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In this paper, a color image segmentation approach based on holographic thresholding and region merging is presented. The holographic image considers both the occurrence of the gray levels and the neighboring nearest value among-st pixels. Thus, it employs both the local and global information. Holographic analysis is performed using fuzzy entropy as a tool for finding all major kindred regions at the first stage followed by region merging process which is carried out based on color similarity among-st these regions to avoid over segmentation. The proposed Kindred -based approach (KOB) is compared with the histogram-based approach (HIB). The experimental results demonstrate that the KOB can find similar regions more effectively than HIB does, and thus can solve the problem of discriminating shading in color images to a greater extent.

Color Image Segmentation, Fuzzy Logic, Region Merge, Color Space, Thresholding

[1]. H. D. Cheng, Ying Sun, X. H. Jiang and Jingli Wang. �Color Image Segmentation: Advances and Prospects.�, Pattern Recognition, 2001.
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[4]. D. Tseng and C. H. Chang.�Color Segmentation Using Perceptual Attributes.� IEEE International Conference on Image �Processing-A,226-231,1992.
[5]. R. Ohlander, K. Price and Reddy D.R. �Picture Segmentation Using A Recursive Region Splitting Method.� Computer Graphics and Image Processing. 8, 310-333,1978.
[6]. N.Ito. et al., �The Combination of Edge Detection and Region Extraction in Non- parametric Color Image Segmentation� Information Sciences,92, 280-294,1996.
[7]. R. I. Taylor and Lewis P.H., �Color Image Segmentation Using Boundary Relaxation,� IEEE International Conference on Image Processing-C, 720-724,1992.
[8]. R. Schettini, �Segmentation Algorithm for Color Images,� Pattern Recognition Letter,14, 500-506,1993.
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[10]. P. K. Sahoo, et, al., �A Survey of Thresholding Techniques for image processing,� Computer Vision, Graphics and Image Processing, 41,255-260,1988.
[11]. L. Spirkovski. �A Summary of Image Segmentation Techniques� NASA Technical Memorandum 104022, June 1993.
[12]. C. H. Chen, �On the Statistical Image Segmentation Techniques,� Proceedings, IEEE Conference on Pattern Recognition and Image Processing, 260-266,1981.
[13]. P. W. M. Tsang and W. H. Tsang, �Edge Detection techniques on Object Color,� IEEE International Conference on Image Processing,C, 1040-1052,1996.
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[17]. T. Carron and P. Lambert, �Color Edge Detector Using Jointly Hue, Saturation and Intensity,� International Conference on Image Processing , Austin, USA, 975-985,1994.
[18]. M. Chapron, �A new Chromatic Edge Detector Used for Color Image Segmentation,� IEEE International Conference on Image Processing,A, 310-315,1992.
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G.S. Sudi, A.A. Gadgil, "Improved Color Image Segmentation using Kindred Thresholding and Region Merging," International Journal of Computer Sciences and Engineering, Vol.1, Issue.3, pp.1-9, 2013.

Wireless networking brings a whole new meaning to network security risk analysis and mitigation. With readily available equipment, attacks on wireless networks are very easy. The wireless security mechanism is not same as in wired networks. Because there is no user controlling for each individual node, wireless environment, and more importantly, scarce energy resources. The wireless security mechanism is not same as in wired networks. Because there is no user-controlling for each individual node, wireless environment, and more importantly, scarce energy resources. This paper looks at the basic risks inherent in wireless networking security protects a wireless network by denying access to the network itself before a user is successfully authenticated. This paper proposed a new security model which addresses three important types of active attacks like Rushing attack, Black hole and Replay attack. By using 3-roundof well known AES algorithm we implement this model. Thus it is easy for the administrator to identify these attacks using WPA. Different types of attack there related information, different cryptographic strength and performance of the proposed model get analyzed in this system. One particularly important improvement over the WPA standards is the inclusion of the Advanced Encryption Standard (AES) which could be used in many rounds to protect the overall network from the external attacks.

