iosr-JCE   Volume-10 ~ Issue-4

Abstract: Software engineers and architects have been faced with the problem of IT system complexity for some years. The challenge to build highly complex IT systems, ensure that these systems meet the needs of increasingly complex business processes and do all this in a way that allows everything to adapt quickly to changing market condition coupled with rapid development in information technology has been a problem facing the development and building of workable and functional information systems. Research on this problem has been conducted and it was found to cause large cost of software development project, schedule overrun and outright software project failure. A novel architecture framework was developed as a tool for resolving and managing IT system complexity in the enterprise as the end objective. Comprehensive business system frameworks are necessary to capture the entire complexity of such systems. The framework provides the conceptual foundation necessary for building and managing the integral business system and all its components and also provides an integrated description of enterprise information systems that comprises of the back-end systems, front-end systems, management tools and communication system. The framework provides a detailed process of information system development and defines the necessary subsystems that make up the integrated enterprise information system.

Keywords and phrases: Complexity; Information System; Enterprise Architecture Frameworks Enterprise Architecture, Information Technology

[1]. Oracle (2009). An Oracle White Paper in Enterprise Architecture October.
[2]. Booch G (2005). "The Complexity of Programming Models". Keynote talk at AOSD 2005, Chicago, Il, March 14-18, 2005.
[3]. Card D. N. and R. L. Glass (1990., Measuring Software Design Quality, Englewood Cliffs, NJ:Prentice Hall.
[4]. Coad P. and E. Yourdon (1991). Object-Oriented Design, Englewood Cliffs, NJ:Prentice Hall.
[5]. Chan, J.O (2004). The Analytic Enterprise Model for the Value Chain. Communications of the International Information Management Association, 4(4), 59-69.
[6]. Chan, J.O (2008). An Integrated Architecture for Enterprise Relations Management. Communication of International Information Management Association, 8(2), 55-66.
[7]. DoD Architecture Framework Working Group. DoD Architecture Framework, Feb 2004.
[8]. Kemal A. Delic (2002) .Enterprise It Complexity Zuse H. (1990). Software Complexity Measures and Models, New York, NY: de Gruyter & Co

Abstract: A Wireless Sensor Network(WSN) contains short range energy limited terminals/nodes in which multiple nodes participates one by one to transfer data from source node to Base station. Each node appends some amount of delay which degrades the network performance as the jittered behaviour of network may not be allowed in some applications. Again the faulty nature of tandem nodes may create some severe routing scenarios. Concept of Broad Area Sensor Network (BASN) incorporates a real time communication between sensor node and Base station, which helps to optimize the Quality of Service (QoS). Our goal is to do extensive simulation on performance analysis of such sensor networks and its optimization.

Keywords - WSN ,energy limited terminals, jitter, Quality of service(QoS)

[[1] B. Cook, S. Lanzeisera, and K. Pister, "SoC Issues for RF Smart Dust", Proc. of the IEEE, vol. 94, pp. 117-1196, June 2006.

[2] A. Saipulla, B. Liu and J. Wang, "Barrier Coverage with Airdropped Wireless Sensors", Proc. of Miltary Comms Conf, pp. 1-7, 2008.

[3] K. Martinez, J.K. Hart, and R. Ong, "Environmental Sensor Networks", Computer,Vol.37, Iss.8, August 2004.

[4] R. Nemzek, J. Dreicer, and D. Torney, "Distributed Sensr Networks for Detection of Mobile Radioactive Sources," IEEE Nuclear Science Symposium Conference, Vol. 3, pp. 1462-1467, Oct. 19-25 2003.

Abstract: Sequential pattern mining (SPM) is an important data mining task of discovering time-related behaviours in sequence databases. Sequential pattern mining technology has been applied in many domains, like web-log analysis, the analyses of customer purchase behaviour, process analysis of scientific experiments, medical record analysis, etc. Increased application of sequential pattern mining requires a perfect understanding of the problem and a clear identification of the advantages and disadvantages of existing algorithms. SPM algorithms are broadly categorized into two basic approaches: Apriori based and Pattern growth. Most of the sequential pattern mining methods follow the Apriori based methods, which leads to too many scanning of database and very large amount of candidate sequences generation and testing, which decrease the performance of the algorithms. Pattern growth based methods solve all above problems and in addition, it works on projected database which minimize the search space. Paper reviews the existing SPM techniques, compares various SPM techniques theoretically and practically. It highlights performance evaluation of each of the techniques. Paper also highlights limitation of conventional objective measures and focused on interestingness measures. Finally, a discussion of the current research challenges and pointed out future research direction in the field of SPM.

