum Spamming Using Context-based Analysis, In NDSS, 2007
  [13] A. Garg, “A Framework to Optimize Load Balancing to Improve the Performance of Distributed Systems”, International Journal of Computer Applications, Volume 122 – No.15, pp. 24-27, July 2015.
  [14] I. Psaras and L. Mamatas , “On demand connectivity sharing: Queuing management and load balancing for user provided networks”, Computer Networks, Vol. 55, Issue 2,pp. 399-414, 2011.
  [15] Md. A.M. Ibrahim, "Cluster of heterogeneous computers: Using mobile agents for improving load balance", International Journal of Science and Technology Education Research, Vol 1, Issue 7, pp. 143-146, 2010.
  [16] Archana B. Saxena, Deepti Sharma, “Framework for threshold based centralized load balancing policy for heterogeneous systems”, published in an International Research Journal “Oriental Journal of Computer Science and Technology” (OJCST), Vol. 4, Issue 1, pp.99-105 (2011) ISSN: 0974-6471, May 2011.
  

  Citation
  Deepti Sharma, Vijay B. Aggarwal, "Dynamic Load Balancing Algorithms for Heterogeneous Web Server Clusters," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.4, pp.56-59, 2017

• Open Access   Article

  Study and Overview of Anti-Trespasser

  Jayendra S Jadhav

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.4 , pp.60-62, Aug-2017

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  In current scenario, security systems remain generic with limited authentication abilities. Existence of such security methods for primary purpose is legitimate. With the growing technology and emergence of malicious people around, it may be possible to break barriers. Safety of one’s precious data is primary concern. This project proposes a security mechanism to enhance the level of security for every individual. The application tries to leverage individual’s presence to be a key to access virtual area. The system requires mobile device with Bluetooth functionality, which is coupled with principle device that you need to secure. The Project aims to tightly couple security mechanism with the operating system allowing it to take final steps to maintain privacy of data.

  Key-Words / Index Term
  Bluetooth; Piconet; Ad hoc; Trespasser;Mobile

  References
  [1] Esteban Alcorn, Bluetooth Architecture Overview”, Microsoft Windows Embedded Compact 7, Published: March 2011, https://www.ieee.org/documents/ieeecitationref.pdf
  [2] S.K. Kenue and J.F. Greenleaf, “Limited angle multifrequency diffiaction tomography,” IEEE Trans. Sonics Ultrason., vol. SU-29, no. 6, pp. 213-2 17, July 1982. www.techterms.com/definition/manet
  [3] C. Brusaw, C. Aired, and W. Oliu, Handbook of Technical Writing, 3rd ed. New York: St. Martin’s Press, 1987. [Online]. Retrieved on- December 2016 Available: http://softsprogrammer.blogspot.com/2014/04/lock-folder
  [4] G. J. Broadhead, “Style in technical and scientific writing.” In M.G. Moran and D. Joumet, eds. Research in Technical Communication. A Bibliographic Sourcebook, pp. 379-401. Westport. CT: Greenwood Press, 1985.
  [5] M. M. Botvinnik, Computers in Chess: Solving Inexact Search Problems. Translated by A. Brown, Berlin: Springer-Verlap, 1984. http://www.cs.wustl.edu/~jain/cis788-97/ftp/ip_security
  [6] Smart Handheld Group, Hewlett-Packard Company, Bluetooth Technology Overview[Online]. Retrieved on: October 2016 Available:(http://inpressco.com/wp-content/uploads/2015/02/Paper71397-400.pdf)
  [7] Securing Computer Folders using Bluetoothand Rijndael Encryption [Online].Retrieved on - December 2016 Available: (http://inpressco.com/wp-content/uploads/2015/02/Paper71397-400.pdf)
  [8] Securing ComputerDeviceUsing Bluetoothtechnology, Retrieved on- December 2016, [Online]. Available: (http://www.ijecs.in/issue/v4-i4/60%20ijecs.pdf)
  [9] Wankhade S.B., Damani A.G., Desai S.J., Khanapure A .V., “An Innovative Approach to File Security using Bluetooth”, Mumbai, Maharashtra, IJSET, Vol. 02, Issue No. 5, pp:417-223
  

