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Energy efficient Routing is one of the keyissues in MANETs due to their highly dynamic topology and limited battery power at the nodes. In particular identifying energy efficient routing is the most important parameters for mobile ad-hoc networks. Power failure of a mobile node not only affects the node itself but also reduces the overall network lifetime. The goal of this paper is to facilitate research efforts in combining existing solutions in order to offer a more energy efficient routing approach. Towards this goal, we analysed of the three routing protocols AODV, DSR and DSDV for mobile ad-hoc networks scenarios. Our study mainly the energy consumed by each protocol.

Routing Protocols, Energy Consumption, Ad-Hoc Network

[1]. Niranjan Kumar Ray, Ashok Kumar Turuk Energy Efficient Techniques for Wireless Ad Hoc Network, in proceedings of first international joint conference on Information & communication technology, IJCICT, Pages(105-111),January 2010.
[2]. Chansu Yu, Ben Lee, Energy efficient routing protocols for mobile ad hoc networks, wireless communications and mobile computing, 2003; 3:959�973.
[3]. MortezaMaleki, KarthikDantu, Power-aware Source Routing Protocol for Mobile Ad Hoc NetworksISLPED�02, August 12-14, 2002.
[4]. Sanjay Kumar Dhurandher, EEAODR: An energy-efficient ad hoc on-demand routing protocol for mobile ad hoc networks, International Journalof Communication Systems, 2009; 22:789�817.
[5]. M. X. Cheng, J. Sun, M. Min, and D.-Z. Du, �Energy efficient broadcast and multicast routing in ad hoc wireless networks,� in Proceedings of the 2003 IEEE International Performance, Computing, and Communications Conference (IPCCC), April 2003, pp. 87�94.
[6]. W. Liang, �Constructing minimum-energy broadcast trees in wireless ad hoc networks.� In Proceedings of 3rd International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc). ACM, 2002, pp.112�122.
[7]. Suman Banerjee, ArchanMisra, Minimum Energy Paths for Reliable Communication in Multi-hop Wireles Networks,MOBIHOC�02, June 9-11, 2002.
[8]. Deying Li, XiaohuaJia, Energy Efficient Broadcast Routing in Static Ad Hoc Wireless Networks,IEEE Transactions On Mobile Computing, Vol. 3, No. 2, April-June 2004 .
[9]. Perkins C. and Royer EM. Ad hoc On Demand Distance Vector (AODV) Routing. Proceedings of the Second IEEE Workshopon Mobile Computing Systems and Applications, 1999; 90-100.
[10]. Johnson DB. andMaltz DA. Dynamic Source Routing in Ad-HocWireless Networking, Mobile Computing; Kluwer AcademicPublishing: New York, 1996.
[11]. Das SR., Perkins CE., and Royer EM. Performance Comparison of Two On-Demand RoutingProtocols for Ad Hoc Networks.Proceedings of the IEEE INFOCOM 2000; 3-12.
[12]. Royer E. and Toh CK. A Review of Current Routing Protocols for Ad Hoc MobileWireless Networks. IEEE PersonalCommunications 1999; 46-55.
[13]. Cordeiro CM. and Agrawal DP.Mobile Ad Hoc Networking.Proceedings of the 20th Brazilian Symposium on Computer Networks 2002; 125-186.
[14]. J. Broch, D. A. Maltz, D. B. Johnson, Y.-C. Hu, and J. Jetcheva, �A performance comparison of multi-hop wireless ad hoc network routingprotocols,� in MobileComputing and Networking(MobiCom), 1998, pp.85--97.
[15]. T. Chu and I. Nikolaidis, �On the artifactsof random waypointsimulations,� in First International Workshop on Wired/Wireless Internet Communications (WWIC 2002) in conjunction with the 3rd International Conference on Internet Computing 2002 (IC 2002), June 2002.
[16]. De Rango F., Gerla M., Marano S. (2006). A Scalable Routing Scheme with Group MotionSupport in Large and Dense Wireless Ad Hoc Networks, ElsevierComputers andElectrical EngineeringJournal, Vol.32, Issue 1-3, May 2006,pp.224-240.
[17]. De Rango F., Guerriero F., Fazio P.(2011). Link-Stability and Energy aware Routing Protocolin Distributed Wireless Networks,� to be published on IEEE Transaction on Paralleland Distributed Systems.

N. Kishore, S. Singh, R. Dhir, "Energy Related Issues for MANETs: A Study," International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.98-100, 2014.

The Open source installer production tools are widely used for building software installer application. This survey paper deals with the most commonly occurring java based open source installer production tools in the software market and classified the tools according to the file packaging and distribution mechanism. This survey is mainly focused on open source installer production tools, which provides the framework for generating automated unattended installer. The automated installer is more generic installer for all types and versions of operating system and also provides the unique and clean way of distributing the software application during silent unattended installation. In the Introduction the reader is informed about the advantages of the Open source tools, furthermore discussed about types of installation, Open source Licenses, Java based installer production tools. At the end conclusion is drawn and outline some questions for future research.