Keywords: Sequential Pattern Mining, Sequential Pattern Mining Algorithms, Apriori based mining algorithm, FP-Growth based mining algorithm

[1] R. Agrawal and R. Srikant, "Fast Algorithms for Mining Association Rules," Proc. 1994 Int‟l Conf. Very Large Data Bases (VLDB ‟94), pp. 487-499, Sept. 1994.

[2] Agrawal R. And Srikant R. "Mining Sequential Patterns.‟, In Proc. of the 11th Int'lConference on Data Engineering, Taipei, Taiwan, March 1995

[3]AYRES, J., FLANNICK, J., GEHRKE, J., AND YIU, T., "Sequential pattern mining using a bitmap representation‟, In Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining-2002.

[4] Brijs, T., Vanhoof, K. and Wets, G. (2003), "Defining interestingness for association rules‟, International Journal of Information Theories and Applications 10(4), 370–376.

[5] M. Garofalakis, R. Rastogi, and K. Shim, "SPIRIT: Sequential pattern mining with regular expression constraints‟, VLDB'99, 1999. [6] Han J., Dong G., Mortazavi-Asl B., Chen Q., Dayal U., Hsu M.-C.,‟ Freespan: Frequent pattern-projected sequential pattern mining‟, Proceedings 2000 Int. Conf. Knowledge Discovery and Data Mining (KDD‟00), 2000, pp. 355-359.

[7] J. Han, J. Pei, and Y. Yin, "Mining Frequent Patterns without Candidate Generation‟,Proc. 2000 ACM-SIGMOD Int‟l Conf. Management of Data (SIGMOD ‟00), pp. 1-12, May 2000.

[8] J. Pei, J. Han, B. Mortazavi-Asi, H. Pino, "PrefixSpan: Mining Sequential Patterns Efficiently by Prefix- Projected Pattern Growth‟, ICDE'01, 2001.

[9] Ramaswamy, S., Mahajan, S. and Silberschatz, A. (1998), On the discovery of interesting patterns in association rules, in "Proceedings of the 24rd International Conference on Very Large Data Bases‟,Morgan Kaufmann Publishers Inc., pp. 368–379.

[10] Srikant R. and Agrawal R.,‟Mining sequential patterns: Generalizations and performance improvements‟, Proceedings of the 5th International Conference Extending Database Technology, 1996, 1057, 3-17.

Abstract: Man being social by nature cannot live in isolation. He feels being in company with other co-humans. So sometimes he wants to connect with himself and most of the other times he wishes to be connected with others at other places through one means or the other. Man's persistent desire to be connected with something, or with somebody at a distance sometimes even across the globe any times has paved a way to the numerous inventions like Radio, Television, Telephone, Mobile, Internet culminating in the wireless networks. The mobile Adhoc Network popularly called in recent times MANET's is a unique development in modern times. It has converted the whole world into a global village for peoples to exchange information and diffuse knowledge. In this paper on "MOBILE ADHOC INETWORKS" the writer makes an attempt to explain MANET's in terms of its definition, characteristics, routing, protocols, dynamic source routing and its characteristics etc.

Keywords: Internet, network researchers, topology, traditional routing, protocols, assumption, bandwidth, simulation, quantitative study, emulation, stability criterion, dynamic source routing, mobile computing, internet engineering task force, autonomous system.

