iosr-JCE   Volume-14 ~ Issue-1

Abstract: In the current Cellular IP architecture, only one gateway serves the entire CIP network. So, the gateway is single point of failure for all the mobile hosts who rely on it to be connected to the Internet. Cellular IP requires that a mobile host be using exactly one gateway to the Internet backbone with Mobile IP at a time. When multiply gateways are used in a cellular IP network, the optimal design for the multiple domains is needed. The cellular IP protocol provides better performance for hand-off than other protocol using micro-mobility. A set of base station cluster together on the same cellular IP network. This kind of domain base network is superior to mobile IP in support of routing optimization and QoS. Experiment were conduct to explore load our protocol and survey the packet loss. This result so that the load of control packet is negligible for cellular IP and the number of lost packet can be successfully reduced. This thesis developed to design cellular IP architecture and fault detection mechanism and recover the protocol of cellular IP.

Keywords; Protocol Overview, Network Model, Routing, Handoff, Paging, Security, Implement Cellular IP Network Model, Protocol Details, Simulation Results, Conclusions.

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[8] Andrew T. Campbell, Jaview Gomez, Sanghyo Kim, and Chieh-Yih Wan, "Comparison of IP Micromobility Protocols", IEEE Wireless Communications, February 2002.

[9] Zach D. Shelby, Petri Mahonen, Dionisios Gatzounas, Alessandro Inzerilli, and Ville Typpo, "Cellular IP route Optimization", <draft-shelby-ciprouteoptimizationn-00.txt".

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Abstract: Wimax is a wireless metropolitan area network (MAN) technology that provides interoperability, carrier class broadband wireless connectivity to fixed, portable for the last mile. Wimax (Worldwide interoperability for microwave access) is based on IEEE 802.16 standards that provide wireless access to metropolitan area networks and there are several security problems The Wimax technology has great impact in wireless communication and has notched the top position in the wireless technology. But there still are a lot of securities concerns while using such wireless technologies, especially for Wimax where we have to transfer secure data at high rate from one station to another station. Wimax works at the longer distances so there is more security required to protect the communication from attacks and threats. Wimax is a wireless network which is considered to be more vulnerable to attacks and threats than wired network as data transfer publicity in open areas. For secure the communication in Wimax various algorithms and security protocols are used. The researchers have developed various mechanisms which have made a great impact on secure communications in Wimax. Various encryption and authentication mechanisms are being used for secure communication. The concept of use multiple keys with RSA algorithms using PKM (Privacy & Key management) protocol has been used for secure communication. This concept is extended in this paper by combining PGP (Pretty Good Privacy) protocol with RSA algorithm to further improve the secure communication in Wimax. This paper compares the performance of Hard Wimax and Soft Wimax using PKM and PGP protocols over RSA. The performance is analyzed over NS 2.34 simulator using delay, throughput and packet delivery as performance metrics. Keywords - PGP, PKM, RSA, WIMAX, WMAN.

[1] Lu, K., Qian, Y. and Chen, H. (2007), "A Secure and Service-Oriented Network Control Framework for Wimax Networks", IEEE Communication Magazine, May 2007.

[2] Habib, M., Ahmed, M. (2010), "A Review of Some Security Aspects of Wimax & Converged Network", IEEE 2010 Second International Conference on Communication Software and Networks.

[3] Altaf,A., Ahmed,A.and Javed,M. (2008), "Security Enhancement for Privacy and Key Management Protocol in IEEE 802.16e-2005".IEEE Ninth ACIS International Conference on Software Engineering, Artificial Intelligence,Networking and Parallel/Distributed Computing.

[4] Taha, A., Abdel-Hamid, A., and Tahar, S. (2009), "Formal Verification of IEEE 802.16 Security Sub layer Using Scyther Tool", 2009 ESR Grops France.
[5] http://freewimaxinfo.com/pkm-protocol.html.