Distribution, Licenses, Installer, Opensource, Automated Installation, Application, Installer Building Tool

[1] Antigen Installer, http://antigen.sourceforge.net as of 05/15/2014.
[2] AntInstaller, http://antinstaller.sourceforge.net as of 05/15/2014.
[3] Apache SW License v1.1, www.apache.org/licenses/LICENSE-1.1 as of 01/15/2014.
[4] Apache SW License, v2.0, www.apache.org/licenses/LICENSE-2.0 as of 01/15/2014.
[5] BSD license, opensource.org/licenses/bsd-license.php as of 01/15/2014.
[6] CPL v1.0, opensource.org/licenses/cpl1.0.php as of 01/15/2014.
[7] FreeInstaller, http://www.xenonsoft.demon.co.uk/products/freeinstaller as of 05/15/2014.
[8]Free Open Source Software http://freeopensourcesoftware.org/index.php?title=Main_Page as of 05/15/14.
[9] GNU GPL License, www.gnu.org/copyleft/gpl.html as of 01/15/2014.
[10] GNU LGPL License, www.gnu.org/copyleft/lgpl.html as of 01/15/2014.
[11] Installation, http://en.wikipedia.org/wiki/Installation as of 05/15/14
[12] IzPack installer, http://www.izforge.com as of 05/15/2014.
[13] Java-service-wrapper, http://wrapper.tanukisoftware.org as of 05/15/2014.
[14] Jsmooth Installer, http://jsmooth.sourceforge.net as of 05/15/2014.
[15] Launch4j installer, http://launch4j.sourceforge.net as of 05/15/2014.
[16] LiftOff installer, http://liftoff.sourceforge.net/index.en.html as of 05/15/2014.
[17] MiniInstaller, http://www.yagga.net/java/miniinstaller/index.shtml as of 05/15/2014.
[18] Mozilla Public License v1.1, www.mozilla.org/MPL/MPL-1.1.html as of 05/15/2014.
[19] Open source, http://en.wikipedia.org/wiki/Open_source as of 05/15/14.
[20] Packlet installer, http://packlet.sourceforge.net as of 05/15/2014.
[21]VAInstall installer, http://vainstall.sourceforge.net as of 05/15/2014.

Priyadharshini T., Sumathi V.P., "A Survey of Open Source Installer Production Tools," International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.101-104, 2014.

This paper details about the single cloud and multi clouds security systems using MultiPart Secret Sharing Algorithm using Shamir�s Secret and RSA algorithm and addresses possible solutions and methodology. Main focus of in this paper is on use of multi clouds and data security and reduces security risks and affects the cloud computing users using Multipart Secret sharing algorithm. It is a form of secret sharing, where a secret is divided into parts, which is giving each participant its own unique part, where some of the parts are required in order to reconstruct the secret. This algorithm is used where any �k� the parts are sufficient to reconstruct the original secret message, helping in Enhanced Security measures.

Cloud Computing, Multi Clouds,Multipart Secret Sharing Algorithm, Threshold, Reconstruct

[1]. Md Kausar Alam, Sharmila Banu K, �An Approach Secret Sharing Algorithm in Cloud Computing Security over Single to Multi Clouds.�, International Journal of Scientific and Research Publications, Volume 3, Issue 4, April 2013 1 ISSN 2250-3153.School of Computing Science and Engineering, VIT University, Vellore, Tamil Nadu, India.
[2]. Carlos Goncalves, Luis Assuncao, Jose C,�Data Analytics in the Cloud with Flexible MapReduce Workflows�, IEEE 4th International Conference on Cloud Computing Technology and Science.
[3]. Mandeep Kaur and Manish Mahajan,�Implementing various encryption algorithms to enhance the data security of cloud in cloud computing�, VSRD International Journal of Computer Science &Information Technology, Chandigarh Engineering College, Mohali, Punjab, INDIA, Vol. 2 No. 10 October 2012 / 831ISSN No. 2231-2471 (Online), 2319-2224 (Print)
[4]. SafeGuard Encryption for Cloud Storage.
[5]. Available at
http://en.wikipedia.org/wiki/Shamir`s_Secret_Sharing.

A. Vaikar, D. Pawar, Y. Laddha, "Assured Data Storage: A Divide and Secure Multipart Algorithm for Cloud Storage," International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.105-108, 2014.

Oral cancer is the most common cancer found in both men and women. Early Detection of Oral Cancer is important in saving life. Dental Radiographs assists experts in identifying cancers grown inside the mouth. To help radiologists, Computer Aided Detection and Computer Aided Diagnosis algorithms are developed. The algorithms help to identify cancers by reducing the need for Biopsy. This paper gives a review of Computer Aided Techniques that have been developed for detection and classification of oral cancers.

