Volume-2 , Issue-11 , Nov - 2014 Go Back

As the number of data is stored in a database, searching of a relevant data is the important issue in text mining. Though the today’s searching method provides us the relevant data but the numbers of results are too big to find the useful data. The needs of the user vary from time to time and they require different information at every instant of time. Keywords are useful for scanning large documents in a short time. Extracting keywords manually are very difficult and time consuming process. In this paper, we present the technique that are most likely able to satisfy the user’s needs and bring useful data in the top positions by extracting keywords from the data present in the database, scoring those keywords based on their occurrences and ranking the data based on keyword scores.

Extraction,Scores,Text Mining,Page Rank,Clustering,Open Calais

[1] Dilip Kumar Sharma, A. K. Sharma,”A Comparative Analysis of Web Page Ranking Algorithms”, Dilip Kumar Sharma et al. / (IJCSE) International Journal on Computer Science and Engineering Vol. 02,,2010.
[2] Vishal Gupta, Gurpreet S. Lehal,”A Survey of Text Mining Technique and Applications”, Journal of Emerging Technologies in Web Intelligence, Vol. 11, AUGUST 2009.
[3] Namita Gupta,”Text Mining For Information Retrival”, May 2011.
[4] Menaka S, RadhaN,”An Overview of Techniques Used for Extracting Keywords from Documents”, International Journal of Computer Trends and Technology (IJCTT) – volume 4, 7–July 2013.
[5] Min Ye,”Text Mining for Building a Biomedical Knowledge Base on Diseases, Risk Factors, and Symptoms”, 2011.
[6] Roberto De Virgilio ,” Efficient and effective ranking in Top-K exploration for Keyword Search on RDF “ Dipartimento di informatica e automazione universita RomaTre, Rome Italy.

Priyanka Gonnade, Sarika Bongade and Tushar Mendhe, "Information Extraction Using Text Mining by Keyword Ranking and Scoring," International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.50-54, 2014.

Network overload is one of the key challenges in wireless LANs. This goal is typically achieved when the load of access points is balanced. Recent studies on operational WLANs, shown that access point’s load is often uneven distribution i.e. it will be a crucial task to handle the load of overloaded server. To identify such overloaded server many kind of techniques like load balancing have been proposed already. These methods are commonly required proprietary software or hardware at the user side for controlling the user-access point association. In this proposed system we are presenting a new load balancing method by controlling the size of WLAN cells, which is conceptually similar to cell breathing in cellular networks. This method does not require any modification to the users neither the IEEE 802.11 standard. It only requires the ability of dynamically changing the transmission power of the AP beacon messages. We have develop a set of polynomial time algorithms which find the optimal beacon power settings which minimizes the load of the congested access point. We have also considered the problem of network-wide min-max load balancing. Simulation results show that the performance of the proposed method is comparable with or superior to the best existing association-based method.

Load balance in wireless LAN, Power reduction, assign access point assign to Wireless LAN