[6] Altaf,A., Ahmed,A.and Javed,M. (2008), "Security Enhancement for Privacy and Key Management Protocol in IEEE 802.16e-2005".IEEE Ninth ACIS International Conference on Software Engineering, Artificial Intelligence,Networking and Parallel/Distributed Computing.
[7] http://en.wikipedia.org/wiki/Pretty_Good_Privacy.
[8] http://en.wikipedia.org/wiki/RSA_28algorithm

[9] Yang, F. (2011), "Comparative Analysis on TEK Exchange between PKMv1 and PKMv2 for Wimax", IEEE 2011 School of Information and Security Engineering, Zhongnan University of Economics and Law.

[10] Xu, S., Huang, T., and Matthew, M. (2008), "Modelling and Analysis of IEEE 802.16 PKM Protocol using CasperFRD", IEEE 2008.

Abstract: Image denoising based on ridgelet transforms gives better result in image denoising than standard wavelet transforms. In this research work, the researcher introduces a new approach for image denoising that is based on ridgelets computed in a localized manner and that is computationally less intensive than curvelets, but similar donising performance. The projection of image at a certain angle is computed at a certain angle, but only on a defined slice of the noisy image. After that, ridgelet transform of each slice is computed , to produce the ridgelet coefficients for an image.The denoising operation corresponds to a simple thresholding of these ridgelet coefficients.

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[4] G.Y. Chen, T.D. Bui, A. Krzy˙zak, Image denoising with neighbour dependency and customized wavelet and threshold, Pattern Recognition 38 (1) (2005) 115–124.

[5] D.L. Donoho, A.G. Flesia, in: J. Stoecker, G.V. Welland (Eds.), Digital ridgelet transform based on true ridge functions, Beyond Wavelets, Academic Press, New York, 2001.

[6] G.Y. Chen, T.D. Bui, A. Krzy˙zak, Rotation invariant pattern recognition using ridgelet, wavelet cycle-spinning and Fourierfeatures, Pattern Recognition 38 (12) (2005) 2314–2322.

[7] J.L. Starck, E.J. Candes, D.L. Donoho, Astronomical image representation by the curvelet transform, Astron. Astrophys. 2 (2003) 785–800.

Abstract: Bacterial foraging optimization algorithm has been widely accepted as a global optimization algorithm. Since Image segmentation is the basic step in many image processing applications, so faithful segmentation algorithm must be developed for successful implementation of the processing applications. Core aim of image segmentation is to extract the information which is of interest for a particular application. Infact this research addresses the novel segmentation of infected part of fruits based on color features and the image into various color components by using combined approach of Advanced Bacterial foraging optimization Algorithm (ABFOA) approach and RGB decomposition. The original image is decomposed into separate planes of R G and B and then Improved Bacterial Foraging algorithm is applied on three planes separately to calculate three different thresholds. The experimental results clarify the effectiveness of proposed approach to improve the segmentation quality in aspects of precision and computational time. The simulation results reveal that the proposed approach is promising. Segmentation is performed on the basis of Thresholding. Key Words: Improved Bacterial Foraging Optimization Algorithm, Segmentation, Fruit Images, Image Processing.

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Abstract: The surfacing of dynamic execution environments such as 'grids' forces scientific applications to take dynamicity. Dynamic adaptation of Grid Components in Grid Computing is a critical issue for the design of framework for dynamic adaptation towards self-adaptable software development components for the grid. This paper carries the systematic design of dynamic adaptation framework with the effective implementation of the structure of adaptable component. i.e, incorporating the layered architecture environment with the concept of dynamicity.

Keywords: Grid, adaptation, resources, entities, component specific level, component independent level.