Radiographs, Computer Aided Detection, Computer Aided Diagnosis

[1] Arlene Guagliano, �Oral Cancer: Early Detection Saves Life�, Dental Tribune, Middle East and African Edition, Page No (6-7), June � August 2011.
[2] National Cancer Institute Website, www.cancer.gov
[3] A.S.Jadhav, S.Banerjee, P.K.Dutta, R.R. Paul, M.Pal, P. Banerjee, K. Chaudhuri and J. Chatterjee, �Quantitative analysis of histopathological features of precancerous lesion and condition using Image Processing Techniques�, 19th IEEE Symposium on Computer-Based Medical Systems, ISBN 0-7695-2517-1, Page No (231 � 236), June 22 � 23, 2006.
[4] Ghassan Hamarneh, Artur Chodorowski and Tomas Gustavsson, �Active Contour models: Application to oral Lesion detection in color images�, IEEE Conference in Systems, Man and Cybernetics, Nashville, TN, USA, Page No (2458 � 2463), October 2000.
[5] Yung nien Sun, Yi-ying Wang, Shao-chien Chang, Li-wha Wu and Sen � tien Tsai, �Color � based tumor segmentation for the automated estimation of oral cancer parameters�, Microscopy Research and Technique, Volume - 73, Issue - 1, Page No (5- 13), June 2009.
[6] Man Kin Derek Ho, �Watershed segmentation algorithm for medical confocal image analyses towards in vivo early cancer detection�, National Nanotechnology Infrastructure Network. Page No 14 � 16.
[7] Woonggyu Jung, Jun Zhang, Jungrae Chung, Petra Wilder � Smith, Matt Brenner, J. Stuart Nelson and Zhongping Chen, �Advances in Oral Cancer Detection using Optical Coherence Tomography�, IEEE Journal of Selected Topics in Quantum Electronics, Volume - 11, No.4, Page No (811 � 817), 2005.
[8] R.Hari Kumar, C.Ganesh babu, P.Shri vignesh, �Earlier Detection of Oral cancer from fuzzy based photo plethysmography�, International Journal of Soft Computing and Engineering, Volume � 2, No � 1, Page No (128 � 133), March 2012.
[9] A.Banumathi, J.Praylin Mallika , S.Raju and V.Abhai Kumar, �Automated Diagnosis and Severity Measurement of Cyst in Dental X-ray Images using Neural Network�, International Journal of Biomedical Soft Computing and Human Sciences, Volume - 14, Issue - 2, Page No (103 � 108), 2009.
[10] A.Banmathi, A.Kannammal, R.Arthee, S.Raju and V.Abhai Kumar.V, �Automated Diagnosis and Severity Measurement of Cysts in Dental X-ray Images using Neural Network�, International Journal of Biomedical Soft Computing and Human Sciences, Volume -11, Issue - 1, Page No (15 � 19), 2005.
[11] C.Venugopal, S.Nazeer Shaiju, Balan Anita and R.S.Jayasree, �Autofluorescence Spectroscopy Augmented by Multivariate Analysis as a Potential Noninvasive Tool for Early Diagnosis of Oral Cavity Disorders�, Journal of Photomedicine and Laser Surgery, Volume - 31, (12), Page No (605-612), 2013.
[12] Ranjan Rashmi Paul, Anirban Mukherjee, Pranab K. Dutta, Swapna Banerjee, Mousumi, Pal, Jyotirmoy Chatterjee and Keya Chaudhuri, �A novel wavelet neural network based pathological stage detection technique for an oral precancerous condition�, Journal of Clinical Pathology, Volume - 58 (9), Page No (932 �938), 2005.
[13] Simon Kent, �Diagnosis of oral cancer using Genetic Programming � A Technical Report�, CSTR-96-14 CNES-96-04, 1996.
[14] S.Prasanna, K.Govinda and U.Senthil Kumaran, �An evaluation study for oral cancer detection using Data Mining Classification Techniques�, International Journal of Advanced Research in Computer Science, Volume � 3, Issue - 1, Page No (142 � 146), 2012.
[15] Neha Sharma and Hari Om, �Framework for early detection and prevention of oral cancer using Data Mining�, International Journal of Advances in Engineering and Technology, Volume � 4, Issue - 2, Page No (302 � 310), 2012.
[16] P.Konstantinos, Exarchos, Yorgos Goletsis and Dimitrios I. Fotiadis, �Unification of heterogeneous data towards the prediction of oral cancer reoccurrence�, AIAI-2009 Workshops Proceedings, Page No (24 � 35), 2009.
[17] M.M. Krishnan, U.R.Acharya, C. Chakraborty and A.K. Ray, �Automated Diagnosis of Oral Cancer Using Higher Order Spectra Features and Local Binary Pattern: A Comparative Study�, Technology in Cancer Research and Treatment, 10 (5), Page No (443-455), 2011.
