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Volume-1 Issue-3

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Volume-1 Issue-3, January 2013, ISSN:  2319–6378 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



M. Deva Priya, M. L Valarmathi, M. Deepa, K. Jaya Bharathi 

Paper Title:

Implementation and Evaluation of GPSR and M-LAER in Mobile WiMAX Networks

Abstract: An appropriate routing protocol is mandatory for scalable wireless networks. Various routing protocols have been proposed in the literature for mobile WiMAX networks. The reliability of a path depends on the stability of the links constituting the path. A long lasting path is desirable. Energy is an important factor that should be taken into consideration as nodes are energy contingent. In this paper, the behavior of GPSR and Modified Link-StAbility and Energy aware Routing (M-LAER) are analyzed for WiMAX environment. 

GPSR, WiMAX, LAER, Routing, Energy, M-LAER.


1.        Qing Chen and Mustafa Cenk Gursoy, Energy-Efficient Modulation Design for Reliable Communication in Wireless Networks, 2009.
2.        IEEE standard 802.16-2004, IEEE standard for local and metropolitan area networks-part 16: Air interface for fixed broadband wireless access systems, 2004.

3.        IEEE standard 802.16.2-2004, IEEE recommended practice for local and metropolitan area networks coexistence of fixed broadband wireless access system, 2004.

4.        IEEE standard 802.16-2004/cor1, Corrigendum to IEEE standard for local and metropolitan area networks –part 16: air interface for fixed broadband wireless
access system, Draft 5, 2005.

5.        Sarat Chandra and Anirudha Sahoo, An Efficient Call Admission Control for IEEE 802.16 Networks.

6.        IEEE Standard for Local and Metropolitan Area Networks, IEEE 802.16 Standard 2002.

7.        Stojmenovic, I., Lin, X., Power-Aware Localized Routing in Wireless Networks, IEEE Transactions on Parallel and Distributed Systems, 12 (11), pp. 1122 - 1133, 2001.

8.        Rabiner,W., Kuli,J., Balakrishnan,H., Adaptive Protocols for Information Dissemination in Wireless Sensor Networks, MobiCom’99,  pp. 174-185, 1999.

9.        Chang J.H, Tassiulas L, Energy Conserving Routing in Wireless Ad-Hoc Networks, INFOCOM’ 00, Tel Aviv, Israel, pp.22-31, 2000.

10.     Jie Gao, Li Zhang, Load Balanced Short Path Routing in Wireless Networks, IEEE Transactions on Parallel and Distributed Systems,17(4),pp.377-388, 2006.

11.     R C. Shah and J. M. Rabaey, Energy aware routing for low energy ad hoc sensor networks, In Proc. IEEE Wireless Communications and Networking Conference, pp.350-355, 2002.

12.     Stojmenovic, I., Lin, X., Power aware localized routing in ad hoc networks, IEEE Transactions on Parallel and Distributed Sys¬tems, 12(10),1023-1032, 2001.

13.     Finn, Gregory G, Routing and addressing problems in large metropolitan-scale internetworks, ISUIRR-87¬180, USC ISI, Marina del Ray, CA, 1987.

14.     G.G. Finn, Routing and addressing problems in large metropolitan-scale internetworks, ISI Research Report ISU/RR-87-180, 1987.

15.     Kranalkis E. Singh H, Urrutia ,Compass routing on geometric networks, In Canadian Conference on Computational Geometry (CCCG '99), pp. 51-54 ,1999.

16.     Haque IT, Assi C, Atwood JW, Randomized energy aware rout¬ing algorithms in mobile ad hoc networks, In 8th ACM/lEEE International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MsWim 05), 2005.

17.     Hai Liu, Xiaohua Jia, Peng-Jun Wan, Chih-Wei Yi, S.Kami Makki, S.K. and  Pissinou,N. Maximizing Lifetime of Sensor Surveillance System, IEEE/ACM Transactions on Networking, 15(2), pp. 334-345, 2007.

18.     S.Singh, M.Woo and C.S. Raghavendra, Power-aware routing in Mobile Adhoc Networks, MOBICOM, pp.181-190 , 1998.

19.     Dongkyun Kim, Garcia-Luna-Aceves, J.J. ,  Obraczka, K. ,  Cano, J.-C. , Manzoni, P.  Routing Mechanisms for Mobile Ad Hoc Networks Based on the Energy Drain Rate, IEEE Transactions on Mobile Computing, 2(2) pp. 161-173, 2003.

20.     K.-J. Kim and S.-J. Yoo, Power-Efficient Reliable Routing Protocol for Mobile Ad-Hoc Networks, MWSCAS’04, pp. 481-484, 2004.

21.     Agarwal, S., Ahuja, A. , Singh, J.P. ,Shorey, R. Route-lifetime assessment based routing (RABR)  protocol for mobile ad-hoc networks. IEEE International Conference on Communications. ICC 2000, New Orleans, LA, USA, 18-22, pp.1697-701, 2000.