[1] Je´re´my Buisson, Franc¸oise Andre´, and Jean-Louis Pazat. Dynamic adaptation for grid computing. In P.M.A. Sloot, A.G. Hoekstra, T. Priol, A. Reinefeld, and M. Bubak, editors, Advances in Grid Computing- EGC 2005 (European Grid Conference, Amsterdam, The Netherlands, February 14-16, 2005, Revised Selected Papers), volume 3470 of LNCS, pages 538–547, Amsterdam, February 2005. Springer-Verlag.
[2] Je´re´my Buisson, Franc¸oise Andre´, and Jean-Louis Pazat. Performance and practicability of dynamic adaptation of parallel computing : an experience feedback from Dynaco. Publication interne 2006 Projeeects Paris.
[3] Je´re´my Buisson, Franc¸oise Andre´, and Jean-Louis Pazat. Enforcing consistency during the adaptation of a parallel component. In The 4th International Symposium on Parallel and Distributed Computing, July 2005.Eason, B. Noble, and I. N. Sneddon, "On certain integrals of Lipschitz-Hankel type involving products of Bessel functions," Phil. Trans. Roy. Soc. London, vol. A247, pp. 529–551, April 1955.
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[5] Introduction to Grid Computing – A IBM‟s red book for details about Grid Computing is also useful for installation of Globus Tool Kit 4.
[6] Jérémy Buisson, Françoise André and Jean-Louis Pazat. A framework for dynamic adaptation of parallel components. In ParCo 2005, Málaga, Spain, 13-16 September 2005.
[7] Pierre-Charles David and Thomas Ledoux. Towards a framework for self-adaptive component-based applications. In DAIS'03, volume 2893 of LNCS. Springer-Verlag, November 2003.
[8] Brian Ensink and Vikram Adve. Coordinating adaptations in distributed systems. In 24th International Conference on Distributed Computing Systems, pages 446–455, March 2004.
[9] Brian Ensink, Joel Stanley, and Vikram Adve. Program control language: a programming language for adaptive distributed applications. Journal of Parallel and Distributed Computing, 63(11):1082–1104, November 2003.
[10] Introduction to Grid Computing – A IBM‟s red book for details about Grid Computing is also useful for installation of Globus Tool Kit 4.

Abstract: In this Research paper we describe mobile ad hoc networking and routing protocols modeling. Moreover we discuss system model and ad hoc wireless networks about the routing protocols. We decisions of report Solutions for Routing Protocols in Ad Hoc Networks. This paper we discuss verification of the Ad Hoc Routing. We discuss for another process of copying with the state explosion in Ad Hoc Networks and checking of the mobile ad hoc network. Finally we survey the current checking of the modeling solutions for the mobile ad hoc network.

Keyword: Networking, Modeling, Protocol, node, Verification, Routing, UPAAL, BDD, SPIN.

[1]. Arup Acharya, Archan Misra and Sorav Bansal. .A Label-switching Packet Forwarding architecture for Multi-hop Wireless LANs.
[2]. Proc WoWMoM'02, Sep 2002, Atlanta, USA Lundgren, H.: Implementation and Real-world Evaluation of Routing Protocols for Wireless Ad hoc Networks. Licentiate thesis, Uppsala University (2002).
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[5]. Johnson, D.B., Maltz, D.A., Hu, Y.C.: Internet draft: The dynamic source routing protocol for mobile ad hoc networks (DSR). http://www.ietf.org/internet-drafts/draft-ietf-manet-dsr-09.txt (2003).
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[7]. Tian-Tsair SutS, Po-Chiun Huangt, and Chung-Ju Changt,―A channel borrowing protection scheme for handoffs in a cellular based pcs system‖ , 0-7803-2955-4/95/ IEEE
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Abstract: This survey report basically gives a comparison report on different page ranking algorithm on the basis of numerical analysis. Four popular algorithms used for this purpose PageRank, Weighted PageRank, PageRank using VOL and finally weighted PageRank using VOL. This report will give brief introduction of web mining concept because web mining is core content in page rank calculation .Many aspect related to the page ranking will be discussed by taking PageRank algorithm and its variation as a basis for this purpose. A detailed comparison table of PageRank, Weighted PageRank, PageRank using VOL and finally weighted PageRank using VOL will be used for better analysis.