[1]. T. Lin, S.F. Midkiff and J.S. Park "A Framework for Wireless Adhoc Routing Protocols in Proc. Of IEE Wireless Communication and Networking Conference (WCNC) Vol 2. PP 1162 – 1167-2003
[2]. A. Boukerche – "A Simulation based Study of on Demand Routing Protocols lfor adhoc wireless networks. In Proc. 34th Annual simulation symposium PP 85-92 – 2001
[3]. C. Bettstetter and C. Wagner "The Spatial node distribution of the random waypoint mobility model in Proc. Of the 1st German Workshop on Mobile Adhoc Networks, Ulm, Germany Gi Lecture Notes in Informatics No. PP 41-58, 2002
[4]. R.G. Ogier, "Efficient Routing Protocols for Packet-Radio Networks Based on Tree Sharing" in Proc. Of the 6tth IEEE intl. workshop on Mobile Multimedia Communications PP 104-113, 1999
[5]. Vikram Goyal, Shyam K. Gupta, Ananda Gupta. "Malafide Intention and its mapping to Privacy Policy Purposes for Masquerading" in Proc. 10th International Data Base Engineering and Applications Symposium (IDEAS 2006) Pages 311-312, 2006

Abstract: The National Institute of Standards and Technology (NIST) defined cloud computing as a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or cloud provider interaction [Def:1]. Cloud computing has the potential to change how organizations manage information technology and transform the economics of hardware and software at the same time. Cloud computing promised to bring a new set of entrepreneurs who could start their venture with zero investment on IT infrastructure. How ever this captivating technology has security concerns which are formidable. The promises of cloud computing, especially public cloud can be shadowed by security breaches which are inevitable. As an emerging information technology area cloud computing should be approached carefully. In this article we will discuss the security and privacy concerns of cloud computing and some possible solutions to enhance the security. Based on the security solutions suggested i have come up with a secured framework for cloud computing.

Keywords: Cloud computing, Security and Privacy, Information Technology, IT, Software as a service, Platform as a service

...............,

Abstract: Efficient execution of top-k queries is increasingly becoming a major challenge for relational database technology. Top-k query has emerged as a key requirement in modern application. In these applications, efficient and adaptive evaluation of top-k queries is an integral part of application semantics. In this paper we discuss a query optimization framework of top-k queries that fully integrates rank-join operators. Ranking queries produce results that are ordered on some computed score. A key property of top-k queries is that, users are interested only in the first k results and not in total ranking of all query results. This property directly impacts the optimization of top-k queries by optimizing for the first k results. Traditionally, most real world database systems offer the feature of first n row optimization

[1] S. Chaudhury, R. Ramakrishnan and G. Weikum (2005), Integrating db and ir technologies, CIDR.

[2] Ilyas, I.F. and W.G. Aref (2006), Adaptive Rank aware Query Optimization in Relational Databases, ACM Transactions on Database Systems.

[3] Ilyas, I.F. and R. Shah (2004), Rank-aware Query Optimization,SIGMOD, June13-18, Paris, France.

[4] Ilyas, I.F. and C. Li, 2005. Ranksql: Query algebra and optimization for relational top-k queries.SIGMOD 2005, June 1416, Baltimore, Maryland, USA.

[5] Ilyas, I.F. and W.G. Aref, 2003. Supporting Top-k Join Queries in Relational Databases. Proceedings of the 29th VLDB Conference, Berlin, Germany.

[6] M.A. Kashem, A S Chowdhury, R Deb, M Jahan (2010), Query Optimization on Relational Databases for Supporting Top-k Query Processing techniques, JCIT

Abstract: Ad-hoc networks have mass of applications; though, a dynamic problem regarding their security aspects must be answered in order to realize these applications. Validating the source and ensuring the integrity of the message traffic become an essential constraint for the operation and management of the network. We focus on the security problem of protecting the network connectivity between nodes in ad-hoc network. New nodes start to contribute in the network as guests; they can only become full members with a network signed certificate after their authenticity has been warranted by some other members. In this paper we introduce routine of multicast Protocol for tired authentication between the multilevel of ad-hoc network. In this proposed protocol Central Authority with trilateral authentication for managing key authentication and certification process which leads to increase the security and reliability of the network.

Keywords---Central Authority, Multicast Security, Wireless Network, Tiered Network, WANET.