22.     Tragoudas, S., Dimitrova, S., Routing with energy considerations in mobile ad-hoc networks. 2000 IEEE Wireless Communications and Networking Conference, Chicago, IL, USA, 23-28, p.1258-61, 2000.
23.     Kyungtae Woo, Chansu Yu, Dongman Lee, Hee Yong Youn, Lee B. Non-blocking, localized routing algorithm for balanced energy consumption in mobile ad hoc networks. MASCOTS 2001, pp.117-24, 2001.
24.     Maleki, M., Dantu, K.,  Pedram, M.  Lifetime Prediction Routing in Mobile Ad Hoc Networks, Proc. IEEE Wireless Communication and Networking (WCNC ’03), pp. 1185-1190, 2003.

25.     P. Bergamo, D. Maniezzo, A. Travasoni, A. Giovanardi, G. Mazzini, and M. Zorzi, Distributed Power Control for Energy Efficient Routing in Ad Hoc Networks, Wireless Networks J.,10(1), pp. 29-42, 2004.

26.     Dube, R., Rais, C.D., Kuang-Yeh Wang; Tripathi, S.K., Signal Stability-Based Adaptive Routing (SSA) for Ad Hoc Mobile Networks, IEEE Personal Communications, 4(1), pp. 36-45,1997

27.     C-K. Toh, Associativity based routing for ad hoc mobile networks, Wireless Personal Communications Journal, 4(2), 103–139, 1997.

28.     W. Su, S. Lee, and M. Gerla. Mobility Prediction and Routing in Ad Hoc Wireless Networks, International Journal of Network Management, 3–30, 2001.

29.     McDonald, A.B. and Znati, T. A Path Availability Model for Wireless Ad-Hoc Networks. In Proceedings of the IEEE WCNC, pp. 35–40. IEEE, 1999.

30.     G. Lim, K. Shin, S. Lee, H. Yoon, and J. S. Ma. Link stability and route lifetime in ad hoc wireless networks. In International Workshop on Ad Hoc Networking (IWAHN’02), 2002.

31.     Brad Karp, H. T. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless Networks,” In Proceedings of the 6th annual international conference on Mobile computing and networking (MOBICOM ‘00), pp. Pages 243-254, August 06 - 11, 2000.

32.     Johnson, D. B.  and Maltz, D. A. , Protocols for Adaptive Wireless and Mobile Networking, IEEE Personal Communications, 3(1), pp. 34-42, 1996.

33.     D. B. Johnson, D. A. Maltz and J. Broch, DSR: The Dynamic Source Routing Protocol for Multi-hop Wireless Adhoc Networks in Ad hoc Networking, Chapter 5, C. E. Perkins, Eds. Addison Wesley, pp. 139 – 172, 2000.

34.     Marina, M. K. and Das, S. R., On-demand multipath distance vector routing in ad hoc networks. In Proc. of IEEE International Conference on Network Protocols, pp. 14 -23, 2001.

35.     Lee, S.-J. and Gerla, M.  Split multipath routing with maximally disjoint paths in ad hoc networks. In Proc. IEEE International Conference on Communications 2001 (ICC’01), pp. 3201–3205, 2001.

36.     T. Goff, N. B. Abu-Ghazaleh, D. S. Phatak, and R. Kahvecioglu. Pre-emptive routing in ad hoc networks. In ACM Seventh Annual International Conference on Mobile Computing and Networking (MOBICOM’01), pp. 43 - 52, 2001.

37.     Gerharz, M., de Waal, C., Martini, P. and James, P., Strategies for Finding Stable Paths in Mobile Wireless Ad Hoc Networks, In Proceedings of IEEE 28th Annual Conference on Local Computer Networks (LCN ’03), pp. 130-139, 2003.

38.     De Rango, Guerrerio, F., Marano, S., A Multi-Objective Approach for Energy Consumption and Link Stability Issues in Ad Hoc Networks,  IEEE Communication Letters, 10(1), pp. 28-30, 2006.

39.     F. De Rango, M. Fotino, and S. Marano, “EE-OLSR: Energy Efficient OLSR Routing Protocol for Mobile Ad-Hoc Networks,” In Proceedings of the IEEE Military Communications Conference (MILCOM ’08), pp. 1-7, 16 - 19 Nov. 2008

40.     Floriano De Rango, Member,Francesca Guerriero and Peppino Fazio, Link stability and Energy Aware Routing  Protocol in Distributed Wireless Networks, IEEE Transactions on parallel and distributed systems, 23(4), 2012.





K. R. Arjunadhityaa, G. Murugaboopathi, T. K. S. Rathish Babu

Paper Title:

Implementation of Autonomous Network Reconfiguration System in Wireless Networks

Abstract: Wireless Mesh Networks (WMNs) experience frequent link failures caused by channel interference. These link failures cause severe performance degradation in WMNs .This project is aimed towards developing an Autonomous Network Reconfiguration System (ANRS) that enables a multiradio wireless mesh networks to autonomously recover from local link failures to preserve network performance. Further we carry out simulation using Network Simulator NS-2 to compare the performance of ANRS with the existing link failure recovery methods. The metrics used for the performance evaluation are throughput, efficiency and Delay.