[1] Y. Bejerano and S.-J. Han, “Cell Breathing Techniques for Load Balancing in Wireless LANs,” Proc. IEEE INFOCOM, 2006.
[2] M. Balazinska and P. Castro, “Characterizing Mobility and Network Usage in a Corporate Wireless Local-Area Network,”Proc. USENIX Int’l Conf. Mobile Systems, Applications, and Services (MobiSys ’03), 2003.
[3] T. Henderson, D. Kotz, and I. Abyzov, “The Changing Usage of a Mature Campus-Wide Wireless Network,” Proc. ACM MobiCom, pp. 187-201, 2004.
[4] T. Togo, I. Yoshii, and R. Kohno, “Dynamic Cell-Size Control According to Geographical Mobile Distribution in a DS/CDMA Cellular System,” Proc. IEEE Personal, Indoor, and Mobile Radio Comm. Symp. (PIMRC ’98), pp. 677-681, 1998.
[5] A. Jalali, “On Cell Breathing in CDMA Networks,” Proc. IEEE Int’l Conf. Comm. (ICC ’98), pp. 985-988, 1998.
[6] I. Papanikos and M. Logothetis, “A Study on Dynamic Load Balance for IEEE 802.11b Wireless LAN,” Proc. Int’l Conf. Comm.Control (COMCON ’01), 2001.
[7] I. Tinnirello and G. Bianchi, “A Simulation Study of Load Balancing Algorithms in Cellular Packet Networks,” Proc. ACM/ IEEE Int’l Workshop Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM ’01), pp. 73-78, 2001.
[8] A. Balachandran, P. Bahl, and G.M. Voelker, “Hot-Spot Congestion Relief and Service Guarantees in Public-Area Wireless Networks,” SIGCOMM Computing Comm. Rev., vol. 32, no. 1, pp. 59-59, 2002.
[9] H. Velayos, V. Aleo, and G. Karlsson, “Load Balancing in Overlapping Wireless LAN Cells,” Proc. IEEE Int’l Conf. Comm. (ICC ’98), 1998.
[10] A. Kumar and V. Kumar, “Optimal Association of Stations and APs in an IEEE 802.11 WAN,” Proc. Nat’l Conf. Comm., 2005.

Rishikesh B. Pansare and I.R.Shaikh, "Min-Max and Limited Knowledge Algorithmic Approach for Load Balancing," International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.50-59, 2014.

This project is aimed at developing an online application for the Training and Placement Dept. Of the college. The system is an online application that can be accessed throughout the organization and outside as with proper login provided. This system can be used application for the TPO of the college to manage the student can be information with regards to placement. Students logging should be able to upload their information in the form of a CV. Visitors/Company representatives logging in may also access/search any information put up by Students.

Generic Technology Keywords, Specific Technology Keywords,Project type Keywords

[1]Hongxin Hu, Member, IEEE, Gail-Joon Ahn, Senior Member, IEEE, and Jan Jorgensen, “Multiparty Access Control for Online Social Networks: Model and Mechanisms”, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
[2] Facebook Beacon, 2007.
[3] T. Zeller, “AOL Executive Quits After Posting of Search Data,” The New York Times, no. 22, http://www.nytimes.com/2006/08/22/technology/22iht aol.2558731.html?pagewanted=all&_r=0, Aug. 2006.
[4] K.M. Heussner, “‘Gaydar’ n Facebook: Can Your FriendsReveal Sexual Orientation?” ABC News, http://abcnews.go.com/Technology/gaydar-facebook-friends/story?id=8633224#.UZ939UqheOs, Sept. 2009.
[5] C. Johnson, “Project Gaydar,” The Boston Globe, Sept. 2009

Mareedu Ramesh, "Development of a feature-rich, practical online application for the Training and Placement Dept. of the college," International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.60-64, 2014.

The Web is a distributed, dynamic, and large information repository. However, a major drawback in this is that the Web contains much human consumable contents. The flaws that can be incurred are the user is ineffectual to incur his archetype data. To achieve an effective utilization of the multiple websites simultaneously, we go for Web services. Though, there are multiple web services available, the user is still inferior to his required data using a methodology called web service composition that facilitates users in accessing their desired services to retrieve their much required information to his need using queries. Genetic algorithms is used to adaptive heuristic search algorithms premised on the evolutionary ideas of natural selection used in solving various computational problems that demands optimization and adaptation to changing environments. Here, we provide access to multiple websites through web services where we can furnish all the required data.

Web Service Composition, Multi Objective Service

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R. Sudha, "Multi Objective Service Selection Using Web Service Composition," International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.65-68, 2014.

A major difficulty of any anomaly-based intrusion detection system is that patterns of normal behavior change over time and the system must be retrained. One of the principal problems of the intrusion detection systems based on the anomaly detection principles is their error rate, both in terms of false negatives (undetected attacks) and false positives, i.e. legitimate traffic labeled as malicious. This problem is amplified by the fact that the sensitivity (and consequently the error rate) varies dynamically as a function of the network traffic. An IDS must be able to adapt to these changes, and be able to distinguish these changes in normal behavior from intrusive behavior. In this paper, we address some of the key issues of detecting intrusion when a potential change occurs in operational environment and learn from the changed environment.