[18] Ingrid Nurtanio, Renwi Astuti, I Ketut Eddy Purnama, Mohamad Hariadi and Mauridhi Hery Purnomo, �Classifying Cyst and Tumor Lesion using Support Vector Machine Based on Dental Panoramic Images Texture Features�, IAENG International Journal of Computer Science, 40(1), 2013.
[19] Ingrid Nurtanio, I Ketut Eddy Purnama, Mohamad Hariadi, and Mauridhi Hery Purnomo, �Cyst and Tumor Lesion Segmentation on Dental Panoramic Images using Active Contour Models�, IPTEK The Journal of Technology and Science, Volume � 22, No - 3, Page No (152 � 158), 2011.
[20] Lalit Gupta, Sarif Kumar Naik and Srinivasan Balakrishnan, �A new feature selection and classification scheme for screening of oral cancer using laser induced fluorescence�, Proceedings of the First International Conference on Biometrics (ICMB�08 ), ISBN:3-540-77410-6 978-3-540-77410-5, Page No (1-8), Jan 4 � 5, 2008.
[21] Sebastian Steger, Marius Erdt, Gianfranco Chiari and Georgios Sakas, �Feature Extraction from Medical Images for an oral cancer reoccurrence prediction environment�, World Congress on Medical Physics and Biomedical Engineering, Munich, Germany, Page No (97 � 100), Sep 7 -12, 2009.
[22] G. Landini, �Quantitative analysis of the epithelial lining architecture in radicular cysts and odontogenic keratocysts�, Head & Face Medicine, Volume � 2, Feb 2006.
[23] Yusaku Nishi, Keiichi Horio, Kentaro Saito, Manabu Habu and Kazuhiro Tominaga, �Discrimination of Oral Mucosal Disease Inspired by Diagnostic Process of Specialist�, Journal of Medical and Bioengineering, Volume - 2, No - 1, Page No (57 � 61), 2013.
[24] Yung �nien Sun, Yi-ying Wang, Shao-chien Chang, Li-wha Wu and Sen � tien Tsai, �A color � based approach for automated segmentation in Tumor Tissue Classification�, Proceedings of the 29th Annual International conference of the IEEE Engineering in Medicine and Biology Society, 2007.
[25] Yung nien Sun, Yi-ying Wang, Shao-chien Chang, Li-wha Wu and Sen � tien Tsai, �Color � based tumor segmentation for the automated estimation of oral cancer parameters�, Microscopy Research and Technique, 73(1), Page No (5- 13), 2010.
[26] Ji Wan Han. A Toby Breckon, David Randell, Gabriel Landini, �Radicular cysts and odontogenic keratocysts epithelia classification using Cascaded Haar classifiers�, Proceedings of the 12th Annual Conference on Medical Image Understanding and Analysis, 2008.
[27] Tathagata Ray, D. Shivashanker Reddy, Anirban Mukherjee, Jyotirmoy Chatterjee, Ranjan R. Paul and Pranab K. Dutta, �Detection of constituent layers of histological oral sub-mucous fibrosis: Images using the hybrid segmentation algorithm� Science Direct, Oral Oncology, Volume - 44, Issue � 12, Page No (1167 � 1171), Dec 2008.
[28] S.Venkatakrishnan, V. Ramalingam and S.Palanivel, �Classification of Oral Sub mucous Fibrosis using SVM�, International Journal of Computer Applications, Volume - 78, No - 3, Page No (8-11), 2013.
[29] Muthu Rama Krishnan.M, Chandran Chakraborthy and Ajoy Kumar Ray, �Wavelet based texture classification of oral histopathological sections�, International Journal of Microscopy, Science, Technology, Applications and Education, Volume � 2, Page No (897-906), 2011.
[30] M.R.Brickley, J. G. Cowpe and J. P. Shepherd, �Performance of a computer simulated neural network trained to categorise normal, premalignant and malignant oral smears�, Journal of Oral Pathology and Medicine, Volume - 25, Issue - 8, Page No (424 � 428), 1996
[31] A. Chodorowski, U. Mattsson and T. Gustavsson, �Oral Lesion classification using true color images�, Proceedings of SPIE (International Society for Optics and Photonics), Volume � 3661, Page No (1127 � 1138), 1999.
[32] Neha Sharma, Nigdi Pradhikaran and Akurdi, �Comparing the performance of data mining techniques for oral cancer prediction�, International Conference on Communication, Computing & Security (ICCCS�11), ISBN: 978-1-4503-0464-1, Page No (433 � 438), New York, USA, 2011.
[33] R. Jaya Suji and S.P.Rajagopalan, �An automatic oral cancer classification using Data Mining Techniques�, International Journal of Advanced Research in Computer and Communication Engineering, Volume � 2, Issue - 10, Page No 3(759 � 3765).