Autonomous Network Reconfiguration System (ANRS), multiradio wireless Mesh Networks (mr-WMNs), Wireless link failures.


1.        I. Akyildiz, X. Wang, and W. Wang, “Wireless mesh networks: A survey,” Comput. Netw., vol. 47, no. 4, pp. 445–487, Mar. 2005.
2.        “MIT Roofnet,” [Online]. Available: http://www.pdos.lcs.mit.edu/  roofnet

3.        M. Alicherry, R. Bhatia, and L. Li, “Joint channel assignment and routing for throughput optimization in multi-radio wireless mesh networks,” in Proc. ACM MobiCom, Cologne, Germany, Aug. 2005, pp. 58–72.

4.        A. Brzezinski, G. Zussman, and E. Modiano, “Enabling distributed throughput maximization in wireless mesh networks: A partitioning approach,” in Proc. ACM MobiCom, Los Angeles, CA, Sep. 2006, pp

5.        A. Raniwala and T. Chiueh, “Architecture and algorithms for an IEEE802.11-based multi-channel wireless mesh network,” in Proc. IEEE INFOCOM,





Rajesh Nema, Rajeev Thakur, Ruchi Gupta

Paper Title:

Design & Implementation of FPGA Based on PID Controller with Motor & Sensor

Abstract:  Proportional-Integra- Derivative controllers are universal control structure and have widely used in Automation systems, they are usually implemented either in hardware using analog components or in software using Computer-based systems. In this paper, we focused our works designing on building a multi-channel PID controller by Field Programmable Gate Arrays (FPGAs). To overcome the hardware complexity by the use of more processors for multi channel, we are using single PID controller for multi channel .Multi channel can be implemented by the use of FPGA.when the error is more it can differentiate and produce the constant output, when signal is low when compared to reference signal it can integrate it.FPGA can offer parallel processing, more speed.



1.        Efficient Dynamic System Implementation Of Fpga Based Pid Control Algorithm For Temperature Control System. Volume 3, Issue 2, July – September (2012), pp. 306-312
2.        High-Speed and Low-Power PID Structures for Embedded ApplicationsPATMOS’11. Madrid: Spain (2011)"

3.        ISSN 0974-2190 Volume 2, Number 1 (2010), pp. 71--82 Analysis and Implementation of Discrete Time PID Controllers using FPGA

4.        FPGA technology for multi-axis control systems Armando Astarloa *, Jesús Lázaro, Unai Bidarte, Jaime Jiménez, Aitzol Zuloaga Accepted 1 September 2008

5.        Design and Implementation of Modular FPGA-Based PID Controllers,Yuen Fong Chan, M. Moallem, Member, IEEE, and Wei Wang, Member, IEEE-2007.

6.        Simulink/Modelsim Simulable VHDL PID Core for Industrial SoPC Multiaxis Controllers Jes´us L´azaro, Armando Astarloa, Jagoba Arias, Unai Bidarte, Aitzol Zuloaga IEEE-2006.

7.        Xilinx Corp. Multipliers.

8.        National Semiconductor. LMD18245 3A, 55V DMOS Full- Bridge Motor D





P. Thamizharasi, D. Vinoth

Paper Title:

Unobservable Privacy-Preserving Routing in MANET

Abstract: Privacy-preserving routing is crucial for some ad hoc networks that require stronger privacy protection. A number of anonymous routing schemes have been proposed for ad hoc networks in recent years, and they provide different level of privacy protection at different cost. These schemes are more scalable to network size, but require more computation effort. However, existing schemes provide only anonymity and unlinkability, while unobservability is never considered or implemented by now. An obvious drawback in existing schemes is that packets are not protected as a whole. An efficient privacy-preserving routing protocol USOR that achieves content unobservability by employing anonymous key establishment based on group signature. USOR is to protect all parts of a packet’s content and it is independent of solutions on traffic pattern unobservability. The unobservable routing protocol is then executed in two phases. First, an anonymous key establishment process is performed to construct secret session keys. Then an unobservable route discovery process is executed to find a route to the destination. By using NS-2 the performance analysis such as energy, bandwidth etc., are simulated.

MANET, Privacy, Public key, Routing, Unobservable.


1.        J. Kong and X. Hong, “ANODR: anonymous on demand routing with untraceable routs for mobile ad-hoc networks,” in proc.  ACM MOBIL-HOC’03,pp, 291-302.
2.        B. Zhu, Z. Wan, F. Bao, R. H. Deng, and M. KankanHailli, “Anonymous secure routing in mobile ad-hoc networks,” in proc. 2004 IEEE conference on Local Computer Networks, pp. 102-108.

3.        D. Sy, R. Chen, and L. Bao, “ODAR: on-demand anonymous routing ad hoc networks,” in 2006 IEEE Conference on Mobile Ad-hoc and Sensor Systems.