Keywords: PageRank, Weighted pageRank, PageRank based on visits of links, Weighted page rank based on visits of links, Web mining

[1] Neelam Duhan, A. K. Sharma, and Komal Kumar Bhatia, Page Ranking Algorithms: A Survey, proc. IEEE International Advance Computing Conference (IACC 2009)

[2] Gyanendra Kumar, Neelam Duhan, and A. K. Sharma, Page Ranking Based on Number of Visits of Links of Web Page, proc. India International Conference on Computer & Communication Technology (ICCCT), 2011

[3] Hany M. Harb, Ahmed R. Khalifa, and Hossam M. Ishkewy, Personal Search Engine Based on User Interests and Modified Page Rank , IEEE , 2009, 978-1-4244-5844-8/09

[4] Yong Zhang, and Long-bin Xiao,The Research about Web Page Ranking Based on the A-PageRank and the Extended VSM , proc. Fifth IEEE Conference on Fuzzy Systems and Knowledge Discovery, 2008, 978-0-7695-3305-6/08

[5] Dilip Kumar Sharma, and A. K. Sharma, A Comparative Analysis of Web Page Ranking Algorithms, International Journal on Computer Science and Engineering,08( 02), 2010, 2670-2676.

[6] Neelam tyagi, and Simple Sharma, Weighted Page Rank Algorithm Based on number of visits of links (VOL), International Journal of Soft Computing and Engineering (IJSCE), 3(2), 2012, 2231-2307

[7] Kavita Sharma, Gulshan Shrivastwa, and Vikash Kumar ,Web mining: Today and Tomorrow , IEEE, 2011, 978-1-4244-8679/11

[8] Brijendra Singh ,Web data mining A research: Survey, IEEE, 2010, 978-1-4244-5967/10
[9] http://en.wikipedia.org/wiki/PageRank

Abstract: Data mining is a collection of techniques which is used to extract knowledge from huge amount of data. The first section contains the introduction and the next part describes the main task of data mining. Third part explains the clustering methods like partitioning and hierarchical methods.

Keywords: Clustering, k-means, agglomerative and divisive.

[1] Robert J. Hilderman and Howard J. Hamilton. Knowledge Discovery and Measures of Interest. Kluwer Academic Publishers, 1 edition, 2001.

[2] Gregory Piatetsky-Shapiro, Usama Fayyad, and Padhraic Symth. From Data Mining to Knowledge Discovery in Databases. AAAI/MIT Press, 1996.

[3] Philip S. Yu, Ming-Syan Chen, and Jiawei Han. Data Mining: An Overview from Database Perspective. Ieee Trans. on Knowledge and Data Engineering, 1994.

[4] Elkan, C. (2001). Magical Thinking in Data Mining: Lessons from CoIL Challenge 2000. Proc. of SIGKDD01, 426-431.

[5] Lavrac, N., Motoda, H., Fawcett, T., Holte, R., Langley, P. & Adriaans, P. (2004). Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving. Machine Learning 57(1-2): 13-34.
[6] http://en.wikipedia.org/wiki/Data_mining

[7] Veyssieres, M.P. and Plant, R.E. Identification of vegetation state and transition domains in California's hardwood rangelands. University of California, 1998
[8] Introduction to data mining by G.K.Gupta.

Abstract: Texture classification is used in various pattern recognition applications that possess feature-liked Appearance. This paper aims to compile the recent trends on the usage of feature extraction and classification methods used in the research of texture classification as well as the texture datasets used for the experiments. The study shows that the signal processing methods, such as Gabor filters and wavelets are gaining popularity but old methods such as GLCM are still used but are improved with new calculations or combined with other methods. For the classifiers, nearest neighbor algorithms are still fairly popular despite being simple and SVM has become a major classifier used in texture classification. For the datasets, DynTex, Brodatz texture dataset is the most popularly used dataset despite it being old and with limited samples, other datasets are less used.

Index Terms: Texture Classification, wavelet –Based Dynamic, Computer Vision, Pattern Recognition, Machine Learning.

[1] M. Tuceryan, and A.K. Jain, "Texture Analysis," The Handbook of Pattern Recognition and Computer Vision (2nd Ed), World Scientific Publishing, Singapore, pp. 207-248, 1998.

[2] L. Lepisto, L. Kunttu, J. Autio, and A. Visa, "Rock Image Classification Using Non-Homogenous Textures and Spectral Imaging," WSCG, 2003.

[3] J.Y. Tou, Y.H. Tay, and P.Y. Lau, "A Comparative Study for Texture Classification Techniques on Wood Species Recognition Problem," ICNC, vol. 5, pp. 8-12, 2009.