Wireless Network, Wireless Security, Wireless Threats, WEP, RC4, AES, IEEE 802.11, WPA

[1]. B. Parno, A. Perrig, and V.D. Gligor, �Distributed Detection of Node Replication Attacks in Sensor B. Parno, A. Perrig, and V.D. Gligor, �Distributed Detection of Node Replication Attacks in Sensor Networks,� Proc. IEEE Symposium. Security and Privacy, pp. 49-63, May 2005
[2]. Kai Xing Fang, Liu Xiuzhen, Cheng David, H. C. Du, Real-Time Detection of Clone Attacks in Wireless Sensor Networks Proceedings of the 28th International Conference on Distributed Computing Systems, 2008, Pages 3-10.
[3]. Klempous R.; Nikodem J.; Radosz, L.; Raus, N. Byzantine Algorithms in Wireless Sensors Network, Wroclaw Univ. of Technology .,Wroclaw; Information and Automation, 2006. ICIA2006.International Conference on, 15-17 Dec. 2006, pages :319-324
[4]. Mehmet Ulema and Barcin Kozbe, �Management of Next-generation Wireless Networks and Services�, IEEE Communications Managing, February 2003.
[5]. B. Parno, A. Perrig, and V.D. Gligor, �Distributed Detection of Node Replication Attacks in Sensor B. Parno, A. Perrig, and V.D. Gligor, �Distributed Detection of Node Replication Attacks in Sensor Networks,� Proc. IEEE Symposium. Security and Privacy, pp. 49-63, May 2005.
[6]. Y. Wang, G. Attebury, and B. Ramamurthy, �A Survey of Security Issues in Wireless Sensor Networks,� IEEE Communication. Surveys Tutorials, vol. 8, pp. 2�23, year 2006
[7]. Security in Mobile Ad Hoc Networks: Challenges and Solutions H. Yang, H. Luo, F. Ye, S. Lu, and L. Zhang IEEE Wireless Communications, Vol.11, Issue 1, pp. 38-47, 2004
[8]. Fluhrer, S., Mantin, I. and Shamir, A. 2001. Weaknesses in the Key Scheduling Algorithm of RC4, Selected Areas in Cryptography 2001, Lecture Notes in Computer Science, Vol. 2259, pp. 1-24. Springer.
[9]. Mead, N.R. and McGraw, G. 2003. Wireless Security�s Future, IEEE Security and Privacy, 1 (4), pp. 68-72.
[10]. Joseph Binder, Hans Peter Bischof, Zero Knowledge Proofs of Identityfor Ad Hoc Wireless Networks An In-Depth Study Technical Report, 2003

M. Amjad, "Wireless Network Security: Susceptibilities, Extortion and kiosk," International Journal of Computer Sciences and Engineering, Vol.1, Issue.3, pp.10-14, 2013.

Big Data concerns large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data is now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. However, big data entails a huge commitment of hardware and processing resources, making adoption costs of big data technology prohibitive to small and medium sized businesses. Cloud computing offers the promise of big data implementation to small and medium sized businesses. Big Data processing is performed through a programming paradigm known as MapReduce. Typically, implementation of the MapReduce paradigm requires networked attached storage and parallel processing. The computing needs of MapReduce programming are often beyond what small and medium sized business are able to commit. Cloud computing is on-demand network access to computing resources, provided by an outside entity. Common deployment models for cloud computing include platform as a service (PaaS), software as a service (SaaS), infrastructure as a service (IaaS) & hardware as a service (HaaS).