4.        K. E. Defrawy and G. Tsudik, “ALARM: anonymous location-aided routing in suspicious MANETs,” IEEE Trans. Mobile Comput., vol. 10, no. 98

5.        S. Seys and B. Preneel, “ARM: anonymous routing protocol for mobile ad hoc networks,” in Proc. 2006 IEEE International Conference on Advanced Information Networking and Applications, pp. 133–137.

6.        Zhiguo Wan, Kui Ren, and Ming Gu,” USOR: An Unobservable Secure On-Demand Routing Protocol for Mobile Ad Hoc Networks.

7.        http://www.academia.edu/219032/A_Review_of_Broadcasting_Methods   _for_Mobile_Ad_Hoc_Network.

8.        http://www.ijcse.com/docs/IJCSE10-01-04-61.pdf.

9.        http://www.ijopcm.org/Vol/10/IJOPCM(vol.3.5.11.D.10).pdf





Ashwini Jarali, Jyoti Rao

Paper Title:

Unique LSB Compression Data Hiding Method

Abstract: This paper presents a unique method of reversible data hiding separately in encrypted image..This work presents a new method that combines image cryptography, data hiding and LSB compressing technique for reversible data hiding separately. In this method we encrypt the original image with stream cipher algorithm. Then, a data-hider may compress the least significant bits of the encrypted image using a data-hiding key to create a sparse space to accommodate some additional data. With an encrypted image containing additional data, if a receiver has the data-hiding key, she can extract the additional data though she does not know the image content. If the receiver has the encryption key, she can decrypt the received data to obtain an image similar to the original one, but cannot extract the additional data. If the receiver has both the data-hiding key and the encryption key she can extract the additional data and recover the original content without any error by exploiting the spatial correlation in natural image.

LSB compressing, reversible data hiding, Image encryption, data embedding, Pixel Permutation.


1.        J. Tian, “Reversible data embedding using a difference expansion,” IEEE Trans. Circuits Syst. Video Technol. , vol. 13, no. 8, pp. 890–896, Aug. 2003
2.        Z.Ni,Y.-Q.Shi,N.Ansari,andW.Su,“Reversible data hiding,” IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 3, pp. 354–362, 2006.

3.        M.U.Celik,G.Sharma,A.M.Tekalp,andE.Saber,“Losslessgeneralized-LSB data embedding,” IEEE Trans. Image Process. ,vol.14, no. 2, pp. 253–266, Feb. 2005.

4.        L. Luo, Z. Chen, M. Chen, X. Zeng, and Z. Xiong, “Reversible image watermarking using interpolation technique,”IEEE Trans. Inf. Foren- sics Secur., vol. 5, no. 1, pp. 187–193, 2010.

5.        W. Hong, T.-S. Chen, Y.-P. Chang, and C.-W. Shiu, “A high capacity reversible data hiding scheme using orthogonal projection and prediction error modification, “Signal Process.,vol.90,pp.2911–2922,2010

6.        C.-C. Chang, C.-C. Lin, and Y.-H. Chen, “Reversible data embedding scheme using differences between original and predicted pixel values, “Inform. Secure. , vol. 2, no. 2, pp. 35–46, 2008

7.        W. Zeng, “Digital watermarking and data hiding: technologies and applications,” in Proc. Int. Conf. Inf. Syst., Anal. Synth., vol. 3, 1998, pp.223–229.

8.        X. Zhang, “Reversible data hiding in encrypted image,” IEEE Signal Process. Lett., vol. 18, no. 4, pp. 255–258, Apr. 2011.
9.        I. J. Cox, J. Kilian, T. Leighton, and T. Shamoon, “Secure spread spectrum watermarking for multimedia,” in IEEE Trans. on Image Processing , vol. 6. No. 12, pp.
1673-1687, Dec. 1997.

10.     J. Huang and Y. Q. Shi, “An adaptive image watermarking scheme based on visual masking,” Electronics Letters , 34 (8), pp. 748-750, 1998.

11.     B. Chen, G. W. Wornell, “Quantization index modulation: a class of provably good meth-ods for   digital watermarking and information embedding,” IEEE Transaction on Information Theory,  vol. 47, no. 4, pp. 1423-1443, May 2001.

12.     An Improved Reversible Data Hiding in Encrypted Images Using Side Match ,Wien Hong, Tung-Shou Chen, and Han-Yan Wu , IEEE SIGNAL PROCESSING LETTERS, VOL. 19, NO. 4, APRIL 2012

13.     M. Johnson, P. Ishwar, V. M. Prabhakaran, D. Schonberg, and K. Ramchandran, “On compressing encrypted data,” IEEE Trans. Signal Process., vol. 52, no. 10, pp. 2992–3006, Oct. 2004

14.     W. Liu, W. Zeng, L. Dong, and Q. Yao, “Efficient compression of encrypted grayscale images,” IEEE Trans. Image Process., vol. 19, no. 4,pp. 1097–1102, Apr. 2010.