  Citation
  Jayendra S Jadhav, "Study and Overview of Anti-Trespasser," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.4, pp.60-62, 2017

• Open Access   Article

  Smart Lighting for Better Health

  Anil Z. Chhangani, Dickson Arulraj, Divya Panchal, Neha Singh

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.4 , pp.63-65, Aug-2017

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Humans evolved to live according to rhythms of the sun. Human respond physically and mentally to the light around us. Today, we live in a world in which our sleep/wake cycles are easily disrupted. Human often feel groggy in the morning, lethargic during the day, and restless at night. Our bodies respond to light direction, color, intensity, and time, releasing hormones that control our body processes - physiology, sleep, metabolism, behavior, and mood. In our system, human can wake up naturally with sunrise-like lighting ,Increase focus and productivity with energizing blue-rich light ,detect if human need rest or need to sleep than human can relax with sunset-like amber lighting and sleep better at night. By doing this human can improve health: manage weight, reduce stress, increase antioxidant levels, and boost immune system

  Key-Words / Index Term
  Sunrise-like lighting, human health, automated sleeping pattern, Android Application, Wireless Technology

  References
  [1] Zohra Aziz Ali Manjiyani, Renju Thomas Jacob, Keerthan Kumar R, Babu Varghese. 2014. Development of MEMS Based 3-Axis Accelerometer for Hand Movement Monitoring
  [2] Anil K. Jain,Jianjiang Feng, Karthik Nandakumar. 2010. Fingerprint Matching
  [3] Cheah Wai Zhao, Jayanand Jegatheesan. 2015. Exploring IOT Application Using Raspberry Pi
  [4] Lutz Prechelt. 2000. An empirical comparison of C, C++, Java, Perl, Python, Rexx, and Tcl.
  [5] Li Ma, Lie Gu, Jin Wang. 2014. Research and Development of Mobile application for Android Platform
  [6] Hoyt Koepke. 2010. Why Python Rocks for Research
  [7] Harshada Chaudhari .2015. Raspberry Pi Technology: A Review
  [8] Ms. Sejal V. Gawande, Dr. Prashant R. Deshmukh. 2015. Raspberry Pi Technology,
  [9] Mary Carskadon, Thomas Roth .2000. An olescent sleep needs and patterns.
  [10] Kimm Fesenmaier. 2015. Caltech Team Produces Squeezed Light Using a Silicon Micromechanical System
  

  Citation
  Anil Z. Chhangani, Dickson Arulraj, Divya Panchal, Neha Singh, "Smart Lighting for Better Health," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.4, pp.63-65, 2017

• Open Access   Article

  Proposed Authentication Model for Location Based Queries

  Roshan S. Deshmukh, D.G. Harkut

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.4 , pp.66-69, Aug-2017

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  the popularity of location-based services leads to serious concerns on user privacy. It is very easy for a person to know his/her location with the help of devices having GPS facility. When user’s location is provided to Location Based Services (LBS), it is possible for user to know all location dependent information like location of friends or Nearest Restaurant, whether or traffic conditions. The massive use of mobile devices paves the way for the creation of wireless networks that can be used to exchange information. When the exchange of information is done amongst entrusted parties, the privacy of the user could be in harmful. Existing protocol doesn’t work on many different mobile devices and another issue is that, Location Server (LS) should provide misleading data to user. This gives rise to new challenges and reconsideration of the existing privacy metrics.