Network Intrusion Detection System (NIDS), Stream Data Mining, Drift Detection, Early Drift Detection Method (EDDM)

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[4] Charu C. Aggarwal, Jiawei Han, Jianyong Wang, and Philip S. Yu. On demand classification of data streams. In Knowledge Discovery and Data Mining, pages 503–508, 2004.
[5] Concept drift - http://en.wikipedia.org/wiki/Concept_drift.
[6] Damon Sotoudeh, Aijun An, “Partial Drift Detection Using a Rule Induction Framework”, CIKM’10 Proceedings of the 19th ACM International Conference on Information and Knowledge Management, Pages 769-778, 2010
[7] Dariusz Brzezinski, “Mining Data Streams with Concept Drift” , Poznan University of Technology, Faculty of Computing Science and Management, Institute of Computing Science,2010.
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Manish Kumar and M. Hanumanthappa, "Self-Learning and Configurable IDS for Dynamic Environment," International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.69-75, 2014.

A simple search over a document can be considered as a traditional method of searching from a single document in database. A keyword or string is considered as core element while searching where string may be strings of words, characters for any phrase. Many problems in such keyword or phrase-based searching arise when a keyword or phrase is intended to be searched in multiple documents. For the same, a solution suggested is a repetitive procedure of searching for every document. It can be helpful for limited number of copies of document. But this solution can never be considered efficient and effective in case of large number of documents in database which is supposed to be increasing continuously. Also, searching for the pattern based or the regular expression based content from the document is one of the demanding topics of research. Processing such queries requires a lot of processing time and complete indexing of data is bit difficult process.

Document retrieval, Indexing, Unstructured Text

[1] Debnath Bhattacharyya, Poulami Das,” Unstructured Document Categorization: A Study”, International Journal of Signal Processing, Image Processing and Pattern Recognition, pp. 55-62,Jan 2008.
[2] Weiguo Fan, ”Tapping into the Power of Text Mining”, article accepted for publication at the Communications of ACM, pp. 02-15, February 16, 2005.
[3] V.V.Jaya Rama Krishnaiah, D.V.Chandra Sekhar, Dr. K. Ramchand H Rao, Dr. R Satya Prasad,” Predicting the Diabetes using Duo Mining Approach”, International Journal of Advanced Research in Computer and Communication Engineering ISSN : 2278 – 1021,Vol. 1, Issue 6, pp. 423-431, August 2012.