15.     X. Zhang, “Lossy compression and iterative reconstruction for encrypted image,” IEEE Trans. Inform. Forensics Security, vol. 6, no. 1,pp. 53–58, Feb. 2011.

16.     A Survey on Various Data Hiding Techniques and their Comparative Analysis Harshavardhan Kayarkar* Corresponding Author M.G.M‟s College of Engineering and Technology, Navi Mumbai, India

17.     Stream Encryption Standard for Digital Images, Akhil Kaushik, Satvika Khanna, Manoj Barnela and Anant Kumar, International Journal of Computer and Electrical  Engineering, Vol. 3, No. 2, April, 2011

18.     Efficient Data Hiding With Plus-Minus One or Two, Xinpeng Zhang, IEEE SIGNAL PROCESSING LETTERS, VOL. 17, NO. 7, JULY 2010

19.     An Overview of Reversible Data Hiding, Mohammad Aurangzeb, National University of Singapore, published at ICCIT 2 003,  19- 21 Dec, Jahangirnagar  University , Bangladesh,  pp 75-79

20.     Reversible Data Hiding ,Yun Q. Shi, Department of Electrical and Computer Engineering, New Jersey Institute of Technology.





Arun Kumar R

Paper Title:

Shipyard Management through Android Technology

Abstract: The purpose of paper is to provide security for user. User can store all the information about ships and loads and also the incoming and outgoing transactions in entire port information. The existing system is when user want to store the data information about all ships in port user will registered in a book to maintain all the data and operations timings about load for this they are keeping one accountant he will do accounts calculation and all the information about entire port. The proposed system our application is when user want to store the data about all the information, calculation of accounts, weighment operations user can store all accounts and also include calculator to calculation part. This is the advantage of the proposed system. Modules we can use Database, ui designing, Authentication, Barcode scanner. Android is a software stack for mobile devices that includes an operating system, middleware and key applications. The android sdk provides the tools and API necessary to begin developing applications on the android platform using the java programming language. In this application user can store all the information about ships and loads and also the incoming and outgoing transactions in entire port information.



1.        Hello, Android, E. Burnette, the Pragmatic Programmers (2009).
2.        Professional Android 2 Application Development, R. Meier, Wiley (2010).

3.        Beginning Android 2, M. Murphy, Apress (2010).

4.        Android Wireless Application Development, S. Conder and L. Darcey, Addison-Wesley (2010).

5.        Android Application Development in 24 Hours, L. Darcey and S. Conder, Sams (2010).

6.        The Android Developer's Cookbook, J. Steele, N. To, Addison-Wesley (2011).





Pratik Gite, Sanjay Thakur

Paper Title:

Comparative Study and Simulation Based Analysis of MANET Routing Protocols Using NS-2

Abstract: Mobile Ad-hoc Network is a collection of wireless devices that can be set up instantly anywhere and anytime without the needs of any pre-existing network infrastructure. It is an autonomous system in which mobile devices are connected through wireless links and free to move randomly and often act as host as well as router at the same time. The main objective of this paper is to simulation based analysis of MANET routing protocols viz. Destination Sequence Distance Vector (DSDV), Dynamic Source Routing (DSR) and Ad-hoc On Demand Distance Vector (AODV) on the basis of different performance metrics which are throughput, packet delivery ratio, routing overheads, packet drop. The simulation is performed through the simulation tool Network Simulator-2 (NS-2) due to its open source simplicity and free availability.

Destination Sequence Distance Vector (DSDV), Dynamic Source Routing (DSR), Ad-hoc On Demand Distance Vector (AODV), Network Simulator (NS-2).


1.        David B. Johnson and David A. Maltz. Dynamic source “Routing in ad hoc wireless networks” Technical report, Carnegie Mellon University, 1996.
2.        Mehran Abolhasan, Tadeusz Wysocki and Eryk Dutkiewicz. “A review of routing protocols for mobile ad hoc networks” Technical report, Telecommunication and Information Research Institute, University of Wollongong, Wollong, NSW 2522. Motorola Australia Research Centre, 12 Lord St., Botany, NSW 2525, Australia, 2003.

3.        Azzedine Boukerche “Algorithm and Protocols for wireless and Mobile Ad-hoc networks”.

4.        Integration of mobile ad-hoc networks, EU project DAIDALOS, Susana Sargento, and Institute of Telecommunications.

5.        C. Siva Ram Murthy and B. S. Manoj, “Ad Hoc Wireless Networks, Architectures and Protocols”, Second Edition, Low price Edition, Pearson Education, 2007.

6.        Mobile Ad Hoc Networking: An Essential Technology for Pervasive Computing Jun-Zhao Sun MediaTeam, Machine Vision and Media Processing Unit, 2002.

