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Today, the use of web technologies in education allows envisaging new learning forms, giving a preponderant place to the social dimension. However, with the emergence of these new orientations, are also developed difficulties in implementing pedagogical contents adapted to this new type of learning (collaborative, cooperative, etc.). This work is at the heart of this issue. It seeks to find conceptual and computer solutions, both at the pedagogical and technical levels, for computer modeling of pedagogical knowledge, which should be in adequacy with current learning practices. It gives itself as main objective to develop a reference model for production of distance learning contents adapted to the socioconstructivist learning context. Thus, this work proposes to develop a Socioconstructivist Model of Collaborative Learning Design (SMC-LD) of distance learning contents. In this model, the process of content development is based on socioconstructivist approach and focuses on two main aspects of production of learning content: "design" and "development". At the level "design", SMC-LD suggests a collaborative design process based on the concept of life cycle. At the level "development", SMC-LD proposes a process for educational modeling, upstream of SCORM and IMS-LD standards, describing pedagogical content using scenarios and activities. The modeling process is facilitated by an author tool to produce interoperable and reusable learning objects. To implement the proposed approach, XML and Java technologies were used.

Socioconstructivism; learning design; collaborative design; development; learning object; distance learning; norm and standard

[1] D.A. Wiley, �Connecting learning objects to Instructional design theory: a definition, a methaphor, and taxonomy�. In Wiley (Ed), The Instructional Use of Learning Objects. Agency for Instructional Technology and Association for Educational Communications of Technology, Bloomington, Indiana, 2002.
[2] A. El Mhouti, A. Nasseh and M. Erradi, �An Evaluation Model of Digital Educational Resources�, International Journal of Emerging Technologies in Learning, Volume-8, No-2, Page 29�35, May 2013
[3] A. El Mhouti, A. Nasseh and M. Erradi, �Development of a Tool for Quality Assessment of Digital Learning Resources�, International Journal of Computer Applications, Vol-64, No-14, Page 27�31, Feb 2013.
[4] F. Trillaud, "Architecture pour le contr�le des interactions et le pilotage d�une application interactive multi-utilisateurs � ex�cution adaptative : application � un environnement de FOAD", Doctoral dissertation, University of La Rochelle, France, 2013.
[5] L. Cormier, "Le soutien au d�veloppement de ressources num�riques pour l�enseignement et l�apprentissage dans les universit�s qu�b�coises", 80�me Congr�s de l�ACFAS, 2012.
[6] A. Battou, "Approche granulaire des objets p�dagogiques en vue de l�adaptabilit� dans le cadre des Environnements Informatiques pour l`Apprentissage Humain", Doctoral dissertation, Ibn Zohr University, Morocco, 2012.
[7] N. Zniber and C. Cauvet, "Mod�le orient� service pour la conception de parcours p�dagogiques personnalis�s", Doctoral dissertation, Aix-Marseille University, France, 2009.
[8] L. Oubahssi, "Conception de plates-formes logicielles pour la formation � distance, pr�sentant des propri�t�s d`adaptabilit� � diff�rentes cat�gories d`usagers et d`interop�rabilit� avec d`autres environnements logiciels", Doctoral dissertation, Ren� Descartes University, France, 2005.
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[10] R. Boughacha and H. Aliane, "Syst�me de productions de contenus p�dagogiques multilingues", International Conference on Artificial Intelligence and Information Technology (ICA2IT `14), Ouargla, Algeria, 2014.
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[14] A. El Mhouti, A. Nasseh and M. Erradi, �A Socio-constructivist Model of Development of Learning Content in an e-learning Platform Oriented to Management of Academic Knowledge�, E-Learn World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, Las Vegas, United States, Page No 74-80, Oct 21, 2013.
[15] SCTIC (Sous-comit� sur les technologies de l�information et de la communication), "Les normes et standards de la formation en ligne, �tats des lieux et enjeux ", 2002.
Retrieved from:
http://www.crepuq.qc.ca/IMG/pdf/norm-0210-d-rapport.pdf
[16] ADLNet, �Advanced Distributed Learning, Documentation Suite (SCORM 2004 4th Edition.)�, 2014. Retrieved from: http://www.adlnet.gov/scorm/scorm-2004-4th/
[17] R. Koper, �Educational modeling language: adding instructional design to exiting specifications�, Technical report, Educational Expertise Technology Center, Open University of Netherlands, 2002.
[18] R. Koper, �Modeling units of study from a pedagogical perspective. The pedagogical meta-model behind EML�. Open University of the Netherlands, 2002.
[19] P. Laforcade, �Towards a UML-based Educational Modeling Language�, in the Proceeding of Fifth IEEE International Conference on Advanced Learning Technologies (ICALT`05), ISBN 0-7695-2338-2 Kaohsiung, Taiwan, July 05-08, 2005.
[20] IMS, �IMS Learning Design Best Practice and Implementation�, Technical report, 2003.
[21] N. Bousbia and A. Balla, "Processus de mod�lisation de contenus p�dagogiques destin�s � la FOAD", Revue �lectronique des technologies de l`information (e-TI), No 3, 2007.
[22] O. Catteau and P. Vidal, "Le Cycle de Vie de l�Objet P�dagogique et de ses M�tadonn�es", Doctoral dissertation, Paul Sabatier University, France, 2008.
[23] X. Ochoa, J. Klerkx, B. Vandeputte and E. Duval, �On the Use of Learning Object Metadata: The GLOBE (Global Learning Objects Brokered Exchange) Experience�, Lirias KU Leuven, 2011.
[24] S. Kannan and T. Pushparaj, �A Study on Variations of Bottlenecks in Software Testing�, International Journal of Computer Sciences and Engineering, Volume-2, Issue-5, Page No 8-14, May 2014.