K. Anuradha, K. Sankaranarayanan, "A Review on Computer Aided Detection Techniques of Oral Cancer," International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.109-114, 2014.

The administrators are always worried about not being informed of the failure which takes place in network, or they are informed lately. Even if they are informed soon, it is not possible for them to reach the location to solve the problem. This mainly occurs because the network manager needs to go there or need an access to internet to fix the problem. This paper suggests a method for remote administration of computer network. Also network managers can send commands to the application software by Short Message Service (SMS) to let it issue commands for fixing the failure. By applying this approach, network managers can control and manage their network when they are far from the network location. In this approach administrator can send an SMS and get all the information what exactly is client doing.

Network;Monitor;Remote;SMS

[1]. Vieira Junior, A.C., Anido, M.L. �The Architecture of a Novel Tool for Network Management Using GSM/GPRS Mobile Devices�, Consumer Communications and Networking Conference, ISBN: 078038145-9, Page No (539-544), Jan 5-8, 2004.
[2]. Dr. S.A.Ladhake ,Nitin D. Shelokar �Network Handle by mobile� International Journal of Computer Trends and Technology, Volume-01, Issue-02, Page No(1-4), May to June 2011.
[3]. Carlos E. CaicedoBastidas �Remote Management of Computer Network by Short Message Service�, Computer and Communication Engineering International Conference, ISBN:978142441692-9, Page No (300-305), May 13-15, 2008.
[4]. Faramarz Givehki, Abbas Nicknafs �Mobile control and management of computer network using sms service� Journal of Telematics and Informatics, Volume-27, Issue-03, Page No (341�349), August 2010.
[5]. Prof. C. S. Nimodia, Prof. S. S. Asole �A Survey on Network Monitoring and Administration Using Email and Android Phone� International Journal of Emerging Technology and Advanced Engineering, Volume-03, Issue-04, Page No (83-87), April 2013.
[6]. Anis Ismail, Mohammad Hajjar, Haissam Hajjar �Remote Administration Tools: A Comparative Study�, Journal of Theoretical and Applied Information Technology, Volume-04, Issue-02, Page No (140-148), 2005.
[7]. Rupali Chopade, Shashank Diwan, Ajinkya Jiman, Avinash Jadhav, Avinash Navale, Sagar Lad �Local Area Network Administration Using Mobile�, International Journal of Engineering and Innovative Technology, Volume-01, Issue-03, Page No (61-63), March 2012.
[8]. Amol Poman, Mahesh Gundras, Prashant Pujari �GSM Based LAN Monitoring System�, International Journal of Computer Science and Information Technologies, Voume-03, Issue-03, Page No (3848-3851), 2012.
[9]. Herbert Schildt �Java Complete Reference�, Tata McGraw-Hill Education Private, Seventh Edition, ISBN: 9780070636774, Page No (813-845), 2006.
[10]. Amit Chauhan, Reecha Ranjan Singh, Sangeeta Agrawal, Saurabh Kapoor, S.Sharma, �SMS Based Remote Control System�, International Journal of Computer Science and Management Studies, Volume-11, Issue-02, Page No (19-24), August 2011.

P. Gupta, M. Pagar, G. Patil, R. Ugale, "Remote Control and Administration of Computer Network via SMS," International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.115-118, 2014.

Cloud computing is considered to be the next generation of information technology framework. It is the next generation computing platforms that can provide dynamic resource pools, virtualization and high availability. The new character brings a lot of new security challenges which have not been taken into account completely in the current cloud computing system. As a consequence, to build a cloud computing data security system is the basis to build cloud computing security system. In this article, the cloud computing technology architecture and the cloud computing data security challenges are the first to be studied and considered, and then the Biometric is raised. At last, the problem definition & resolving strategy has been researched. First of all, user authentication is required to ensure that user data cannot be tampered. Users who pass the authentication can get relative operation on the user data, such as addition, modification, deletion. If the unauthorized user use illegal means to deceive the biometric authentication system, the file entered the system encrypt and privacy defense levels. If key has been got by the intruder. The user data cannot be got valid information even it is obtained through function of privacy protection. It is very important for commercial users of the cloud computing to protect their business secrets.

Cloud Computing,VPN,SLA,QoS, API,Biometrics

[1] Hataichanok, S., Clarke, N. L., and Furnell, S. M. 2012. Multi-modal Behavioural Biometric Authentication for Mobile Devices. In Information Security and Privacy Research, pp. 465-474. Springer Berlin Heidelberg.
[2] Clarke, N. L., and Furnell S. M. 2007. Advanced user authentication for mobile devices. computers & security 26, no. 2: 109-119.
[3] Bhattacharyya, D., Rahul R., Farkhod Alisherov A., and Minkyu Ch. 2009. Biometric authentication: A review. International Journal of u-and e-Service, Science and Technology 2, no. 3 :13-28.
[4] Crawford, H., Karen R., and Tim, S. 2013. A Framework for Continuous, Transparent Mobile Device Authentication." Computers & Security.
[5] Briggs, P., Olivier, PL. 2008. Biometric daemons: authentication via electronic pets. In: Proceedings of conference on human factors in computing systems. ACM; p. 2423e32.
[6] Kochetkov, A. 2013. Cloud-based biometric services: just a matter of time." Biometric Technology Today 2013, no. 5: 8-11.
[7] Voth, D. 2003. Face recognition technology. Intelligent Systems, IEEE 18, no. 3 (): 4-7.
[8] Fernando, N., Seng W. L., and Wenny R. 2013. Mobile cloud computing: A survey. Future Generation Computer Systems 29, no. 1 : 84-106.
[9] Wu, K., Jen-Chun L., Tsung-Ming L., Ko-Chin Ch., and Chien-Ping Ch. 2013. A secure palm vein recognition system. Journal of Systems and Software 86, no. 11: 2870-2876.
[10] Wang, Xu., Fangxia G., and Jian-feng M. 2012. User authentication via keystroke dynamics based on difference subspace and slope correlation degree. Digital Signal Processing 22, no. 5: 707-712.
[11] Gomez-Barrero, M., Javier G., and Julian F. 2013. Efficient Software Attack to Multimodal Biometric Systems and its Application to Face and Iris Fusion. Pattern Recognition Letters.
[12] Guo, J., Chih-Hsien H., Yun-Fu L., Jie-Cyun Y., Mei-Hui Ch., and Thanh-Nam L. 2012. Contact-free hand geometry-based identification system. Expert Systems with Applications 39, no. 14 : 11728-11736.
[13] Bhatt, Sh., and Santhanam, T. 2013. Keystroke dynamics for biometric authentication�A survey. In Pattern Recognition, Informatics and Medical Engineering (PRIME), International Conference on, pp. 17-23. IEEE.
[14] Araujo, L. C, Luiz, S. J., Miguel, G. L., Lee, L. L., and Jo�o B. T. Y. 2005. User authentication through typing biometrics features. Signal Processing, IEEE Transactions on 53, no. 2: 851-855.
[15] Pursani, M. P. J., and Ramteke, P. L. 2013. Mobile Cloud Computing. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) 2, no. 4: pp-1512.
[16] Altinkemer, K., and Tawei W. 2011. Cost and benefit analysis of authentication systems. Decision Support Systems 51, no. 3: 394-404.
[17] Khan, A. N., Mat Kiah M. L., Samee U. Kh., and Madani S. A. 2012. Towards secure mobile cloud computing: A survey. Future Generation Computer Systems.