7.        Jun-Zhao Sun “Mobile Ad Hoc Networking: An Essential Technology for Pervasive Computing” USA 2003.

8.        G. S. Mamatha1 and Dr. S. C. Sharma, “ANALYZING THE MANET VARIATIONS, CHALLENGES, CAPACITY AND PROTOCOL ISSUES”, “International Journal of Computer Science & Engineering Survey (IJCSES) Vol.1, No.1, August 2010“

9.        Nor Surayati Mohamad, Usop Azizol Abdullah, Ahmad Faisal and Amri Abidin, ”Performance Evaluation of AODV, DSDV & DSR Routing Protocol in Grid Environment, “IJCSNS International Journal of Computer Science and Network Security, VOL.9 No.7, July 2009.

10.     Zygmunt J. Haas, Jing Deng, Ben Liang, Panagiotis Papadimitratos, and S. Sajama, “Wireless Ad Hoc Networks”  Cornell University School of Electrical and Computer Engineering, 2004.

11.      Elizabeth M. Royer and Chai-Keong Toh, “A review of current routing protocols for ad-hoc mobile wireless networks” Technical report, University of California and Georgia Institute of Technology, USA, 1999.

12.     C.E. Perkins and E.M. Royer, “Ad-hoc on Demand Distance Vector Routing Protocols”, in proceeded 2nd IEEE work shop mobile computing system and applications, new ore leans, Loss Angelis, pp 90-100, February 2011.

13.     Md Shohidul Islam, Md Naim Hider, Md. Touhidul Haque, Leton miah “An Extensive Comparison among DSDV, DSR and AODV Protocols in MANET, “International journal of computer application (0975-8887) Volume 15-no.2, February 2011.





Ali Broumandnia, Mostafa Cheraghi, Mohsen Azararjmand

Paper Title:

Content-Based Image Retrieval with Graph Theoretic Approach

Abstract: The need for content-based image retrieval has increased with increment size and volume of digital images. This paper introduces the graph-based approach in order to retrieve the content-based image. In the proposed method, an image presents by a set of regions, while comparison of images are posing, each image represents by a graph, hence the estimation of the region correspondence transform into an graph matching problem. In addition, by using and image distance criteria, the difference between images obtained. Experimental results show that the proposed graph-theoretic image matching performance is acceptable.

Component: Content Based Image retrieval, Graph matching, Image segmentation, Matching Matrix.


1.        Ying Liua, DengshengZhanga, GuojunLua, Wei-Ying  Mab. “Asurvey of content-based image retrieval with high-level semantics”.Pattern Recognition 40(2007) 262 – 282, 2007.
2.        James Z.wang, Jia Li, GioWederhold. “Image SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries”. IEEE Transactions On Pattern Analaysis And Machine Intelligence,vol. 23, NO. 9, September 2001.

3.        Chueh-Yu Li, Chiou-Ting Hsu. “Image Retrieval With Relevance Feedback Based on Graph-Theoretic Region Correspondence Estimation”. IEEE Transactions on knowledge and data engineering , vol. 10, no. 3, 2008.

4.        Feng Jing, Mingjing Li, Hong-Jiang Zhang, Bo Zhang. “An Efficient and Effective Region-BasedImage Retrieval Framework”.IEEE Transactions on Image Processing, vol. 13, NO. 5, MAY 2004.

5.        W. Niblack et al., “The QBIC project: Querying images by content usingcolor, texture, and shape,” Proc. SPIE, vol. 1908, pp. 173–187, Feb.1993.

6.        A. Pentland, R. Picard, and S. Sclaroff, “Photobook: Content-based manipulationof image databases,” SPIE Storage and Retrieval for Imageand Video Databases II, no. 2185, pp. 34–47, Feb. 1994.

7.        Ying Liu, Xin Chen, Chengcui Zhang, Alan Sprague, “Semantic clustering for region-based image retrieval” J. Vis. Commun. Image R. 20 (2009) 157–166.

8.        SongheFeng, Congyan Lang, De Xu , “Localized Content-based Image Retrieval UsingSaliency-based Graph Learning Framework” 978-1-4244-5900-1/10/$26.00 ©2010 IEEE.

9.        Adel Hlaqui, Hao-Jun Sun, Sheng-Rui Wang, “Image Retrieval Using Fuzzy Segmentation And A Graph Matching Technique,” Proceedings of the First International Conference on Machine Leaning and Cybernetics, Beijing, 4-5 November 2002.

10.     Chuan-Yu Chang a,*, Hung-Jen Wangb, Chi-Fang Li, “Semantic analysis of real-world images using support vector machine,” Expert Systems with Applications 36 (2009) 10560–10569.

11.     D. Comaniciu and P. Meer, “Mean shift: A robust approach towardfeature space analysis,” IEEE Trans. Pattern Anal. Mach. Intelli., vol.23, no. 5, pp. 603–619, May 2002.

12.     Nozomi Oka, Nonmember and Keisuke Kameyama, “Relevance Tuning in Content-based Retrieval of Structurally-Modeled Images using Particle Swarm Optimization,” 978-1-4244-2771-0/09/$25.00 ©2009 IEEE. 2009.