[1] Perrig, R. Canetti, D. Song, and D.Tygar, "Efficient authentication and signing of multicast streams over lossy channels," in Proc. 2000 IEEE Symposium Security Privacy.
[2] A.M. Hegland, E. Winjum, S. F. Mjolsnes, C. Rong, O. Kure, and P. Spilling, "A survey of key management in ad hoc networks," IEEE Commun. Surveys & Tutorials, vol. 8, no. 3, pp. 48–66, Dec. 2006.
[3] R. Safavi-Naini and H. Wang, "Multi-receiver authentication codes: models, bounds, constructions, and extensions," Inf. Computation, vol. 151, no. 1–2, pp. 148–172, May 1999.
[4] J. Y. Yu and P. H. J. Chong, "A survey of clustering schemes for mobile ad hoc networks," IEEE Commun. Surveys & Tutorials, vol. 1, no. 1, pp. 31–48, 2005.
[5] P. B. Velloso, et al., "Trust management in mobile ad hoc networks using a scalable maturity-based model," IEEE Trans. Network Service Management, vol. 7, no. 3, Sep. 2010.
[6] L. Junhai, Y. Danxia, X. Liu, and F. Mingyu, "A survey of multicast routing protocols for mobile ad-hoc networks," IEEE Commun. Surveys & Tutorials, vol. 11, no. 1, pp. 78–91, first quarter 2009.
[7] M. Younis, O. Farrag, and S. Lee, "Cluster mesh based multicast routing in MANET: an analytical study," in Proc. 2011 IEEE International Conf. Commun..
[8] K. Marzullo and S. Owicki, "Maintaining the time in a distributed system," in Proc. 1983 ACM Symposium Principles Distrib. Computing.
[9] R. Canetti et al., "Multicast security: a taxonomy and efficient constructions," in Proc. 1999 IEEE INFOCOM.
[10] Y. Challal, H. Bettahar, and A. Bouabdallah, "A taxonomy of multicast data origin authentication, issues and solutions," IEEE Commun. Surveys & Tutorials, vol. 6, no. 3, pp. 34–57, 2004.

Abstract: A watermarking technique that hinders camcorder piracy in Theaters by implementing the playback control is set forth. In this technique we watermark a finite number of frames so that any acquiescent video player cannot play the video. The watermarking technique should be impervious to any kind of geometric alterations and it should be a lossless compression, which will prevent the re-recorded video to be played in any of the video players.The IWT is not only computationally faster and more memory-efficient but also more suitable in lossless data-compression applications. The IWT enables you to reconstruct an integer signal perfectly from the computed integer coefficients. This method is not only simple to implement but is also more efficient than the other proposed watermarking techniques..

[1] Mot. Picture Assoc. Amer., 2007. [Online]. Available: http://www.mpaa.org/piracy.asp.

[2] P. B. Schneck, "Persistent access control to prevent piracy of digital information," Proc. IEEE, vol. 87, no. 7, pp. 1239–1249, Jul. 1999.

[3] I. J. Cox, M. L. Miller, and J. A. Bloom, Digital Watermarking. San Francisco, CA: Morgan Kaufmann, 2002.

[4] J. J. K. O'Ruanaidh and T. Pun, "Rotation, scale and translation invariant digital image watermarking," in Proc. Int. Conf. Image Processing, 1997, pp. 536–539.

[5] C.-Y. Lin, M.Wu, J. A. Bloom, I. J. Cox, M. L. Miller, and Y. M. Lui, "Rotation, scale, and translation resilient watermarking for images," IEEE Trans. Image Process., vol. 10, no. 5, pp. 767–782, May 2001.

Abstract: In this paper we are proposing a fast and efficient algorithm to track humans in a indoor surveillance video. Here we have used hog features and correlation based method to track humans in a surveillance video. Strips on the borders of a frame is analyzed to know the entry of new objects in to the frame. This algorithm can applied to real time systems due to the low time complexity of the system. Keywords – Image correlation, human tracking, hog features..

[1] Papageorgiou, C., Poggio, T. Trainable Pedestrian Detection, Center for Biological and Computational Learning Artificial Intelligence Laboratory MIT, 1999.