A.E. MHOUTI, A. NASSEH, Moh.ERRADI, "Design and implementation of a Socioconstructivist Model of Collaborative Learning Design (SMC-LD) dedicated to distance learning," International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.1-10, 2014.

Now a day the internet was generating an explosion in growth of data in the form of data sets called Big Data that are complex to store, manage and analyze using conventional RDBMS that is used for Online Transaction Processing (OLTP) only. This new data is not only unstructured, voluminous but even more difficult to control, the cost of hardware and software infrastructure required to crunch it using conventional RDBMS. To exploit on the Big Data trend, a new type of Bigdata technologies (like Hadoop, HBase, PIG, HIVE, SQOOP,OOZIE, APACHE FLUME, MAHOUT) have developed by many companies that leverages new paralleled processing, commodity machines, open source framework to capture and analyze these new data sets. Bigdata presents a performance better than the existing Database or Data Warehouse or Business Intelligence systems. In this study we shall know how the emergent Bigdata is controlled for managing huge volume of data. This paper also lays out the ecosystem of big data technology that has been evolving rapidly.

Bigdata, Flume, DBMS, HBase, HIVE, Mahout, OOZIE, PIG, RDBMS, SQOOP

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[4]. Digital Universe Study (on behalf of EMC Corporation): Big Data, Bigger Digital Shadows, and Biggest Growth in the Far East 2012.
[5]. DunrenChe, MejdlSafran, and ZhiyongPeng, From Big Data to Big Data Mining: Challenges, Issues, and Opportunities, DASFAA Workshops 2013, LNCS 7827, pp. 1�15, 2013.
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[7]. Ekpe Okorafor1 and Mensah Kwabena Patrick : Availability of jobtracker machine in Hadoop/MapReduce Zookeeper coordinated clusters in Advanced Computing: An International Journal ( ACIJ ), Vol.3, No.3, May 2012
[8]. Esteves RM, Rong C: Using Mahout for Clustering Wikipedia�s Latest Articles: A Comparison between K-means and Fuzzy C-means in the Cloud in the proceedings of IEEE Third International Conference on Cloud Computing Technology and Science (Cloud Com �11) 2011 IEEE pp 565�569.
[9]. Esteves RM, Pais R, Rong C: K-means Clustering in the Cloud � A Mahout Test. IEEE International Conference on Advanced Information Networking and Applications (WAINA �11) 2011.
[10]. GrzegorzMalewicz, Matthew H. Austern, Aart J. C. Bik, James C.Dehnert, Ilan Horn, NatyLeiser, and GrzegorzCzajkowski,Pregel: A System for Large-Scale Graph Processing, SIGMOD‟10, June 6�11, 2010, pp 135-145.
[11]. Garhan Attebury. "Hadoop distributed file system for the Grid", 2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC), 10/2009
[12]. J. Dean and S. Ghemawat, �MapReduce: Simplified data processing on large clusters,� in USENIX Symposium on Operating Systems Design and Implementation, San Francisco, CA, Dec. 2004, pp. 137�150.
[13]. Jefry Dean and Sanjay Ghemwat, MapReduce: A Flexible Data Processing Tool, Communications of the ACM, Volume 53, Issuse.1,January 2010, pp 72-77.
[14]. Karmasphere: Deriving Intelligence from Big Data in Hadoop: A Big Data Analytics Primer 2011.
[15]. Kyuseok Shim, MapReduce Algorithms for Big Data Analysis, DNIS 2013, LNCS 7813, pp. 44�48, 2013.
[16]. McKinsey Global Institute: Big data: The next frontier for innovation, competition, and productivity 2011.
[17]. OnurSavas, YalinSagduyu, Julia Deng, and Jason Li,Tactical Big Data Analytics: Challenges, Use Cases and Solutions, Big Data Analytics Workshop in conjunction with ACM Sigmetrics 2013,June 21, 2013.
[18]. Owen S, Anil R, Dunning T, Friedman E, Manning Publications: Mahout in action. Chapter 8. Shelter Island, N.Y; 2012:130-144.
[19]. Poornima Sharma, Varun Garg , Prof. Randeep Kaur , Prof. Satendra Sonare , "Big Data in Cloud Environment", Int. Journal of Computer Sciences and Engineering, Volume01, Issue-03, Page No (15-17), Nov 2013.
[20]. Ren, Shengbing, and Dieudonne Muheto. "A Reactive Scheduling Strategy Applied On MapReduce OLAM Operators System", Journal of Software, 2012.
[21]. Sanjay Ghemawat and Jeffrey Dean, �MapReduce: Simplified data processing on large clusters,� in OSDI`04: Proceedings of the 6th Symposium on Operating Systems Design and Implementation. USENIX Association, 2004.
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[24]. Shen, Qingni, Yahui Yang, Zhonghai Wu, Dandan Wang, and Min Long. "Securing dataservices: a security architecture design for private storage cloud based on HDFS", International Journal of Grid and Utility Computing, 2013.
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[29]. Wang, Lizhe, Jie Tao, Rajiv Ranjan, Holger Marten, Achim Streit, Jingying Chen, and DanChen. "G-Hadoop:MapReduce across distributed data centers for data-intensive computing", Future Generation Computer Systems, 2013.
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P.N. Priyanka, S.V. Phaneendra, "Study on Migration from conventional File System to advancement of Bigdata Technologies in the real world," International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.11-20, 2014.