[4] W.H. Yap, M. Khalid, and R. Yusof, "Face Verification with Gabor Representation and Support Vector Machines," AMS, pp. 451-459, 2007

. [5] Y.B. Salem, and S. Nasri, "Texture Classification of Woven Fabric Based on a GLCM Method and using Multiclass Support Vector Machine," SSD, 2009.

[6] J.A.R. Recio, L.A.R. Fernandez, and A. Fernandez-Sarria ,"Use of Gabor Filters for Texture Classification of Digital Images," Física de la Tierra, no. 17, pp. 47-56, 2005.

[7] Y.Q. Chen, "Novel Techniques for Image Texture Classification," PhD Thesis, University of Southampton, United Kingdom, 1995.

[8] R.M. Haralick, K. Shanmugam, and L. Dinstein, "Textural Features for Image Classification," IEEE TSMC, vol. 3, pp. 610-621, 1973.

[9] M. Petrou, and P.G. Sevilla, Image Processing Dealing with Texture, John Wiley & Sons, West Sussex, England, 2006.

[10] S. Arivazhagan, L. Ganesan, and T.G.S. Kumar, "Texture Classification using Curvelet Statistical and Co-occurrence Features," ICPR, 2006.

Abstract: Wireless sensor networks are exposed to different types of security threats that can reduce the performance of the whole network; that might result in serious problems like denial of service attacks, routing attacks, Sybil attack etc. Defensive mechanisms like Key management protocols, authentication protocols and secure routing cannot provide security to WSNs for these types of attacks. Intrusion detection system is a solution to this problem. It analyses the network by collecting sufficient amount of data and detects anomalous behaviour of sensor node. IDS based security mechanisms suggested for other network models such as ad hoc networks, cannot directly be used in WSNs. Researchers have proposed various intrusion detection systems for wireless sensor networks during the last few years. Essentially these approaches can be classified into two main categories i.e. distributed and stand alone. Distributed IDS can be further classified into hierarchical, mobile agent based and hybrid IDS. This paper presents distributed intrusion detection system for wireless sensor networks.

Keywords: Wireless Sensor Networks, Security, Intrusion Detection System

[1] A. S. K. Pathan, L. Hyung-Woo, and H. Choong Seon, "Security in wireless sensor networks: issues and challenges," in Advanced Communication Technology, 2006. ICACT 2006. The 8th International Conference, 2006, pp. 6 pp.-1048.
[2] P. Inverardi, L. Mostarda, and A. Navarra, "Distributed IDSs for enhancing Security in Mobile Wireless Sensor Networks," in Advanced Information Networking and Applications, 2006. AINA 2006. 20th International Conference on, 2006, pp. 116-120.
[3] W. Yong, G. Attebury, and B. Ramamurthy, "A survey of security issues in wireless sensor networks," Communications Surveys & Tutorials, IEEE, vol. 8, pp. 2-23, 2006.
[4] I. Krontiris, T. Dimitriou, and F. C. Freiling, "Towards Intrusion Detection in Wireless Sensor Networks," Paris, April 2007.
[5] L. Besson and P. Leleu, "A Distributed Intrusion Detection System for Ad-Hoc Wireless Sensor Networks: The AWISSENET Distributed Intrusion Detection System," in Systems, Signals and Image Processing, 2009. IWSSIP 2009. 16th International Conference on, 2009, pp. 1-3.
[6] A. H. Farooqi and F. A. Khan, "Intrusion Detection Systems for Wireless Sensor Networks: A Survey," in Communication and Networking. vol. 56, D. Ślęzak, T.-h. Kim, A. C.-C. Chang, T. Vasilakos, M. Li, and K. Sakurai, Eds., ed: Springer Berlin Heidelberg, 2009, pp. 234-241.
[7] I. Krontiris, T. Giannetsos, and T. Dimitriou, "LIDeA: a distributed lightweight intrusion detection architecture for sensor networks," in Proceedings of the 4th international conference on Security and privacy in communication netowrks, Istanbul, Turkey, 2008, pp. 1-10.
[8] A. P. R. d. Silva, M. H. T. Martins, B. P. S. Rocha, A. A. F. Loureiro, L. B. Ruiz, and H. C. Wong, "Decentralized intrusion detection in wireless sensor networks," in Proceedings of the 1st ACM international workshop on Quality of service ; security in wireless and mobile networks, Montreal, Quebec, Canada, 2005, pp. 16-23.