  Key-Words / Index Term
  Location Based Services, Location Server, Path Confusion, Private Information Retrieval, K-anonymity

  References
  [1] A. Beresford and F. Stajano, “Location privacy in pervasive comput,”IEEE Pervasive Computing., vol. 2, no. 1, pp. 46–55, Jan.–Mar.2003.
  [2] B. Palanisamy and L. Liu, “MobiMix: Protecting location privacy with mix-zones over road networks,” in Proc. ICDE, Hannover, Germany, pp. 494–505, 2011.
  [3] C. Bettini, X. Wang, and S. Jajodia, “Protecting privacy against location-based personal identification,” in Proc. 2nd VDLB Int. Conf. SDM, W. Jonker and M. Petkovic, Eds., Trondheim, Norway, pp. 185–199, LNCS 3674, 2005.
  [4] B. Gedik and L. Liu, “Location privacy in mobile systems: A personalized anonymization model,” in Proc. ICDCS, Columbus, OH, USA, pp. 620–629, 2005.
  [5] M. Gruteser and D. Grunwald, “Anonymous usage of location based services through spatial and temporal cloaking,” in Proc.1st Int. Conf. MobiSys, pp. 31–42, 2003.
  [6] L. Sweeney, “k-Anonymity: A model for protecting privacy,” Int. J. Uncertain. Fuzziness Knowl. Based Syst., vol. 10, no. 5, pp. 557–570, Oct. 2002.
  [7] S. Mascetti and C. Bettini, “A comparison of spatial generalization algorithms for lbs privacy preservation,” in Proc. Int. Mobile Data Manage., Mannheim, Germany, pp. 258–262, 2007.
  [8] M. F. Mokbel, C.-Y. Chow, and W. G. Aref, “The new Casper: Query processing for location services without compromising privacy,” in Proc. VLDB, Seoul, Korea, pp. 763–774, 2006.
  [9] L. Marconi, R. Pietro, B. Crispo, and M. Conti, “Time warp: How time affects privacy in LBSs,” in Proc. ICICS, Barcelona, Spain, pp. 325–339, 2010.
  [10] T. Xu and Y. Cai, “Feeling-based location privacy protection for location-based services,” in Proc. 16th ACM CCS, Chicago, IL,USA, pp. 348–357, 2009.
  [11] X. Chen and J. Pang, “Measuring query privacy in location-based services,” in Proc. 2nd ACM CODASPY, San Antonio, TX, USA, pp. 49–60, 2012.
  [12] B. Hoh and M. Gruteser, “Protecting location privacy through path confusion,” in Proc. 1st Int. Conf. SecureComm, pp. 194–205, 2005.
  [13] P. Kalnis, G. Ghinita, K. Mouratidis, and D. Papadias, “Preventing location-based identity inference in anonymous spatial queries,” IEEE Trans. Knowl. Data Eng., vol. 19, no. 12, pp. 1719–1733, Dec. 2007.
  [14] M. Damiani, E. Bertino, and C. Silvestri, “The PROBE framework for the personalized cloaking of private locations,” Trans. Data Privacy, vol. 3, no. 2, pp. 123–148, 2010.
  [15] T. Hashem and L. Kulik, “Safeguarding location privacy in wireless ad-hoc networks,” in Proc. 9th Int. Conf. UbiComp, Innsbruck, Austria, pp. 372–390, 2007.
  [16] M. Duckham and L. Kulik, “A formal model of obfuscation and negotiation for location privacy,” in Proc. 3rd Int. Conf. Pervasive Comput., H. Gellersen, R. Want, and A. Schmidt, Eds., pp. 243–251, LNCS 3468, 2005.
  [17] H. Kido, Y. Yanagisawa, and T. Satoh, “An anonymous communication technique using dummies for location-based services,” in Proc. Int. Conf. ICPS, pp. 88–97, 2005.
  [18] J. Krumm, “A survey of computational location privacy,” Pers. Ubiquitous Comput., vol. 13, no. 6, pp. 391–399, Aug. 2009.
  [19] G. Ghinita, P. Kalnis, A. Khoshgozaran, C. Shahabi, and K.-L. Tan, “Private queries in location based services: Anonymizers are not necessary,” in Proc. ACM SIGMOD, Vancouver, BC, Canada, pp. 121–132, 2008.
  [20] B. Chor, E. Kushilevitz, O. Goldreich, and M. Sudan, “Private information retrieval,” J. ACM, vol. 45, no. 6, pp. 965–981, 1998.
  [21] E. Kushilevitz and R. Ostrovsky, “Replication is not needed: Single database, computationally-private information retrieval,” in Proc. FOCS, Miami Beach, FL, USA, pp. 364–373, 1997.
  [22] G. Ghinita, P. Kalnis, M. Kantarcioglu, and E. Bertino, “A hybrid technique for private location-based queries with database protection,” in Proc. Adv. Spatial Temporal Databases, N. Mamoulis, T. Seidl, T. Pedersen, K. Torp, and I. Assent, Eds., Aalborg, Denmark, pp. 98–116, LNCS 5644, 2009.
  [23] G. Ghinita, P. Kalnis, M. Kantarcioglu, and E. Bertino, “Approximate and exact hybrid algorithms for private nearest-neighbor queries with database protection,” GeoInformatica, vol. 15, no. 14, pp. 1–28, 2010.
  [24] P. Paillier, “Public-key cryptosystems based on composite degree residuosity classes,” in Proc. EUROCRYPT, vol. 1592, Prague, Czech Republic, pp. 223–238, 1999.
  