[18] Dharamjeet Singh,Surabhi Shukla,�Cloud�s SaaS Security by Biometric Concept�;International Journal of Computer Science and Engineering 2014; Review r.
[19] www.dialogic.com/12023-cloud-computing-wp
[20] P. Syam Kumar, R. Subramanian and D. Thamizh Selvam.� Ensuring Data Storage Security in Cloud Computing using Sobol Sequence�; 2010 1st International Conference on Parallel, Distributed and Grid Computing (PDGC - 2010).
[21] 4. NIST/SP800-144.
[22] Kaspersky Internet Security
[23] Mahnoush Babaeizadeh, Majid Bakhfiari, Mohd Aizani Maarof.�Keystroke Dynamic Authentication in Mobile Cloud Computing�;2014 International Journal of Computer Applications 2014; Volume 90- Number 1.
[24] Zirra Peter Buba, Gregory Maksha Wajiga,�Cryptographic Algoriths for Secure Data Communication�;International Journal of Computer Science and Security(IJCSS), Volume(5) :Issue(2) :2011.
[25] Hassan Takabi, James B. D. Joshi, Gail-Joon �Security and Privacy Challenges in Cloud Computing Environments�1540-7993/10/IEEE.

S. Shukla, D. kumar, "Cloud�s Software- Security as a Service(S-SaaS) via Biometrics," International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.119-124, 2014.

IPv6 mobility management is one of the most challenging research topics for an efficient support of global roaming of mobile nodes (MNs) in next-generation wireless networks. The Internet Engineering Task Force (IETF) has developed Mobile IPv6 (MIPv6) and its proposed enhancements, i.e., Fast Handovers for Mobile IPv6 (FMIPv6) and Hierarchical Mobile IPv6 (HMIPv6) as host-based mobility management protocols. Recently IETF working group has standardized network-based mobility management protocols, such as, Proxy Mobile IPv6 (PMIPv6) and Fast Proxy Mobile IPv6 (FPMIPv6). Unlike host-based mobility management protocols PMIPv6 and FPMIPv6 have significant features and enable IP mobility for a host without requiring its participation in any mobility-related signaling. In this literature, host-based IPv6 mobility management protocols including the network-based PMIPv6 and FPMIPv6 are analyzed and compared. Each IPv6 mobility management protocol�s characteristics and performance indicators are identified by examining handover operations in terms of handover latency, handover blocking probability and packet loss. The conducted analysis in this literature can be used to facilitate decision making in development for a new mobility management protocol.

Fast mobile IPv6 (FMIPv6), fast proxy mobile IPv6 (FPMIPv6), handover, hierarchical mobile IPv6 (HMIPv6), latency, mobile IPv6 (MIPv6), proxy mobile IPv6 (PMIPv6)

[1] D. Johnson, C. Perkins, and J. Arkko, �Mobility support in IPv6,� IETF RFC 3775, Jun 2004.
[2] V. Vassiliou, Z. Zinonos, �An Analysis of the Handover Latency Components in Mobile IPv6�, Journal of Internet Engineering, vol. 3, no. 1, Dec 2009.
[3] Soliman, C. Castelluccia, K. ElMalki, and L. Bellier, �Hierarchical mobile ipv6 mobility management HMIPv6,� IETF RFC 4140, Aug 2005.
[4] M.H. Habaebi, �Macro/micro-mobility fast handover in hierarchical mobile IPv6�, Computer Communications, Volume 29, Issue 11, 26 July 2006, Page 2168.
[5] R. Koodli, �Fast handovers for mobile IPv6,� IETF RFC 4068, Jun 2009.
[6] M.Torrent-Moreno. �A Performance Study of Fast Handovers for Mobile IPv6�, IEEE International Conference on Local Computer Networks, 2003.
[7] S. Gundavelli, K. Leung, V. Devarapalli, K. Chowdhury, and B. Patil, �Proxy mobile IPv6,� IETF RFC 5213, Aug 2008.
[8] H. Yokota, K. Chowdhury, R. Koodli, B. Patil, and F. Xia, �Fast handovers for proxy mobile IPv6,� IETF RFC 5949, Sep 2010.
[9] G. Heijenk, M.S. Bargh, J. Laganier, and A.R. Prasad "Reducing Handover Latency in Future IP-based Wireless Networks: Fast Proxy Mobile IPv6," In Second ERCIM workshop on eMobility, 30 May 2008.
[10] C. Makaya and S. Pierre, "An Analytical Framework for Performance Evaluation of IPv6-Based Mobility Management Protocols," IEEE Trans. Wireless Comm., vol. 7, no. 3, pp. 972-983, Mar. 2008.
[11] K. S. Kong, W. Lee, Y. H. Han, and M. K. Shin, "Handover Latency Analysis of a Network-Based Localized Mobility Management Protocol," IEEE International Conference on Communication, Beijing, China, pp. 5838-5843, 2008.
[12] J. Lee, J. Bonnin, I. You, and T. Chung, �Comparative handover performance analysis of IPv6 mobility management protocols,� IEEE Transactions on Industrial Electronics, vol. 60, no. 3, pp. 1077�1088, Mar 2013.