13.     Chuech-Yu Li and Chiou-Ting Hsu, “Region Correspondence For Image Retrieval Using Graph-Theoretic Approach And Maximum Likelihood Estimation 2004 International Conference on Image Processing (ICIP).

14.     J. Li, J. Z.Wang, and G.Wiederhold, “IRM: Integrated region matching for image retrieval,” in Proc. ACM Multimedia, 2000.

15.     Y. Chen and J. Z.Wang, “A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval,” IEEE Trans. Pattern Anal.Mach.Intell., vol. 24, no. 9, pp. 1252–1267, Sep. 2002.

16.     Y. Rubner, L.J. Guibas, and C. Tomasi, ªThe Earth Mover's Distance, Multi-Dimensional Scaling, and Color-Based Image Retrieval, Proc. DARPA Image Understanding Workshop, pp. 661-668, May 1997.





Aruna Rani, R. K. Singh, Ashish Negi

Paper Title:

Design and Analysis of Nano Fractal Antenna Protection Chip to Overcome Crimes Against Women and Remedial Measures

Abstract: In this paper   novel technology fractal antenna structures are proposed to protect the women and girls from the crimes and brutal mishaps and to provide them a multifunctional, multiband “Nano fractal antenna protection chip”.  The novel antenna structures have rectangular shaped and U shaped fractals slots. The novel fractal antennas can reduce the size of antenna and chip. The multi frequencies can be generated and bandwidth can be enhanced. This chip can be easily designed, fabricated and implemented. This chip will automatically activated at the time of abnormal activity. It also gives the remedies to use this technology for women protection. The paper also presents the prototype of the technology.

Fractal, antenna, Nano technology, protection chip, multiband antenna, rectangular, U slot.


1.        A. Rani and R. K. Singh, “Fractal Antenna and Nano Technology Uniforms”,International Journal of Soft Computing and Engineering , vol. 2, Issue 6.
2.        Carles Puente Baliarda, Jordi Romeu et al, “The Koch Monopole: A Small Fractal Antenna”, IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, VOL. 48, NO. 11, NOVEMBER 2000

3.        A. Azari and J. Rowhani, “ULTRA WIDEBAND FRACTAL MICROSTRIP ANTENNA DESIGN” , Progress In Electromagnetics Research C, Vol. 2, 7–12, 2008

4.        S.Natarajamani, Santanu Kumar Behera & Sarat Kumar Patra, “Planar UWB Fractal Antenna with Band-Notched Characteristics”, International Conference on Electronic Systems (ICES-2011), 7-9 Jan 2011, NIT Rourkela, India.

5.        S. Beril, 2 T. Anita Jones Mary, “ An Innovative Octagonal Fractal Circular PIFA for Mobile Phone Applications”, The International Journal of Engineering And Science (IJES) ,Volume 1, Issue 2, Pages 308-312, 2012.

6.        A. Rani and R. K. Dawre,” Design and Analysis of Rectangular and U Slotted Patch for Satellite Communication”, International Journal of Computer Applications (0975 – 8887), Vol. 12 , No.7, Dec. 2010.





Nilesh R. Rathod, Hardik J. Patel

Paper Title:

An Approach on Coding and Congestion Aware Routing Mechanism in MANET

Abstract: Routing protocols for mobile ad hoc networks (MANETs) have been explored extensively in last few years. Much of this work is targeted at finding a feasible route from a source to a destination without considering current network traffic or application requirements. Routing may let a congestion happen which is detected by congestion control, but dealing with congestion in reactive manner results in longer delay, and unnecessary packet loss and requires significant overhead if a new route is needed.  Routing should not be only aware of network coding, but also be aware to, network congestion. This paper present the survey of coding and congestion aware routing protocols for mobile ad-hoc network. This paper argue that network coding aware routing protocol in combination with congestion aware routing protocol allows MANET to operate in a more efficient manner and helps to deal with typical MANET issues such as . Congestion in the network and poor utilization of the network as well as various other issues that have been disregarded in previous MANET  researches such as throughput and unreliable channel. By comparison and combination of coding and congestion aware routing mechanism can achieve shorter file downloading delays compared to an existing MANET protocol.

A Mobile Ad hoc networks, congestion aware routing, Congestion metric, network coding.