  Citation
  Roshan S. Deshmukh, D.G. Harkut, "Proposed Authentication Model for Location Based Queries," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.4, pp.66-69, 2017

• Open Access   Article

  USB-Privacy: Security To Software Using USB

  Hemangi R. Patil, Snehal A. Nawale, Jayshree R. Sanap, Chandrashekhar M. Raut

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.4 , pp.70-72, Aug-2017

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  The general way of providing a security to any software or application, is, a key verification. If we share this key and try to use the software on different machines. . We can create the copies of the software. This is basically known as a `piracy`. To prevent such a illegal activities, there are many security applications present in the market nowadays. But piracy prevention can be achieved by simply making it machine specific. The software is provided with USB-drive which is when connected check for the valid machine and allow using the software only on the valid machine. This paper will explain the concept in detail.

  Key-Words / Index Term
  USB (Universal Serial Bus), Machine Specific, Dongle, Piracy, Vendor

  References
  [1] Cryptographic primitives. “handbook of applied cryptography” by menezes
  [2] Modern cryptosystems .Jwezy Wojdylo.September 21, 2001.Cryptography, jerzy wojdylo, 9/21/01. Overview of Classical cryptography.
  [3] Public-key cryptography processor, ieee j.Solid-state cir-cuits, vol. …Rsa and ecc Crypto processor.”
  [4] Kryptonite-A Programmable Crypto processor
  [5] Paul C. Van Oorschot Alfred J. Menezes and Scott A.Vanstone,Handbook of applied cryptography, CRC presses Inc., Florida, 1996.
  [6] Bruce schneier, applied cryptography (2nd ed.), johnwiley and sons, inc., New York, 1996.
  

  Citation
  Hemangi R. Patil, Snehal A. Nawale, Jayshree R. Sanap, Chandrashekhar M. Raut, "USB-Privacy: Security To Software Using USB," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.4, pp.70-72, 2017

• Open Access   Article

  Voice Based E-Mail System for Blind People

  Dhanashree.D.Zope, Pooja.B.Nevewani, Pooja.G.Teje, Husrat Parveen

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.4 , pp.73-75, Aug-2017

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Thevisually challenged people find it very difficult to access the technology because of the fact that using them requires visual perception. Even though many new advancements have been implemented to help them use the computers efficiently no naïve user who is visually challenged can use this technology as efficiently as a normal naïve user can do that. Unlike normal users they require some practice for using the available technologies.This application aims at developing an email system that will help even a visually impaired person to use the services for communication without prior training. This system will also reduce cognitive load taken by blind to rememberand type characters using keyboard. The system will be keyboard independent and will work only on mouse operation and speech recognition. The system is completely based on interactive voice response (IVR) which will make it user friendly and efficient to use.