[4] K.Sreerama Murthy, Dr G. Samuel Varaprasad Raju, Dr C. Sunil Kumar,” Text Mining For Retrieving The Vital Information”, International Journal of Research in Computer and Communication Technology, Vol. 3, Issue 1, pp.99-103,Jan 2014.
[5] Manish Sharma, Rahul Patel,” A Survey on Information Retrieval Models, Techniques and Applications”, International Journal of Emerging Technology and Advanced Engineering, ISSN 2250-2459,pp.542-545, November 2013.
[6] B.Ganga,” Phrase Based Document Retrieving by Combining Suffix Tree index data structure and Boyer- Moore faster string searching algorithm”, International Journal of Advancements in Research & Technology, ISSN 2278-7763,Vol. 3, Issue 3, pp. 147-153,March 2014.
[7] Ian H. Witten,” Text mining”, Computer Science, University of Waikato, Hamilton, New Zealand, pp 01-23,2004.
[8] Roi Blanco González,” Index Compression for Information Retrieval Systems”, Ph.D. Thesis, University of A Coruña, 2008.
[9] Deepak Agnihotri, Kesari Verma, Priyanka Tripathi,” Pattern and Cluster Mining on Text Data”, Fourth International Conference on Communication Systems and Network Technologies, IEEE Computer Society, pp. 428-432, 2014.
[10] R. Sagayam, S.Srinivasan, S. Roshni,” A Survey of Text Mining: Retrieval, Extraction and Indexing Techniques”, International Journal Of Computational Engineering Research, ISSN 2250-3005, Vol. 2 Issue. 5, pp. 1443-1446, September 2012.
[11] Sonali Vijay Gaikwad, Prof. Archana Chaugule, Swapnil Kulkarni, ” Performance Comparison for Text Mining Methods: Review”, International Journal of Advanced Engineering Research and Studies, E-ISSN 2249–8974, pp. 01-04, Oct.-Dec, 2014.
[12] Ning Zhong, Yuefeng Li, and Sheng-Tang Wu,” Effective Pattern Discovery for Text Mining”, IEEE Transactions On Knowledge And Data Engineering, Vol. 24, No. 1,pp. 30-44, Jan. 2012.
[13] S.S. Patil,V.M. Gaikwad, ” Developing New Software Metric Pattern Discovery for Text Mining”, International Journal of Computer Sciences and Engineering, Vol. 2, Issue-4,pp. 119-125, April 2014.
[14] Bhushan Inje, Ujawla Patil,” Operational Pattern Revealing Technique in Text Mining”, IEEE Students’ Conference on Electrical, Electronics and Computer Science,2014.
[15] Ziqi Wang, Gu Xu, Hang Li, and Ming Zhang,” A Probabilistic Approach to String Transformation”,published in IEEE Transactions On Knowledge And Data Engineering, Vol. 26, No. 5,pp. 1063-1075, May 2014.
[16] Saima Hasib, Mahak Motwani, Amit Saxena,” Importance of Aho-Corasick String Matching Algorithm in Real World Applications” published in International Journal of Computer Science and Information Technologies, ISSN: 0975-9646, Vol. 4 (3) , pp. 467-469,2013.