F.T. Zohra, S. Azam, Md.M. Rahman, "Overview of IPv6 Mobility Management Protocols and their Handover Performances," International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.125-133, 2014.

ERP systems way from the manufacturing sector are entering rapidly into universities and colleges. ERP now is experiencing the transformation that will make it highly integrated, more intelligent, collaborative, and web-enabled. Reason for choosing ERP for education are accessing information from paper files is difficult task, lack of means to access old records, wastage of hundreds of hours by staff each month manually entering information or performing task that could be handled automatically like evaluation & generating results. E-college will solve these lacunas and help educational institutes to save their valuable time. This paper provides a limited set of modules and their implementation which are required by educational institutes to function smoothly.

Enterprise resource planning, higher education, Modules, implementation, web enabled

[1] Leo Zornada MSc. & Tamara Bertok Velkavrh MSc. �Implementing ERP Systems in Higher Education Institutions�, 27th Int. Conf. Information Technology Interfaces ITI 2005, June 20-23, 2005, Cavtat, Croatia
[2] Alemayehu Hailu and Syed Rahman, �Evaluation of Key Success Factors Influencing ERP Implementation Success,� 2012 IEEE Eighth World Congress on Services, 978-0-7695-4756-5/12 $26.00 � 2012 IEEE DOI,10.1109/SERVICES.2012.74
[3] Wei She and Bhavani Thuraisingham, �Security for Enterprise Resource Planning Systems,� Information Systems Security, 16:152�163, 2007 Copyright � Taylor & Francis Group, LLC ISSN: 1065-898X print/1934-869X online DOI: 10.1080/10658980701401959
[4] Ahed Abugabah & Louis Sanzogni, �Enterprise Resource Planning (ERP) System in Higher Education: A literature Review and Implications,� International Journal of Human and Social Sciences, 5:6 2010.
[5] R. Addo-Tenkorang and P. Helo, �Enterprise Resource Planning (ERP): A Review Literature Report,� Proceedings of the World Congress on Engineering and Computer Science 2011 Vol II WCECS 2011, October 19-21, 2011, San Francisco, USA, ISBN: 978-988-19251-7-6, ISSN: 2078-0958 (Print); ISSN: 2078-0966 (Online)
[6] P.Shanthi Bala, "Intensification of educational cloud computing and crisis of data security in public cloud," International Journal of Computer Science and Engineering (IJCSE), Vol. 02, No. 03, 2010, 741-745.
[7] Rajan Vohra & Nripendra Narayan Das, �Intelligent Decision Support Systems For Admission Management In Higher Education Institutes,� International Journal of Artificial Intelligence & Applications (IJAIA), Vol.2, No.4, October 2011.

A. Gutte, N. Kate, A. Hulikere, S. Kokate, "E-College: An ERP for Educational Institute," International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.134-138, 2014.

Importance of data mining has been increased rapidly for business domains like marketing, financing and telecommunications. The business organizations urgent need to discover the valuable information and knowledge from the huge data. We can analyze a customer�s purchasing habit or their interests of buying items in market basket analysis. This kind of discovery may help in developing the better marketing strategies. Depending on this strategy this survey paper is based on developing fast processing recommendation engine which suggests the customers for purchasing the needed commodities with the main item. This survey paper focuses on different important association rule mining algorithms like Apriori, FP-Growth and Weighted FP-Growth and on enhancing the processing speed of positive and negative associations rule mining.

Data Mining, Data Processing, Outsource Services, Market basket analysis, Ajax Technique