Big Data, Cloud computing, Map/Reduce

[1]. J. Dean and S. Ghemawa, �MapReduce: Simplified Data Processing on Large Clusters�, Google Labs, OSDI 2004, (2004), pp. 137�150.
[2]. Apache Hadoop Project, http://hadoop.apache.org/.
[3]. B. Stephens, �Building a business on an open source distributed computing�, Oreilly Open Source Convention (OSCON) 2009, (2009) July 20-24, San Jose, CA
[4]. W. Kim, �MapReduce Debates and Schema-Free�, Coord, (2010) March 3.
[5]. J. Lin and C. Dyer, �Data-Intensive Text Processing with MapReduce�, Tutorial at the 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL HLT 2010), (2010) June, Los Angeles, California
[6]. J. Woo, �Introduction to Cloud Computing�, the 10th KOCSEA 2009 Symposium, UNLV, (2009) December 18-19.
[7]. J. Woo, �The Technical Demand of Cloud Computing�, Korean Technical Report of KISTI (Korea Institute of Science and Technical Information), (2011) February.
[8]. J. Woo, �Market Basket Analysis Example in Hadoop�, http://dal-cloudcomputing.blogspot.com/2011/03/ market-basket-analysis-example-in.html, (2011) March.
[9]. Aster Data, �SQL MapReduce framework�, http://www.asterdata.com/product/advanced-analytics.php.
[10]. Apache HBase, http://hbase.apache.org/.
[11]. J. Lin and C. Dyer, �Data-Intensive Text Processing with MapReduce�, Morgan & Claypool Publishers, (2010).
[12]. GNU Coord, http://www.coordguru.com/.
[13]. J. Woo, D. -Y. Kim, W. Cho and M. Jang, �Integrated Information Systems Architecture in e-Business�, The 2007 international Conference on e-Learning, e-Business, Enterprise Information Systems, e-Government, and Outsourcing, Las Vegas, (2007) June 26-29.

P. Sharma, V. Garg, R. Kaur, S. Sonare , "Big Data in Cloud Environment," International Journal of Computer Sciences and Engineering, Vol.1, Issue.3, pp.15-17, 2013.

Session Initiation Protocol (SIP) is a signaling protocol developed by SIP working group specified by the Internet Engineering Task Force (IETF), SIP is a text-based protocol similar to SMTP and HTTP, used to create, manage and terminate sessions on IP data network at application layer. A session could be a simple two-way telephone call or it could be a collaborative multi-media conference session. Such sessions include peer-to-peer voice, video, chat, interactive games, and virtual reality. This makes possible to implement services like voice-enriched e-commerce, web page click-to-dial or Instant Messaging with buddy lists on IP based data network resulting in reduced costs, improved customer service and easily manageable communications architecture. SIP is designed to address the functions of signaling and session management within a packet based telephony network. Signaling allows call information to be carried across the network boundaries. Session management provides the ability to control the attributes of an end-to-end call. In recent years, SIP has been the choice for services related to Voice over IP (VoIP). It is a standard (RFC 3261) proposed by Internet Engineering Task Force (IETF). SIP is still growing and being modified to take into an account all relevant features as the technology expands and evolves.