  Key-Words / Index Term
  Independent,Voice Mail, Interactive voice response (IVR), Automatic Speech Recognition (ASR), Text to speech(TTS)

  References
  [1] JagtapNilesh, Pawan Alai, Chavhan Swapnil and BendreM.R.. “Voice Based System in Desktop and Mobile Devices for Blind People”. In International Journal of Emerging Technology and Advanced Engineering (IJETAE), 2014 on Pages 404-407 (Volume 4, issue 2).
  [2] UmmuhanysifaU.,NizarBanu P K , “Voice Based Search Engine and Web page Reader”. In Internationa Journal of Computational Engineering Research (IJCER). Pages 1-5.
  [3] G. Shoba, G. Anusha, V. Jeevitha, R. Shanmathi. “AN Interactive Email for Visually Impaired”. In International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), 2014 on Pages 5089-5092.(Volume 3, Issue 1).
  [4] T. Dasgupta and A. Basu. A speech enabled indian language text to braille transliteration system. In Information and Communication Technologies and Development (ICTD), 2009 International Conference
  [5] R. Ghose, T. Dasgupta, and A. Basu. Architecture of a web browser for visually handicapped people. In Students’ Technology Symposium (TechSym), 2010 IEEE, pages 325 –329, april 2010
  [6] T. Lauwers, D. Dewey, N. Kalra, T. Stepleton, and M.B. Dias. Iterative design of a braille writing tutor to combat illiteracy. In Information and Communication Technologies and Development, 2007. ICTD 2007. International Conference on, pages 1–8. IEEE,2007.
  

  Citation
  Dhanashree.D.Zope, Pooja.B.Nevewani, Pooja.G.Teje, Husrat Parveen , "Voice Based E-Mail System for Blind People," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.4, pp.73-75, 2017

• Open Access   Article

  Enhanced Query Processing Technique Using RASP Effective Services in Cloud

  N. Deshai, P. Penchala Swamy, G.P. Saradhi Varma

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.4 , pp.76-78, Aug-2017

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Cloud computing is an emerging technology, Privacy and confidentiality has become the major concern in the public cloud. Data owners do not want to move their data to the cloud until and unless the confidentiality and the query privacy are preserved. On the other hand a secured query services should provide efficient query processing and reduce the in-house workload to get the total benefit of cloud computing. This paper presents a Random space perturbation method to provide secure and efficient range query and K nearest neighbor query services for protecting data in the cloud. The RASP data perturbation method combines order preserving encryption, dimensionality expansion, random noise injection, and random projection, to provide strong resilience to attacks on the perturbed data and queries.The kNN-R algorithm is designed to work with the RASP range query algorithm to process the kNN queries.

  Key-Words / Index Term
  Privacy, Confidentiality, Range, query, KNN Privacy

  References
  [1] N. Cao, C. Wang, M. Li, K. Ren, and W. Lou, “Privacy preserving multi-keyword ranked search over encrypted cloud data,” in INFOCOMM, 2011.
  [2] Huiqi Xu, Shumin Geo, Keke Chen, ”Building confidential and Efficient Query services in the Cloud with RASP Data Parturbation” IEEE Transaction on knowledge and data Engineering vol:26 no:2,2014.
  [3] M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. K. andAndy Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, “Above the clouds: A berkeley view of cloud computing,” Technical Report, University of Berkerley, 2009.
  [4] H. Hacigumus, B. Iyer, C. Li, and S. Mehrotra, “Executing sql over encrypted data in the database-service-provider model,” in Proceedings of ACM SIGMOD Conference, 2002.
  [5] R. Agrawal, J. Kiernan, R. Srikant, and Y. Xu, “Order preserving encryption for numeric data,” in Proceedings of ACM SIGMOD Conference, 2004.
  [6] B. Chor, E. Kushilevitz, O. Goldreich, and M. Sudan, “Private information retrieval,” ACM Computer Survey, vol. 45, no. 6, pp. 965–981, 1998.
  [7] B. Hore, S. Mehrotra, and G. Tsudik, “A privacy-preserving index for range queries,” in Proceedings of Very Large Databases Conference (VLDB), 2004.
  [8] J. Bau and J. C. Mitchell, “Security modeling and analysis,” IEEE Security and Privacy, vol. 9, no. 3, pp. 18–25, 2011.
  [9] K. Chen, L. Liu, and G. Sun, “Towards attack-resilient geometric data perturbation,” in SIAM Data Mining Conference, 2007.
  [10] M. F. Mokbel, C. yin Chow, and W. G. Aref, “The new casper: Query processing for location services without Compromising privacy,” in Proceedings of Very Large Databases Conference (VLDB), 2006, pp. 763–774.
  [11] B. Chor, E. Kushilevitz, O. Goldreich, and M. Sudan, “Private information retrieval,” ACM Computer Survey, vol. 45, no. 6, pp. 965–981, 1998.
  [12] H. Hacigumus, B. Iyer, C. Li, and S. Mehrotra, “Executing sql over encrypted data in the database-service-provider model,” in Proceedings of ACM SIGMOD Conference, 2002.
  