[2] Kennedy, J., Eberhart, R. Particle Swarm Optimization, IEEE Inter. Conference on Neural Networks, 1995.

[3] Mohan, A. Object Detection in Images by Components, MIT AI Memo, 1664 (CBCL Memo 178), June 1999.

[4] Papageorgiou, C., Oren, M., and Poggio, T., A General Framework for Object Detection, Proc. International Conf. Computer Vision, Jan. 1998.

[5] Papageorgiou, C., Poggio, T. A Trainable System for Object Detection, International Journal of Computer Vision 38(1), 15–33, Kluwer Academic Publishers. Manufactured in The Netherlands, 2000. [

6] Levi, K., Weiss, Y., Learning Object Detection from a Small Number of Examples: The Importance of Good Features, Proceeding of CVPR(2): 53-60, 2004.

[7] O. Tuzel, F. Porikli, and P. Meer. Human detection via classification on riemannian manifolds. In Conf. Comp. Vis. & Patt. Recognition, 2007.

[8] H. Sidenbladh. Detecting human motion with support vector machines. In Int. Conf. on Pattern Recognition (ICPR), volume 2, pages 188–191,2004.

[9] C. Wren, A. Azarbayejani, T. Darrell, and A.P. Pentland. Pfinder: Realtime tracking of the human body. Trans. Pattern Anal. Machine Intell., 19(7):780–785, July 1997.

[10] D. M. Gavrila and V. Philomin. Real-time object detection for smart vehicles. Coference on Computer Vision and Pattern Recognition (CVPR), 1999.

Abstract: E-learning is a platform that provides materials online with the objective of improving the users' teaching and learning experience. The main objective of this paper is to provide security to users' passwords within the E-learning Password Management System (EPMS) in order to protect the database from hackers. The protection process is done by implementing a symmetric encryption algorithm named International Data Encryption Algorithm (IDEA) on the passwords. The algorithm will be improved by modifying the size of the same secret key that is used in both the encryption and decryption operations of the data. The proposed algorithm is known as Double-Secure IDEA.

Keywords – Database Security, E-Learning, Symmetric Encryption, IDEA, Double-Secure IDEA

[1] E E. Thambiraja, G. Ramesh, and R. Umarani, A Survey on Various Most Common Encryption Techniques, International Journal of Advanced Research in Computer Science and Software Engineering, 2(7), 2012, 226-233.
[2] Z. Yong-Xia, The Technology of Database Encryption, Proc. 2nd IEEE International Conference on Multimedia and Information Technology, Vol. 2, 2010, 268-270.
[3] H. S. Chang, International Data Encryption Algorithm, CS-627-1, Fall 2004. Retrieved from http://scholar.googleusercontent.com/scholar?q=cache:WXJPT0eEM7EJ:scholar.google.com/+International+Data+Encryption+Algorithm&hl=en&as_sdt=0,5 on 15 February 2013.
[4] A. Biryukov, J. N. Jr, B. Preneel, and J. Vandewalle, New Weak-Key Classes of IDEA, Proc. 4th ICICS International Conference on Information and Communications Security, Singapore, 2002, 315-326.
[5] X. Lai, and J. Massy, A proposal for a new block encryption standard, Proc. Workshop on the Theory and Application of Cryptographic Techniques Aarhus, Denmark, 1990, 389-404.
[6] O. Cheung, K. Tsoi, P. Leong, and M. Leong, Tradeoffs in parallel and serial implementations of the international data encryption algorithm IDEA, Proc. 3rd International workshop, Paris, France, 2001, 333-347.
[7] M. Wang, and Y. Que, The Design and Implementation of Passwords Management System Based on Blowfish Cryptographic Algorithm, Proc. 9th IEEE International Forum on Computer Science-Technology and Applications, Vol. 2, 2009, 24-28.
[8] N. H. M. Alwi, and I. Fan, E-learning and information security management, International Journal of Digital Society, 1(2), 2010, 148-156.
[9] J. Eklund, M. Kay, and H. M. Lynch, E-learning: emerging issues and key trends: a discussion paper, Australian National Training Authority, 2013, 2-45.
[10] B. Schneier, Applied cryptography: protocols, algorithms, and source code in C ( John Wiley & Sons, 2007).