Cloud computing is growing as a new paradigm of large-scale distributed computing. It is an agenda for permitting appropriate, on-demand network access to a shared pool of computing resources. Load balancing is the foremost challenges in cloud computing which is vital to distribute the dynamic amount of workload through multiple nodes to confirm that no single node is overwhelmed. Cloud computing is an innovative technology which practices virtual machine instead of physical machine to manage, store and network the different mechanisms. In different virtual machines load balancers are used for assigning load in such a way that none of the nodes gets loaded heavily or lightly. The research area in load balancing is becoming more interested in the cloud computing. And through better load balancing in cloud, the performance is increased and user gets improved services. Here in this paper we have discussed different load balancing techniques along with the proposed technique used to solve the issue of data migration and data security using P-AES.

Cloud Computing, Virtual Machine Migration, Grid Computing, Load Balancing

[1] Parneet Kaur, Sachin Majithia �Various Aspects For Data Migration In Cloud Computing And Related Reviews�, Volume-2, Issue-7 30 July, 2014,
[2] Yatendra sahu, M. K. Pateriya �Cloud Computing Overview and load balancing algorithms�, Internal Journal of Computer Application Vol-65 No.24, 2013.
[3] S. Mohana Priya, B. Subramani,� A new approach for load balancing in cloud computing�, International Journal of Engineering and Computer Science, ISSN: 2319-7242 Volume 2 Issue 5 May, 2013 Page No. 1636-1640
[4] R.G.Rajan , V.Jeyakrishnan, �A Survey on Load Balancing in Cloud Computing Environments�, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 2, Issue 12, December 2013
[5] P. Salot, �Asurvey of various scheduling algorithm in cloud computing environment�, IJRET, Volume: 2 Issue: 2, Feb 2013
[6] A.K. Sidhu, S. Kinger, �Analysis of Load Balancing Techniques in Cloud Computing�, International Journal of Computers & Technology,Volume 4 No. 2, ISSN 2277-3061, March-April, 2013,
[7] S. Mohana Priya, B. Subramani,� A new approach for load balancing in cloud computing�, International Journal of Engineering and Computer Science, ISSN: 2319-7242 Volume 2 Issue 5 May, 2013 Page No. 1636-1640,
[8] Suresh M., Shafi Ullah Z., Santhosh Kumar B.,� An Analysis of Load Balancing in Cloud Computing�, International Journal of Engineering Research & Technology (IJERT),Vol. 2 Issue 10, October � 2013, ISSN: 2278-0181,
[9] N. Sran, N. Kaur, �Comparative Analysis of Existing Load Balancing Techniques in Cloud Computing�, International Journal of Engineering Science Invention ,Volume 2 Issue 1, PP.60-63,ISSN (Online): 2319 � 6734, ISSN (Print): 2319 � 6726, January. 2013,
[10] N. Ajith Singh, M. Hemalatha, �An approach on semi distributed load balancing algorithm for cloud computing systems� International Journal of Computer Applications Vol-56 No.12 2012,
[11] Jasmin James, Dr.Bhup endraVerma �EFFICIENT VM LOAD BALANCING ALGORITHM FOR A CLOUD COMPUTING ENVIRONMENT� International Journal on Comp uter Science and Engineering (IJCSE),September 2012,
[12] Jasp reetKaur et al. � Comparison of load balancing algorithms in a Cloud�, International Journal of En gin eerin g Research and Applications (IJERA), May-Jun 2012,
[13] Nidhi Jain Kansal, Inderveer Chana �Existing Load balancing Techniques in cloud computing: A systematic review� Journal of Information system and communication Vol-3 Issue-1 2012,