Sneha Lohbare and Ashwini Meshram, "A Review on Document Retrieval from Unstructured Text," International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.76-80, 2014.

One of the most important applications in internet is load balancing. For load balancing in IP networks, there are different approaches including Active Queue Management (AQM) which has a proportionate development in research. CHOKe is an AQM method ensures Quality of Service in congested traffic by differentiating responsive flows and unresponsive flows. The survey attempts to study the CHOKe with its descendants and investigates the algorithms based on various congestion metrics and short lived as well as long lived TCP traffic and UDP flows.

AQM, CHOKe, IP Networks, Load Balancing

[1] en.wikipedia.org/wiki/IP_address.
[2] searchnetworking.techtarget.com/definition/load-balancing.
[3] en.wikipedia.org/wiki/Fair_queuing.
[4] en.wikipedia.org/wiki/Weighted_fair_queueing.
[5] en.wikipedia.org/wiki/Explicit_Congestion_Notification.
[6] gettys.wordpress.com/active-queue-management-aqm-faq.
[7] B. Kiruthiga and Dr. E. George Dharma Prakash Raj, “Survey on AQM Congestion Control Algorithms”, IJCSMC, Vol. 2, Issue. 2, pp.38–44, Feb 2014.
[8] G.F.Ali Ahammed, Reshma Banu, “Analyzing the Performance of Active Queue Management Algorithms”, IJCNC, Vol. 2, pp. 19, Mar 2010.
[9] Rong Pan, Balaji Prabhakar, Konstantinos Psounis, “CHOKe: A stateless active queue management scheme for approximating fair bandwidth allocation”, INFOCOM 2000, vol.2, pp. 942-951, Mar 2000.
[10] Ao Tang, Jiantao Wang and Steven H. Low, “Understanding CHOKe: Throughput and Spatial Characteristics”, IEEE/ACM Trans. Networking, vol. 12, No. 4, pp. 694-707, Aug 2004.
[11] Jiang Ming, WU Chumming, Zhang Min and Bian Hao, “CSa-XCHOKe: A Congestion Adaptive CHOKe Algorithm”, Chinese Journal of Electronics, Vol.19, No.4, Oct 2010.
[12] Ying Jiang, and Jing Liu, “Self adjustable CHOKe: an active queue management algorithm for congestion control and fair bandwidth allocation”, IEEE computers and comm., Vol.2, No.4, pp. 1018-1024, Jul 2013.
[13] K.Chitra and Dr. G.Padamavathi, “Adaptive CHOKe: An algorithm to increase the fairness in Internet Routers”, IJANA, vol. 01, Issue. 06, pp. 382-386, Apr 2010.
[14] G. Sasikala and E. George Dharma Prakash Raj, “P-CHOKe: A Piggybacking-CHOKe AQM Congestion Control Method”, IJCSMC, Vol. 2, Issue. 8, pp.136–144, Aug 2013.
[15] Addisu Eshete and Yuming Jiang, “Protection from Unresponsive Flows with Geometric CHOKe”, Centre for Quantifiable Quality of Service in Communication Systems, Feb 2012.
[16] K.Chitra and Dr.G.Padmavathi, “FAVQCHOKE: To Allocate Fair Buffer To A Dynamically Varying Traffic In An Ip Network”, IJDPS, Vol. 2, Issue. 1, pp.73–82, Jan 2011.
[17] Shushan Wen, Yuguang Fang and Hairong Sun, “CHOKeW: Bandwidth Differentiation and TCP Protection in Core Networks”, IEEE Trans. Parallel and Distributed Sys. , Vol. 20, NO. 1, pp. 34-47, Jan 2009.
[18] Lingyun Lu, Haifeng Du and Ren Ping Liu, “CHOKeR: A Novel AQM Algorithm with Proportional Bandwidth Allocation and TCP Protection”, IEEE Trans. Industrail Informatics, Vol. 10, No. 1, pp.637–644, Feb 2014.
[19] Addisu Eshete and Yuming Jiang, “Generalizing the CHOKe Flow Protection”, Preprint submitted to Computer Networks, pp.1–28, Feb 2012.
[20] Shalki Chahar, “Social Networking Analysis”, International Journal of Computer Sciences and Engineering, Vol. 02, No. 5, pp.159–163, May 2014.

Vijith C and M. Azath, "Survey on CHOKe AQM Family," International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.81-85, 2014.

Today, as a result of the global internet viewers increased rapidly, consumers are more focused than ever on searching the best product and the best prices. Consequently, e-commerce corporations also invested their time, money and efforts to know the feedback and comments about their products. That would help the corporations to modernize their product at low prices, which in turn help them to extend and prosper in their business. Customer / Product review is an evaluation of the product performance and comment on the reliability and whether or not the product delivers on these promises. Now-a-days, online reviews are the recent media world-of-mouth, they are enormously influential and may have an enormous effect on however business is perceived. Since, overwhelming information on one product is available in the form of review, individuals or corporation finds very difficult to analyse each and every review to extract knowledge from that pool of unstructured data. So, to analyse and to extract knowledge from these large amounts of data automatic method must be developed. This paper describes the ROM framework for developing such an automatic method to mine the opinion from the online product reviews.