  Citation
  N. Deshai, P. Penchala Swamy, G.P. Saradhi Varma, "Enhanced Query Processing Technique Using RASP Effective Services in Cloud," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.4, pp.76-78, 2017

• Open Access   Article

  Effectiveness Of Ssaha Algorithm For Searching Motif In Large Databases Of Dna Sequences

  Khumukcham Robindro, Ashoke Das

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.4 , pp.79-87, Aug-2017

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Motif finding has become a very significant area of study in the post genomic era because of its various applications and usage in the bioinformatics research. The volume of the biological data is also on the ever increasing trend. Many algorithms have been proposed for efficient motif findings. In this paper, an approach is proposed to use a fast search method called SSAHA for motif finding. SSAHA is an efficient algorithm which effectively searches a given query in large databases containing multiple gigabases of DNA. In our approach, the effectiveness of SSAHA algorithm in searching large databases of DNA is exploited for searching motif in large databases of DNA sequences.

  Key-Words / Index Term
  Motif, Algorithm, SSAHA, DNA, Database

  References
  [1] Zemin Ning, Anthony J. Cox, and James C. Mullikin (2001) SSAHA: A First Search Method for Large DNA Databases
  [2] Altschul, S.F., Gish, W., Miller, W., Myers, E.W., and Lipman, D.J.(1990). Basic Local Alignment Search Tool. J. Mol. Biol.215: 403–410.
  [3] Altschul, S.F., Madden, T.L., Schäffer, A.A., Zhang, J., Zhang, Z.,Miller, W., and Lipman, D.J. (1997). Gapped BLAST and PSI-BLAST: A new generation of protein database search programs.Nucleic Acids Res. 25: 3389–3402.
  [4] Benson, G. (1999). Tandem Repeats Finder: A program to analyzeDNA sequences. Nucleic Acids Res. 27: 573–580.
  [5] Delcher, A.L., Kasif, S., Fletschmann, R.D., Peterson, J., White, O.,and Salzberg, S. (1999). Alignment of whole genomes. NucleicAcids Res. 27: 2369–2376.
  [6] Gusfield, D. (1997). Algorithms on strings, trees and sequences: Computer science and computational biology. Cambridge University Press,Cambridge, UK.
  [7] Knuth, D.E. (1998). The art of computer programming vol. 3: Sorting and searching. Addison-Wesley, Reading, MA.
  [8] Lipman, D.J. and Pearson, W.R. (1985). Rapid and sensitive protein similarity searches. Science 227: 1435–1441.
  [9] Zhang, Z., Schwartz, S., Wagner, L., and Miller, W. (2000). A greedy algorithm for aligning DNA sequences. J. Comp. Biol. 7: 203–214
  [10] Anjali Mohapatra, P.M. Mishra, S. Padhy (2007): Motif Search in DNA Sequences Using Generalized Suffix Tree, 10th International Conference on Information Technology.
  [11] Elena Zheleva and A.N.Arslan, 2005, Fast motif search in protein sequence database, Department of Computer Science, University of Vermont.
  [12] N. S. Dasari, R. Desh, and Z. M.( 2010) An efficient multicore implementation of planted motif problem. In Proceedings of the International Conference On High Performance Computing and Simulation, pages 9–15.
  [13] Sanguthevar Rajasekaran, Sudha Balla, Chun-His Huang(2004): Exact Algorithms for Planted Motif Problems.Dept. of Computer Science and engineering, University of Connecticut.
  [14] J. Davila, S. Balla, and S. Rajasekaran.( 2007) Fast and practical algorithms for planted (l, d) motif search. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4:544–552 .
  