Abstract:A new method for key generation using Data Encryption Standard (DES) is proposed in order to make it more secure for Online Examination System (OES). Privacy and security are crucial in an OES. Privacy represents the ability to maintain a personal space such that there is certain user control on what and how much of personal information can be shared with others. Security describes the level of data integrity and protection the system offers. There are two main factors that affect the student's privacy and security in an OES: exam score and impartiality. The exam score is encrypted before being saved in the database and can only be accessed by the respective authorized student. Impartiality is accomplished by using the proposed cryptography scheme that encrypts the student's identification before sending the paper to the examiner for grading.

Keywords – Online Examination, Privacy, Cryptography Scheme, DES

[1] R. Raitman, L. Ngo, N. Augar, and W. Zhou, Security in the online e-learning environment, Proc. Fifth International Conference on Advanced Learning Technologies (ICALT), 2005, 702-706.
[2] D.Manivannan and R.Sujarani, Light weight and secure database encryption using TSFS algorithm, Proc. International Conference on Computing Communication and Networking Technologies (ICCCNT), 2010, 1-7.
[3] H.Tan and S. Hou, Design and development of the universal testing system based on LAN, Journal of Central South University, 31(4), 367-370.
[4] Z.Liu, L.Wang and M.Dong, Design and implementation of test paper reviewing system for NIT network-based test, Journal of Control Engineering of China, 11(2), 108-110.
[5] R.Hundhausen, S.Borg, C.Francis and K.Wilcox, Building web applications with ADO. net and XML web services (2003).
[6] L.Jun, Design of Online Examination System Based on Web Service and COM, Proc. 1st International Conference on Information Science and Engineering (ICISE), 2009, 3276-3279.
[7] L.Zhang, Y.Zhuang, Z.Yuan and G. Zhan, A Web-Based Examination and Evaluation System for Computer Education, Proc. Sixth International Conference on Advanced Learning Technologies (ICALT'06), 2006.
[8] P.Guo, H.Yu and Q.Yao, The Research and Application of Online Examination and Monitoring System, Proc. IEEE International Symposium on IT in Medicine and Education , 2008, 497-502.
[9] L.Siyao and G.Qianrang, The Research on Anti-Cheating Strategy of Online Examination System, Proc. 2nd international conference in Artificial intelligence, 2011, 1738-1741.
[10] A.Olufisoye and A.Ola, An Integrated E-Learning Examination Model Using Combined MCQ and Essay Based Full Blind Marking Assessment Technique, Journal of Automation and Control Engineering, Vol. 1, No. 2, 2013.

Abstract: Mobile Ad-hoc Network (MANET) special characteristics is an inestimable addition to traditional networking technologies, and is presently under active research & development .MANET are basically peer-to-peer, multihop network which is a group of wireless mobile hosts forming a transient network that is having no fixed infrastructure. This paper encompasses the key studies carried out so far and describes all the parameters for simulation. In particular, draw comparisons among different routing protocols: Bellman-Ford, AODV, DSR, LAR1, WRP, FSR and ZRP based on the performance metrics like PDR, end-to-end delay and throughput. The study is carried out to investigate various statistics and highlights behavior of different routing protocols for several MAC layer protocols such as 802.11, CSMA, TSMA which gives rise to various performance issues using GloMoSim simulation environment. Finally, results show the unusual behavior when varying the number of nodes in the network layout and effects of switching among datalink models.

Keywords - ROUTING PROTOCOLS, AODV, DSR, LAR1, WRP, ZRP

[1] Perkins, C.E. and E.M. Royer. Ad hoc on-demand distance vector routing (AODV), In Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications, New Orleans, LA; 1999.

[2] Perkins, C.E., E.M. Royer, and S.R. Das, Ad hoc on demand distance vector (AODV) routing , IETF Internet Draft, 2003.