Opinion Mining, Sentiment Analysis, Framework for Opinion Mining

[1] Liu, B. 2010. Sentiment analysis and subjectivity. In Handbook of Natural Language Processing, Second Edition, N. Indurkhya and F. J. Damerau, Eds. CRC Press, Taylor and Francis Group, Boca Raton, FL. ISBN 978-1420085921.
[2] Pang, B. and Lee, L. 2008. Opinion mining and sentiment analysis. Found. Trends Inf. Retr. 2, 1-2, 1–135.
[3] Bing Liu. Sentiment Analysis and Opinion Mining, Morgan & Claypool Publishers, May 2012.
[4] Hemalatha, G.P. Saradhi Varma, A. Govardan, Preprocessing the Informal Text for efficient Sentiment Analysis, IJETTCS, Volume 1, Issue 2, July-August 2012, ISSN: 2278-6856
[5] Kushal Bafna, Durga Toshniwal, Feature Based Summarization of Customers' Reviews of Online Products, Elsevier Procedia Computer Science 22(2013) 142-151.
[6] Alexandra Blahur, Mijali Kabadjov, Josef Steinberger, Ralf Steinberger, Andres Montoyo, Challenges and solutions in the opinion summarization of user-generated content, Springer Science, J Intell Inf Syst (2012) 39: 375-398
[7] Bakhtawar Seerat, Farouque Azam, Opinion Mining : Issues and Challengers (A Survey), IJCA, (0975-8887), Volume 48 – No. 9 July 2012.
[8] Kim, Hyun Duk, Ganesan Kavita A., Sondhi Parikshit, and Zhai ChengXiang, Comprehensive Review on Opinion Summarization, 2011.
[9] Dingding Wang, Shenghuo Zhu, Tao Li, SumView: A Web-based engine for summarizing product reviews and customer opinions, Elsevier, Expert Systems with Applications 40 (2013) 27-33
[10] Radev, D., Jing, H., Stys, M., & Tam, D. (2004). Centroid-based summarization of multiple documents. Information Processing and Management, 919–938.
[11] Mihalcea, R., & Tarau, P. (2005). A language independent algorithm for single and multiple document summarization. In Proceedings of IJCNLP 2005.
[12] Wan, X., Yang, J., & Xiao, J. (2007). Manifold-ranking based topic-focused multi-document summarization. In Proceedings of IJCAI (pp. 2903–2908).
[13] Gong, Y., & Liu, X. (2001). Generic text summarization using relevance measure and latent semantic analysis. In Proceedings of SIGIR (pp. 75–95).
[14] Li, T., & Ding, C. (2006). The relationships among various nonnegative matrix factorization methods for clustering. In Proceedings of IEEE international conference on data mining (pp. 362–371).
[15] Shen, D., Sun, J.-T., Li, H., Yang, Q., & Chen, Z. (2007). Document summarization using conditional random fields. In Proceedings of IJCAI (pp. 2862–2867).
[16] Conroy, J., & O’Leary, D. (2001). Text summarization via hidden markov models. In Proceedings of SIGIR (pp. 406–407.
[17] Dhanashri Chafale and Amit Pimpalkar, "Review on Developing Corpora for Sentiment Analysis Using Plutchik’s Wheel of Emotions with Fuzzy Logic", International Journal of Computer Sciences and Engineering, Volume-02, Issue-10, Page No (14-18), Oct -2014, E-ISSN: 2347-2693

K. Vivekanandan and V.L. Helen Josephine, "ROM - Review Opinion Mining a Novelized Framework," International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.86-89, 2014.

The rapid development of data transmission through internet made it easy to send the data at faster rate to the destination. This work proposes a scheme for distinct revocable data hiding in ciphered images. At first, a content owner encrypts the original image with help of the encryption key. Then, the LSB of the encrypted image are compressed using a data-hiding key by the data hider to create a space to include some data. If a receiver has the data-hiding key, the additional data can be retrieved easily. And if the receiver has the encryption key, he can easily decrypt the received data to get the image similar to the original one, but cannot obtain the data. In case if the receiver has both the data-hiding key as well as the encryption key, he can obtain the data and regain the original image content. Hence, in order to transfer the data securely to the destination without any modifications, there are many techniques like cryptography and about the various steganographic algorithms like Least Significant Bit (LSB) algorithm.