1.        T. Ho, R. Koetter, M. Médard, D. Karger, and M. Effros, “The benefits of coding over routing in a randomized setting,” In Proceedings of the IEEE International Symposium on Information Theory June 2003, page 442, Yokohama, Japan, 2003.
2.        A. Mitrokotsa, N. Komninos, C. Douligeris, (2007),      “Intrusion Detection with Neural Networks and Watermarking Techniques for MANET”, In Proceedings of IEEE International Conference on Pervasive Services 2007 (ICPS'07), July 15-20, 2007, pp. 118 - 127 Istanbul, Turkey, 2007.
3.        R. Ahlswede, N. Cai, S.-Y. R. Li, and R. W. Yeung, “Network information flow”, IEEE Transactions on Information Theory, vol. 46, July 2000, pp. 12041216,  2000.
4.        R. W. Yeung “Distributed Source Coding for Satellite Communications”, IEEE Transactions on    Information Theory, May 1999, vol. 43, pp. 11111120, 1999.
5.        S.-Y. R. Li, R. W. Yeung, and N. Cai, “Linear  network coding”, IEEE Transactions on Information Theory”, February 2003, vol. 49, pp. 371- 381,2003.
6.        A. G. Dimakis, P. B. Godfrey, M. J. Wainwright and K. Ramchandran “The Benefits of Network Coding for Peer-to-Peer Storage Systems”, NetCod  Workshop, January 2007.
7.        C. Fragouli, J. Widmer, J. Le Boudec “Network  Coding: An instant primer”, ACM SIGCOMM Computer Communication Review, January 2006,  vol.36, pp. 63 - 68  , 2006.
8.        R. Koetter and M. Médard, “Beyond routing: an  algebraic approach to network coding”, In Proceedings of the Twenty-First Annual Joint Conference of the IEEE Computer and  Communications Societies, vol.1 , pp. 122- 130, 2002.
9.        C. Fragouli, J. Widmer, J. Le Boudec “On the Benefits of Network Coding for Wireless Applications”, Netcod, 2006.
10.     T. Lin, S. F. Midkiff, and Jahng S. Park. "A Framework for Wireless Ad Hoc Routing Protocols," in proceeding of  IEEE WCNC, vol. 2, pp. 1162-1167, 2003.





H. S. Hota

Paper Title:

Diagnosis of Breast Cancer Using Intelligent Techniques

Abstract: Breast cancer is  a  serious and life threatening disease due to its  invasive and infiltrative character and is  very commonly found  in woman .An abnormal growth of cells in breast is the main cause of  breast cancer actually this abnormal growth of cells can be of two types benign (Non-Cancerous) and malignant (Cancerous) ,these types must be diagnosed clearly for proper meditation and for proper treatment. A physician with full of experience and knowledge can deal complex problem  in the breast cancer  diagnosis process to identify disease but modern medical diagnosis system is totally based on data obtained through clinical  and/or other test ,most of the decision related to a patient to find out disease is taken based on these data  Better classification of a disease is a very crucial and challenging  job , a small error can cause the problem because it is directly related to the life of a human being. In  this  research work ,various intelligent techniques including supervised Artificial Neural Network (ANN) ,unsupervised Artificial Neural Network  ,Statistical and decision tree based have been applied to classify data related to breast cancer health care obtained from UCI repository site. The various individual models developed are tested and combined together to form  ensemble model .Experimental works were done using MATLAB and SPSS Clementine software obtained results shows that ensemble model is better than individual models accuracy obtained in case of ensemble model is ,which is higher than all individual models ,however counter propogation network (CPN) is a competitive model among all other individual models and accuracy of this model is very near to that is obtained in case of I ensemble model. In order to reduce dimensionality  of  breast cancer data set a ranking based feature selection technique is applied with best ensemble model ,experimental result show that model has less accuracy with less number of features .Models are also analyzed in terms of other error measures like sensitivity and specificity.

Decision Tree (DT), Supervised and Unsupervised Artificial Neural Network (ANN), Breast Cancer . Support Vector Machine (SVM).


1.  Bendi V.R., Prasad M. S. Babu andVenkateswarlu  N. B.(2012), A Critical Comparative Study of Liver Patients from USA and INDIA: An Exploratory Analysis, International Journal of Computer Science Issues, Vol.9. Issue 3 ,No. 2 ,PP 506-516.
2.    Bendi V. R., Prasad  M. S. Babu and  Venkateswarlu  N. B.(2011) ,A Critical Study of Selected   Classification Algorithms for Liver Disease Diagnosi, International Journal of  Database Management Systems (IJDMS), Vol.3, No.2,  PP 101-114.

3.    Bendi V. R (2011),A Critical Evaluation of Bayesian Classifier for Liver Diagnosis using Bagging and Boosting Methods, International Journal of  Engineering Sciences and Technology (IJEST) ,Vol.3,No. 4 PP 3422-3426.

4.   Obi J.C. and Imainvan A.A(2011) ,Decision Support System for the Intelligent Identification of Alzheimer using Neuro Fuzzy Logic ,International Journal of  Soft Computing (IJSC) ,Vol 2,No. 2 ,PP 25-38

5.    Elsayad, A. M. (2010). Predicting the severity of breast masses with ensemble of Bayesian classifiers. Journal of Computer Science, 6(5), 576-584.

6.    Jiawei Han, Kamber Micheline (2009). Data mining: Concepts and Techniques, Morgan Kaufmann       Publisher.

7. “UCI Machine Learning Repository of machine learning database”, University of California, school of Information and Computer Science, Irvine. C.A. http://www.ics.uci.edu/ last accessed on Dec  2012.

8.        Simon Heykens (1999) .Neural Network comprehensive foundation “ 2nd edition ,prentice hall.