[3] Johnson, D.B., D.A. Maltz, and J. Broch, DSR the dynamic source routing protocol for multihop wireless ad hoc networks, in C.E. Perkins (Ed.). Ad Hoc Networking. Reading, MA: Addison-Wesley; 2001.
[4] J.Broch,D. Johnson, and D. Maltz, The dynamic source routing protocol for mobile ad hoc networks, IETF Internet draft 2003. Available from: http://www.cs.cmu.edu/dmaltz/internetdrafts/draft-ietf-manet-dsr-09.txt.

[5] Ko, Y.B. and N.H. Vaidya., Location-Aided Routing (LAR) mobile ad hoc networks, In Proceedings of ACM/IEEE MOBICOM '98. Dallas, TX; 1998.

[6] Ko, Y.B. and N.H. Vaidya, Location Aided Routing (LAR) in mobile ad hoc networks. Wireless Networks 2000;6 (4):307 321.

[7] Lee, S.J., et al., Selecting a routing strategy for your ad hoc network in Symposium on Applied Computing, Seoul, Korea: Elsevier; 2002.

[8] Pei, G., M. Gerla, and T.-W. Chen. , Fisheye state routing: a routing scheme for ad hoc wireless networks, Proceedings of the IEEE International Conference on Communications. New Orleans, LA; 2000, pp. 70–74

[9] Nicklas Beijar, Zone Routing Protocol (ZRP), Networking Laboratory ,Helsinki University of Technology ".

[10] A. K. Pandey, H. Fujinoki, "Study of MANET routing protocols by Glomosim simulator" , International Journal of Network Management, Volume 15, 2005, pp. 393-410

Abstract: A feedforward neural network is a computing device whose processing units (the nodes) are distributed in adjacent layers connected through unidirectional links (the weights).Feedforward networks are widely used for pattern recognition. Here two feedforward networks are taken into consideration, Multi Layer Perceptron and Radial Basis Network. while designing these networks problem involves in finding the architecture which is efficient in terms of training time. In this paper different data samples will be presented to RBF and Multi Layer network and the best network selection will be done on the basis of minimum time taken by the network for training.

Keywords- Feed forward network, Multi Layer Perceptron Neural Networks, Radial Basis Network, Spread.

[1] Anil K. Jain , Robert P.W. Duin, Jianchang Mao ,"Statistical Pattern Recognition : a Review", IEEE Transactions on pattern analysis and machine intelligence, vol. 22, no. 1, January 2000.

[2] Zekeriya Uykan, Cüneyt Güzelis¸, M. Ertugrul Çelebi, and Heikki N. Koivo "Analysis of Input–Output Clustering for Determining Centers of RBFN", IEEE transactions on neural networks, vol. 11, no. 4, July 2000.

[3] Francesco Lampariello, Marco Sciandrone," Efficient Training of RBF neural networks for pattern recognition", IEEE transactions on neural networks, vol. 12, no. 5, September 2001.

[4] Simon Haykin "NEURAL NETWORK AND LEARNING MACHINE", Tata McGraw Hill Education Private Limited Edition third.

[5] Ilias Maglogiannis, Haralambos Sarimveis, C. T. Kiranoudis, Aristotelis A. Chatziioannou, Nikos Oikonomou, Vassilis Aidinis" Radial Basis Function Neural Networks Classification for the Recognition of Idiopathic Pulmonary Fibrosis in Microscopic Images", IEEE transactions on information technology in biomedicine, vol. 12, no. 1, January 2008.

[6] Indira Hirway," Identification of BPL Households for Poverty Alleviation Programmes" Economic and Political Weekly, 2003,vol 38,no 45,pp 4803-4808.

[7] UCI machine learning dataset http://mlearn.ics.uci.edu/~Mlearn/MLRepository.html.

[8] Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka,"ELEMENTS OF ARTIFICIAL NEURAL NETWORKS",Penram International Publishing(India) Pvt. Ltd,2009.

[9] Jayanta Kumar Basu, Debnath Bhattacharyya, Tai-hoon Kim," Use of artificial neural network in pattern recognition" International Journal of Software Engineering and Its Applications Vol. 4, No. 2, April 2010.

[10] Jing Bi, Kun Zhang, Xiaojing Cheng," Intrusion Detection Based on RBF Neural Network" International Symposium on Information Engineering and Electronic Commerce"2009.