SIP , IETF , SMTP, Text-Based Protocol

[1] J. rosenberg, h. schulzrinne, g. camarillo, a.johnston, j. peterson, r. sparks, m. handley, and e.schooler, sip: session initiation protocol," rfc 3261(proposed standard), jun. 2002, updated by rfcs 3265, 3853,4320, 4916. [online]. available:
http://www.ietf.org/rfc/rfc3261.txt
[2] Handley, m., v. jacobson, �sdp: session description protocol,� rfc 2327, april 1998.
[3] Schulzrinne, h., s. casner, r. frederick, and v. jacobson, �rtp: a transport protocol for real-time applications,� rfc 3550, july 2003.
[4] S. lanzisera, b. nordman, and r. brown, �data network equipment energy use and savings potential in buildings,� energy efficiency, vol. 5, pp. 149-162, 2012, 10.1007/s12053-011-9136-4.
[5] N. freed and n. borenstein, multipurpose internet mail extensions (mime) part one: format of internet message bodies," rfc 2045 (proposed standard), united states, 1996. [online]. available: http://www.ietf.org/rfc/rfc2045.txt.
[6] J. elwell, connected identity in the session initiation protocol (sip)," united states, 2007. [online]. available:
http://www.ietf.org/rfc/rfc4916.txt
[7] Stream control transmission protocol support in session initiation protocol proxy server by thomas kwok cheong pang b.a.sc. (computer engineering), simon fraser university, 1995.
[8] session initiation protocol , kk tan and hl goh. p.13101314 volume 2, ieee international conference on information technology, 11:th14:th of december 2002:
[9] in-stat - voip penetration forecast to reach 79% of us businesses by 2013
[10] S. baset, j. reich, j. janak, p. kasparek, v. misra, d. rubenstein, and h. schulzrinnne, �how green is ip-telephony?� in proceedings of the first acm sigcomm workshop on green networking, 2010, p. 7784.
[11] Walsh, steffan fries, national institute of standards and technologies. nist special publication 80058. january 2005, p. 3945.
[12] Design and implementation of a sipbased voip architecture , s. zeadally and f. siddiquini ieee aina 2004 sip, session initiation protocol used in voipkarin tybring,petra wahlund, zhu yunyun

A. Suryawanshi, M. Bhati, R. Dubey, "Session Initiation Protocol (SIP)," International Journal of Computer Sciences and Engineering, Vol.1, Issue.3, pp.18-21, 2013.

Handwritten Character recognition is one of the active and challenging areas of research in the intense field of Image Processing and Pattern recognition. It has large number of applications which includes, processing of bank cheques, reading aid for blind, conversion of any hand written document into digital form and many more. The main reason behind the activeness of the field are the challenges like the variation and distortion of handwritten characters, different style of writing and also the variety of scripts available across the entire world. This paper provides a brief review of the systems which implements various methodologies to recognize handwritten English characters.

Character recognition, Image Processing, Pattern recognition, Handwritten Character Recognition

[1] Sandeep Saha, Sayam Kumar Das Nabarag Paul. Sandip Kundu ,( 2013) �Optical Character Recognition using 40-point Feature Extraction and Artificial Neural Network� , International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 4.
[2] Nisha Sharma, Tushar Patnaik, Bhupendra Kumar,(2013) �Recognition for Handwritten English Letters�, International Journal of Engineering and Innovative Technology (IJEIT), Volume 2, Issue 7, January 2013.
[3] Apash Roy, N. R. Manna,�Handwritten Character Recognition Using Block wise Segmentation Technique (BST) in Neural Network�, International Conference on Intelligent Infrastucture .
[4] Om Prakash Sharma, M. K. Ghose, Krishna Bikram Shah, Benoy Thakur, (2013) �Recent Trends and Tools for Feature Extraction in OCR Technology�, International Journal of Soft Computing and Engineering (IJSCE), Volume-2, Issue-6.
[5] Ketan S.Machhale, Pradnya P. Zode, Pravin P. Zode, (2012) "Implementation of Number Recognition using Adaptive Template Matching and Feature Extraction Method", International Conference on Communication Systems and Network Technologies (CSNT).
[6] Tirtharaj Dash Tanistha Nayak,(2012) �English Character Recognition using Artificial Neural Network�, Proceedings of National Conference on AIRES-2012, Andhra University.
[7] Debi Prasad Bhattacharya & Susmita Koner,(2012)�ENGLISH Alphabet Recognition Using Chain Code And LCS�, Indian Journal of Computer Science and Engineering (IJCSE), Volume 3, Issue No 2.
[8] Dileep Kumar Patel, Tanmoy Som, Sushil Kumar Yadav, Manoj Kumar Singh, (2012) �Handwritten Character Recognition Using Multiresolution Technique and Euclidean Distance Metric�, Journal of Signal and Information Processing, pp 208-214.
[9] J.Pradeepa, E. Srinivasana, S. Himavathi,(2012) �Neural Network Based Recognition System Integrating Feature Extraction and Classification for English Handwritten�, IJE Transactions & Applications, Volume 25, Issue No 2.
[10] Md Fazlul Kader and Kaushik Deb, (2012) �Neural network-based English alphanumeric character recognition�, International Journal of Computer Science, Engineering and Applications (IJCSEA) Vol.2, No.4.
[11] Rajeshwar Dass, Priyanka, Swapna Devi(2012) �Image Segmentation Techniques�, IJECT Vol. 3, Issue 1, Jan. - March 2012
[12] Yusuf Perwej, Ashish Chaturvedi,(2011) �Machine Recognition of Hand Written Characters using Neural Networks�, International Journal of Computer Applications, Volume 14, Issue No.2, 0975 � 8887.
[13] J.Pradeepa, E. Srinivasana, S. Himavathi,(2011) "Diagonal Based Feature Extraction For Handwritten Character Recognition System Using Neural Network", 3rd International Conference on Electronics Computer Technology (ICECT), Volume 4 ,(2011)