Data hiding; Crptography; Steganography

[1] Study On Separable Reversible Data Hiding In Encrypted Image, International Journal Of Advancements In Research & Technology, Volume 2, Issue 12, December-2013 223 ISSN 2278-7763.
[2] Xinpeng Zhang, Separable Reversible Data Hiding In Encrypted Image, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 7, NO. 2, APRIL 2012.
[3] Kede Ma, Weiming Zhang, Xianfeng Zhao, Member, IEEE, Nenghai Yu, And Fenghua Li, Reversible Data Hiding In Encrypted Images By Reserving Room Before Encryption, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 8, NO. 3, MARCH 2013.
[4] Lalit Dhande, Priya Khune, Vinod Deore, Dnyaneshwar Gawade, Hide Inside-Separable Reversible Data Hiding In Encrypted Image, International Journal Of Innovative Technology And Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-3, Issue-9, February 2014.
[5] Jun Tian, Reversible Data Embedding Using A Difference Expansion, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 13, NO. 8, AUGUST.
[6] M. Johnson, P. Ishwar, V. M. Prabhakaran, D. Schonberg, And K.Ramchandran, On Compressing Encrypted Data,” IEEE Trans. Signal Process, Vol. 52, No. 10, Pp. 2992–3006, Oct. 2004.
[7] C.-C. Chang, C.-C. Lin, And Y.-H. Chen, Reversible Data-Embedding Scheme Using Differences Between Original And Predicted Pixel Values, IET Inform. Security, Vol. 2, No. 2, Pp. 35–46, 2008.
[8] Kede Ma, Weiming Zhang, Reversible Data Hiding In Encrypted Images By Reserving Room Before Encryption, IEEE Trans. VOL. 8, No. 3, Mar 2013.

Anamika Patil, Pooja Bafna, Mona Pounikar and Pranjal Badgujar, "Distinct Revocable Data Hiding In Ciphered Image," International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.90-94, 2014.

The perfect architecture of Grid Computing System, analyzes security requirements. Some security problems existing in Grid Computing System, presents five-layer security architecture, defines a new set of security policy and gives the representation, introduces future work. In various ways we are trying to explain grid computing along with its architecture, infrastructure and the standards available for grid computing. Then at last we have discussed about the earlier and current activities in grid computing.

Grid Computing, Grid Architecture, Application Layer, Open Grid Service Architecture (OGSA). Grid Application, Grid Infrastructure

[1] Foster and C. Kesselman, “The Grid: Blue print for a new computing infrastructure”, Morgan Kaufmann Publications (1999).
[2] Foster, C. Kesselman, J. M. Nick and S. Tuecke, “The physiology of the Grid: An open grid services architecture for distributed systems integration”, Grid Forum white paper, 2003.
[3] Volker Sander, “Networking Issues for Grid Infrastructure”, GFD-I.037, Nov, 22, 2004.
[4] I. Foster, C. Kesselman, C. Lee, R. Lindell, K. Nahrstedt, A.Roy. “A Distributed Resource Management Architecture that Supports Advance Reservations and Co-Allocation”, Intl Workshop on Quality of Service, 1999.
[5] I. Raicu, Y. Zhao, C. Dumitrescu, I. Foster, M. Wilde. “Falkon:a Fast and Light-weight tasK executiON framework”,IEEE/ACM SuperComputing 2007.
[6] Foster, I. & Kesselman, C. (Eds). The Grid: Blueprint for a New Computing Infrastructure. Morgan-Kaufmann (1999).
[7] Foster, I. & Kesselman, C. Globus: A Toolkit-Based Grid Architecture. In ref. 2, pages 259-278. Morgan Kaufmann Publishers (1999).
[6] The Globus Security Team. “Globus Toolkit Version 4 Grid Security Infrastructure: A Standards Perspective,” Technical Report, Argonne National Laboratory, MCS, 2005.
[9] Technology and Strategy Perspectives (Fellenstein, 2004) for further details and precision on important technologies, Grid Computing, and key strategy perspectives.
[10] Fellenstein (2004) for further details and precision on important technologies, Grid Computing, and key strategy perspectives.
[11] Fellenstein (2004) for further details and precision on important service provider technologies, Grid Computing, and key strategy perspectives on both topics.

V.Priya, K.Yamunadevi and P.Priyanga, "Architecture and Layers in Grid Computing," International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.95-101, 2014.