  Citation
  Khumukcham Robindro, Ashoke Das, "Effectiveness Of Ssaha Algorithm For Searching Motif In Large Databases Of Dna Sequences," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.4, pp.79-87, 2017

• Open Access   Article

  Mining Frequent model Using mass-produced Approach

  Pradeep Chouksey

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.4 , pp.89-94, Aug-2017

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  The World Wide Web has evolved in less than two decades as the major source of data and information for all domains. Web has become today not only an accessible and searchable information source but also one of the most important communication channels, almost a virtual society. Web mining is a challenging activity that aims to discover new, relevant, and reliable information and knowledge by investigating the web structure, its content, and its usage. Though the web mining process is similar to data mining, the techniques, algorithms, and methodologies used to mine the webcontains those specific to data mining, mainly because the web has a great amount of unstructured data and the changes are frequent and rapid. Personalization tools rely on click stream data captured in Web Server logs. The lack of user rating, sparse nature and large volume of data poses serious challenges to standard collaborative filtering techniques in terms of efficiency and performance. Web personalization can be effective if it is based on Association rule discovery from usage data.

  Key-Words / Index Term
  Web Usage Mining, Apriori Algorithm, Collabrative Filtering, Recommendation System

  References
  [1] Mobasher, R. Colley, and J. Srivastava, "Automatic Personalization Based on Web Usage Mining", ACM, volume 48,
  [2] Agrawal R, Srikant R., "Fast Algorithms for Mining Association Rules", VLDB. Sep 12-15 1994, Chile, 487-99, pdf, ISBN 1-55860-153-8.
  [3] Mannila H, Toivonen H, Verkamo A I., "Efficient algorithms for discovering association rules." AAAI Workshop on Knowledge Discovery in Databases (SIGKDD). July 1994, Seattle, 181-92.
  [6] P. Becuzzi, M. Coppola, and M. Vanneschi, ì Mining of Association Rules in Very Large Databases: A Structured Parallel Approach,” Proc. Europar-99, vol. 1685, pp. 1441-1450, Aug. 1999.
  [7] Junjie Chen and Wei Liu, “Research for Web Usage Mining Model”, International Conference on Computational Intelligence for Modeling Control and Automation, and International Conference onIntelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC`06) 0-7695-2731-0/06 ©2006 IEEE
  [8] Olfa Nasraoui, Maha SolimanEsin Saka, Antonio Badia, Member and Richard Germain “A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Sites”, IEEE Transactions On Knowledge And Data Engineering, Vol. 20, No. 2, February 2008
  [9] Sutheera Puntheeranurak, Hidekazu Tsuji, “Mining Web logs for a Personalized Recommender System”, 0-7803-8932-S/05/ 2005 IEEE
  [10] B.Santhosh Kumar, K.V.Rukmani,” Implementation of Web Usage Mining Using Apriori and FP Growth Algorithms”,Int.J.of Advanced Networking and Applications, Volume:01, Issue:06, (2010)
  [11] S.Veeramalai, N.Jaisankar and A.Kannan,” Efficient Web Log Mining Using Enhanced Apriori Algorithm with Hash Tree and Fuzzy”, International journal of computer science & information Technology (IJCSIT) Vol.2, No.4, August 2010
  [12] A.kumar, Dr. P. Thambidurai,” Collaborative web recommendation systems based on an effective fuzzy association rule mining algorithm”, Indian Journal of Computer Science and Engineering Vol1 No 3 184-191
  [13] C-H Lee, Y.H.-Kim, P.-K. Rhee,” Web Personalization expert with combining Collaborative filtering and Association rule mining technique”, Expert systems with Applications 21(2001)
  

  Citation
  Pradeep Chouksey, "Mining Frequent model Using mass-produced Approach," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.4, pp.89-94, 2017