[1]. Samet Cokpınar, Taflan _Imre Gundem �Positive and negative association rule mining on XML data streams in database as a service concept �, ELESVIER 39 ,page no(7503�7511) ,Jan 2012.
[2]. Rakesh Agrawal and Ramakrishnan Srikant, �Fast algorithms for mining association rules�, 20th VLDB Conference Santigo Chile ,page no(487-499), Sep 1994.
[3]. Jiawei Han, Jian Pei, Yiwen Yin ,�Mining Frequent Patterns without Candidate Generation� ACM SIGMOD International onference on Management of Data, Dallas, Texas, United States.
[4]. Younghee Kim, Wonyoung Kim and Ungmo Kim, �Mining Frequent Itemsets with Normalized Weight in Continuous Data Streams�, Journal of Information Processing Systems, Vol.6, No.1, page no (79-90) , March 2010.
[5]. Unil Yun and John J. Leggett, �WFIM: Weighted Frequent Itemset Mining with a weight range and a minimum weight� ,SIAM, page no (636-640).
[6]. V.Vidya �Mining Weighted Association Rule using FP � tree�, IJCSE , Vol. 5 No. 08,page no (741-752), Aug 2013
[7]. Raorane A.A. Kulkarni R.V. and Jitkar B.D, �Association Rule � Extracting Knowledge Using Market Basket Analysis� , Research Journal of Recent Sciences,Vol. 1(2), page no(19-27), Feb. 2012.
[8]. Yongmei Liu and Yong Guan, �FP-Growth Algorithm for Application in Research of Market Basket Analysis �,IEEE International Conference on Computational Cybernetics, page no(269�272), Nov 2008.
[9]. Chit Nilar Win, Khin Haymar Saw Hla ,� Mining frequent patterns from XML data�, APSITT, page no (208�212), 2005.

[10]. Ozan �nay Taflan !.G�ndem �A Survey on Querying Encrypted XML Documents for Databases as a Service� SIGMOD Record, Vol. 37, No. 1,page no(12-20),March 2008 .
[11]. Xindong WU,Chengqi Zhang and Shichao Zhang,� Efficient Mining of both Positive and Negative Association Rules�, ACM Transaction on Intenational System,Vol 22 No 3, page no(381-405), July 2004.
[12]. Sun Zhaoyun,Zhang Xiaobo,Zhao Li , �The Web Asynchronous Communication Mechanism Research Based on Ajax� , 2nd international Conference on Education Technology and Computer (ICETC), Vol 3, page no(370-372), 201 0.
[13]. Supratik Mukhopadhyay, Ramesh Bharadwaj, Hasan Davulcu, �Functional �AJAX� in Secure Synchronous Programming�, Proceedings of the 44th Hawaii International Conference on System Sciences, IEEE , 2011.
[14]. Wang Jing and XU Feng , �The Research of Ajax Technique Application Based on the J2EE�, Foundation project: The Design of the System for Zhanjiang Meteorological Forecast (0910262), IEEE, 2010.

V. Kavi, D. Joshi , "A Survey on Enhancing Data Processing of Positive and Negative Association Rule Mining," International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.139-143, 2014.

The amount of data and its dynamicity makes it impossible to crawl the World Wide Web (WWW) completely. It�s a challenge in front of crawlers to crawl only the relevant pages from this information explosion. Thus a focused crawler solves this issue of relevancy to a certain level, by focusing on web pages for some given topic or a set of topics. Also a focused crawler with a page change detection policy can help in narrowing down the search to only newer pages, and thus eliminates risk of redundancy and missing updated data. This paper proposes a policy for design of a focused crawler with web page change detection policy.

Web Crawler, Focused Crawler, World Wide Web(WWW),Content Analysis, Link Scoring, Change Detection

[1] Mahdi Bazarganigilani, Ali Syed and Sandid Burki, �Focused web crawling using decay concept and genetic programming�, published in International Journal of Data Mining & Knowledge Management Process (IJDKP), Vol.1, No.1, Page no(1-12), January 2011.
[2] 3Swati Mali and B B Meshram, �Focused Web Crawler with Page Change Detection Policy�, published in International Journal of Computer Applications (IJCA) proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET), No 9 Article 9, Page No 51-56, 2011.
[3] 4DivakarYadav, AK Sharma, Sonia Sanchez-Cuadrado, Jorge Morato, �an approach to design incremental parallel webcrawler�, published in Journal of Theoretical and Applied Information Technology, Volume 43 No 1, Page no:(8-29), 15 September 2012.
[4] 6Anshika Pal, Deepak Tomar and S.C. Shrivastava, �Effective Focused Crawling Based on Content and Link Structure Analysis�, published in (IJCSIS) International Journal of Computer Science and Information Security, Vol. 2, no. 1, Page No: (1-5), June 2009.
[5] 7Ioannis Avraam and Ioanni Anagnostopoulos, �A Comparison over Focused Web Crawling Strategies�, published in Panhellenic Conference on Informatics(IEEE), Print ISBN 978-1-61284-962-1,Page No: (245-249), September 2011.
[6] 9Weicheng Ma, Xiuxia Chen and Wenqian Shang, �Advanced deep web crawler based on Dom�, published in IEEE Fifth International Joint Conference on Computational Sciences and Optimization, print ISBN 978-1-4673-1365-0, Page No: (605-609), June 2012
[7] Mejdl S. Safran, Abdullah Althagafi and Dunren Che, �Improving Relevance Prediction for Focused Web Crawlers�, published in IEEE/ACIS 11th International Conference on Computer and Information Science, print ISBN 978-1-4673-1536-4, page no: (161-166), May 2012.
[8] Jatinder Manhas, �A Study of Factors Affecting Websites Page Loading Speed for Efficient Web Performance�, published in International Journal of Computer Sciences and Engineering (IJCSE), Vol-1, Issue-3, Nov 2013.

H.P. Trivedi, G.N. Daxini, J.A. Oswal, V.D. Gor, S. Mali, "An Approach to Design Personalized Focused Crawler," International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.144-147, 2014.