S.U. Bohra, P.V. Ingole , "Review on Neural Network Based Approach Towards English Handwritten Alphanumeric Characters Recognition," International Journal of Computer Sciences and Engineering, Vol.1, Issue.3, pp.22-25, 2013.

Detecting and segmenting moving objects in dynamic scenes is a hard but essential task in a number of applications such as surveillance. Most existing methods only give good results in the case of persistent or slowly changing background, or if both the objects and the background are rigid. It is a difficult task to segment the moving object in the existence of dynamic background. Different kinds of methods exist in this paper to solve the problem of motion detection and motion segmentation. This paper tells us about the various methods used to detect objects under dynamic conditions, where each method is explained in brief along with its merits and demerits.

Image Processing, Segmentation, Histogram, Moving Object Detection

Aurelie Bugeau Patrick Perez, �Detection and segmentation of moving objects in highly dynamic scenes�, Proc. Int. Conf. Computer Vision.
[2] Andrea Cavallaro and Touradj Ebrahimi , �Accurate Video Object Segmentation Through Change Detection�, Proc. Int. Conf .Signal Processing Institute.
[3] Yaakov Tsaig and Amir Averbuch,�Automatic Segmentation of Moving Objects in Video Sequences: A Region Labeling Approach� IEEE Transactions On Circuits And Systems For Video Technology, Vol. 12, No. 7, July 2002.
[4] Rita Cucchiara, Costantino Grana, Massimo Piccardi, and Andrea Prati,�Detecting Moving Objects, Ghosts, and Shadows in Video Streams�IEEE Transactions On Pattern Analysis And Machine Intelligence,Vol. 25, No. 10, October 2003.
[5] Gagandeep Kaur�Detection of Moving Objects in Colour based and Graph�s axis Change method� International Journal of Computing & Business Research.
[6] Chang Liua, PongC.Yuena,GuopingQiu, �Object motion detection using information theoretic spatio-temporal saliency �, published in Elsevier journal 2009.
[7] Tao Yang , Stan Z.Li , Quan Pan, Jing Li �Real-Time and Accurate Segmentation of Moving Objects in Dynamic Scene�, published in ACM transactions.
[8] R.Cucchiara, C.Grana, M.Piccardi, A.Prati, �Statistic and Knowledge-based Moving Object Detection in Traffic Scenes�.
[9] Vijay Mahadevan and Nuno Vasconcelos �Unsupervised Moving Target Detection In Dynamic Scenes�.
[10] Bohyung Han, Larry S. Davis, Fellow, �Density-Based Multi-Feature Background Subtraction with Support Vector Machine� IEEE Transactions On Pattern Analysis And Machine Intelligence.
[11] Feng Liu and Michael Gleicher, �Learning color and locality cues for moving object detection and segmentation�.
[12] Amit K Agrawal and Rama Chellappa �Moving object segmentation and dynamic scene reconstruction using two frames�.
[13] Yuanlu Xu, Liang Lin �Moving object segmentation by pursuing local spatio-temporal manifolds� April 17, 2013
[14] Ivan Laptev, Serge J. Belongie, Patrick P�erez and Josh Wills, �Periodic Motion Detection and Segmentation via Approximate Sequence Alignment�.
[15] Jinglan Li,�Moving Objects Segmentation Based on Histogram for Video Surveillance�, published in Modern Applied Science Vol. 3, No. 11, November, 2009.