Abstract: Cloud computing delivers IT resources as a Service over Internet The advantage of cloud computing is everlasting but it brings more issues including security. Ensuring the security of cloud computing is a foremost factor in the cloud computing environment, as users often store sensitive data with cloud storage providers but these providers may be untrusted. Cloud storage providers may be single cloud or multi-cloud. But it is found that the research into the use of multi-clouds providers to maintain security has received less attention from the research community than the use of single clouds. In this paper, we have created a framework to supply a secure cloud database that will guarantee to prevent security risks facing the cloud computing community. This framework applied multi-clouds and the date constraint validation to reduce the risk of data intrusion and the loss of service availability in the cloud and ensure data integrity. We present a virtual storage cloud system called DepSky which consists of combination of different clouds to build a cloud of cloud.

Keywords : Cloud computing, cloud storage, data integrity, data intrusion, multi-clouds, service availability single cloud.

[1] http://www.techaaka.com/cloud-computing-architecture.html
[2] S. Subashini and V. Kavitha, "A survey on security issues in service delivery models of cloud computing", Journal of Network and Computer Applications, 34(1), 2011, pp 1-11.
[3] Md. Tanzim Khorshed, A.B.M. Shawkat Ali, Saleh A. Wasimi, ―A surveys on gaps, threat remediation challenge, and some thoughts for proactive attack detection in the cloud computing‖, School of Information and Communication Technology, CQ University QLD 4702, Australia. Received 15 August 2011. Revised 11 January 2012. Accepted 18 January 2012. Available online 27 January 2012.
[4] Cloud Computing Security: From Single to Multi-Clouds,2012 ,45th Hawaii International Conference on System Sciences.
[5] M. Vukolic,"The Byzantine empire in theintercloud", ACM SIGACT News, 41,2010, pp.105-111.
[6] A. Bessani, M. Correia, B. Quaresma, F. André and P. Sousa, "DepSky: dependable and secure storage in a cloud-of-clouds", EuroSys'11:Proc. 6thConf. On Computer systems, 2011, pp. 31-46.
[7] K.D. Bowers, A. Juels and A. Oprea, "HAIL: A high-availability and integrity layer for cloud storage", CCS'09: Proc. 16th ACM Conf. on Computer and communications security, 2009, pp.187-198.
[8] H. Abu-Libdeh, L. Princehouse and H. Weatherspoon, "RACS: a case for cloud storage diversity", SoCC'10:Proc. 1st ACM symposium on Cloud computing, 2010, pp. 229-240.
[9] C. Cachin, R. Haas and M. Vukolic, "Dependable storage in the Intercloud", Research Report RZ, 3783, 2010.
[10] F. Rocha and M. Correia, "Lucy in the Sky without Diamonds: Stealing Confidential Data in the Cloud", Proc. 1stIntl. Workshop Dependability of Clouds, Data Centers and Virtual Computing Environments, 2011, pp. 1-6.

Abstract: In wireless mobile ad hoc networks (MANETs), packet transmission is impaired by radio link fluctuations. This paper proposes a novel channel adaptive routing protocol which extends the Ad hoc On-Demand Multipath Distance Vector (AOMDV) routingprotocol to accommodate channel fading. Specifically, the proposed Channel-Aware AOMDV (CA-AOMDV) uses the channel averagenonfading duration as a routing metric to select stable links for path discovery, and applies a preemptive handoff strategy to maintainreliable connections by exploiting channel state information. Using the same information, paths can be reused when they become available again, rather than being discarded. We provide new theoretical results for the downtime and lifetime of a live-die-live multiplepath system, as well as detailed theoretical expressions for common network performance measures, providing useful insights into thedifferences in performance between CA-AOMDV and AOMDV. Simulation and theoretical results show that CA-AOMDV has greatly improved network performance over AOMDV

Keywords: Mobile ad hoc networks, routing protocols, channel adaptive routing

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