L. Kala, R. Hemavathy, "A Review on Segmentation of Moving Object Under Dynamic Condition," International Journal of Computer Sciences and Engineering, Vol.1, Issue.3, pp.26-31, 2013.

This paper analyses trends in page loading time which is an important part of any website�s user experience. And many times we�ll let it slide to accommodate better aesthetic design, new nifty functionality or to add more content to web pages. Unfortunately, website visitors tend to care more about speed than all the bells and whistles we want to add to our websites. Additionally, page loading time is becoming a more important factor when it comes to search engine rankings.

Container object (CO), External objects (EOs), Websites, html

[1] Stave Souders, High performance Websites:Essential Knowledge for Front-End Engineers, O�Reilly Media. September 2007.
[2] Bob Wescott, The Every Computer Performance Book.
[3] Microsoft Corproation, Perfirmance Testing Guidance for Web Application.
[4] Andrew B. King, Jakob Nielsen, Speedup Your Site: Website Optimization.
[5] Scoot Ware, Michael Tracy, Louis Slothouber, Robert Barker, Professional Website optimization, 1998.
[6] Patrick Killelea, Web Performance Tunning, 1998.
[7] Daniel A. Menasce, Virgilio A. F. Almeida, Performance: Metrics,Models and Methods.
[8] Brennan Stehling, Pro ASP.NET for SQL Server: High Performance data Access for Web developers.
[9] (2012) Google developer Website. [Online]. Available: https://developers.google.com/speed/articles
[10] (2012) Website Optimization Website. [Online]. Available: http://www.websiteoptimization.com/
[11] (1998) Wrox Press Website.[Online]. Available: http://msdn.microsoft.com/en-us/library/ms953263.aspx

J. Manhas, "A Study of Factors Affecting Websites Page Loading Speed for Efficient Web Performance," International Journal of Computer Sciences and Engineering, Vol.1, Issue.3, pp.32-35, 2013.

4G refers to the fourth generation of wireless communications. Two emerging technologies Mobile WiMAX standard and Long Term Evolution (LTE) standard are being considered as candidates for the fourth generation (4G) of mobile networks. But initial versions of these two were not able to fulfill the requirement set by International Telecommunications Union. In this paper a comparison of their later versions WiMAX2 and LTE-Advance standards has been made.

LTE-Advanced;WiMAX;4G;MIMO;Carriear Aggregation

[1] http://www.4gon.co.uk/solutions/introduction_to_4g.php.
[2] http://en.wikipedia.org/wiki/4G.
[3] http://computer.howstuffworks.com/wimax1.htm.
[4] http://en.wikipedia.org/wiki/LTE_Advanced
[5] http://www.radio-electronics.com/info/cellulartelecomms/lte-long-term-evolution/4g-lte-advanced-carrier-channel-aggregation.php.
[6] http://www.radio-electronics.com/info/antennas/mimo/multiple-input-multiple-output-technology-tutorial.php.
[7] http://www.radio-electronics.com/info/cellulartelecomms/lte-long-term-evolution/4g-lte-advanced-relaying.
[8] Eberle, Dieter. "LTE vs. WiMAX 4th generation telecommunication networks." Berlin Institute of Technology, Germany.
[9] http://www.3gpp.org/LTE-Advanced
[10] Scarfone, Karen, Cyrus Tibbs, and Matthew Sexton. "Guide to securing WiMAX wireless communications." NIST Special Publication 800 (2010): 127.
[11] http://lteworld.org/blog/what-wimax-2-and-what-it-promises
[12] http://www.telecom-cloud.net/wp-content/uploads/2010/07/qos-over-4g-networks.pdf

R. Singh, "4G By WiMAX2 and LTE-Advance," International Journal of Computer Sciences and Engineering, Vol.1, Issue.3, pp.36-38, 2013.

One of the most important metrics in the design of IP mobility protocols is the handover performance. Handover occurs when a mobile node changes its network point-of attachment from one access router to another. If not performed efficiently, handover delays, jitters and packet loss directly impact and disrupt applications and services. With the Internet growth and heterogeneity, it becomes crucial to design efficient handover protocols that are scalable, robust and incrementally deployable. The current Mobile IP (MIP) standard has been shown to exhibit poor handover performance. Most other work attempts to modify MIP to slightly improve its efficiency, while others propose complex techniques to replace MIP.

handover, heterogeneity, deployable, Mobile IP

[1]. A. Helmy, "A Multicast-based Protocol for IP Mobility Support", ACM Second International Workshop on Networked Group Communication (NGC 2000), ACM SIGCOMMsponsored, Palo Alto, November 2000.
[2]. C. Perkins, �IP Mobility Support�, RFC 2002, Internet Engineering Task Force, October 1996.
[3]. C. Perkins, D. Johnson, �Route Optimization in Mobile IP�, Internet Draft, Internet Engineering Task Force, February 2000.
[4]. C. Perkins and D. Johnson, �Mobility Support in IPv6�,Proceedings of MobiCom�96, November 1996.
[5]. J. Mysore, V. Bharghavan, �A New Multicasting-based Architecture for Internet Host Mobility�, roceedings of ACM MobiCom, September 1997.
[6]. S. Seshan, H. Balakrishnan, R. Katz, �Handovers in Cellular Wireless Networks: The Daedalus Implementation and Experience�, Kluwer Journal on Wireless Networks, 1995.
[7]. S. Kumar, P. Radoslavov, D. Thaler, C. Alaettinoglu, D. Estrin, M. Handley, �The MASC/BGMP Architecture for Interdomain Multic.
[8]. L. Breslau, D. Estrin, K. Fall, S. Floyd, J. Heidemann, A. Helmy, P. Huang, S. McCanne, K. Varadhan, Y. Xu, H. Yu, "Advances in Network Simulation", IEEE Computer, vol. 33, No. 5, p. 59-67, May 2000.
[9]. E. Gustafsson, A. Jonsson, C. Perkins, Mobile IP Regional Registration, Internet-draft, draft-ietf-mobileip-reg-tunnel-02, March 2000.
[10]. R. Ramjee, T. La Porta, L. Salgarelli, S. Thuel, K. Varadhan, L. Li, �IP-based access network infrastructure for next-generation wireless data networks�, IEEE Personal Communications, Volume: 7 Issue: 4, Page(s): 34 �41, Aug. 2000.
[11]. R. Hinden, S. Deering, "IP Version 6 Addressing Architecture", Internet Draft, draft-ietf-ipngwg-addr-arch-v3-06.txt, July 2001.
[12]. R. Hinden, M. O`Dell, S. Deering, "An IPv6 Aggregatable Global Unicast Address Format", RFC 2374, July 1998.
[13]. A. Helmy, �State Analysis and Aggregation Study for Multicast-based Micro Mobility�, IEEE International Conference on Communications (ICC), May 2002.
[14]. A. Snoeren, H. Balakrishnan, �An End-to-End Approach to Host Mobility�, Accepted to ACM MobiCom �00, August 2000.

V.G. Babu , "Efficient Mobility Using Multicast Routing Mechanisms," International Journal of Computer Sciences and Engineering, Vol.1, Issue.3, pp.39-46, 2013.