[14] Peter Mell, Timothy Grance, The NIST Definition of Cloud Computing, NIST Special Publication 800-145, September 2011,
[15] "Load Balancing, Load Balancer.. http://www.zeus.comlproducts/zxtmlb/index.html, January 2010,
[16] "What is Cloud Computing?,�
http://www.zeus.comlcloud_computinglc1oud.html, January 2010,
[17] A. Bhadani, and S. Chaudhary, �Performance evaluation of web servers using central load balancing policy over virtual machines on cloud�, Proceedings of the Third Annual ACM Bangalore Conference (COMPUTE), January 2010,
[18] Shufen Zhang, Shuai Zhang, Xuebin Chen, Shangzhuo Wu. Analysis and Research of Cloud Computing System Instance. Future Networks, 2010, pp 88-92,
[19] Z. Zhang, and X. Zhang, �A Load Balancing Mechanism Based on Ant Colony and Complex Network Theory in Open Cloud Computing Federation�, Proceedings of 2nd International Conference on Industrial Mechatronics and Automation (ICIMA), Wuhan, China, May 2010, pages 240- 243,
[20] A. Singh, M. Korupolu, and D. Mohapatra, �Server-storage virtualization: integration and load balancing in data centers�, Proceedings of the ACM/IEEE conference on Supercomputing (SC), Nov 2008,
[21] K.Q., Van, et aI., "A Hybrid Load Balancing Policy Underlying Grid Computing Environment. Computer Standards & Interfaces, Vol. 29,Issue 2, pp 161-173,2007,
[22] N. Shivaratri, P. Krueger, and M. Singhal. Load distributing for locally distributed systems.IEEE Computer, 25(12), pp. 33-44, December 1992.

P. Kaur, S. Majithia, "Implementation and Analysis of Replicated Agent Based Load Balancing In Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.21-27, 2014.

Cognitive Radio (CR) has risen as a tempting solution to the problem of spectral inefficiency as it performs sensing of the radio environment, sharing it without harmful interference to Primary Users (PU) and quickly quitting the frequency band if the corresponding licensed user emerges. Spectrum Sensing is the most crucial task for the establishment of cognitive radio based communication mechanism. Challenges related to spectrum sensing are discussed and different sensing techniques are surveyed in this paper along with the analysis of their advantages and disadvantages.

Cognitive Radio, spectrum sensing techniques, sensing challenges

[1] A.S.B.Kozal, M.Merabti, and F.Bouhafs, �An Improved Energy Detection Scheme for Cognitive Radio Networks in Low SNR Region�, IEEE Symposium on Computers and Communications (ISCC), pp: 000684 � 000689, 2012.
[2] A.Sahai, D.Cabric, �Cyclostationary Feature Detection� ppt at Berkeley Wireless Research Center, 2005.
[3] E.Varadharajan and M.Rajkumari, �Discrete Wavelet Based Spectrum Sensing in Cognitive Radios using Eigen filters�, International Journal of Advanced Engineering Technology, IJAET/Vol.III/Issue I/389-391, 2012.
[4] Federal Communications Commission, �Notice of proposed rulemaking and order: Facilitating opportunities for flexible, efficient, and reliable spectrum use employing cognitive radio technologies�, ET Docket No. 03-108, 2003.
[5] I.F.Akyildiz, B.F.Lo, R.Balakrishnan, �Cooperative spectrum sensing in cognitive radio networks: A survey�, Physical Communication 4, 40�62, 2011.
[6] J.Lehtomaki, �Analysis of Energy Based Signal Detection� Ph.D, dissertation, University of Olu, Finland, 2005.
[7] J.Unnikrishnan and V.V.Veeravalli, �Cooperative Sensing for Primary Detection in Cognitive Radio�, IEEE journal of selected topics in signal processing, vol. 2, no.1, 2008.
[8] K.Kyouwoong, I.A.Akbar, K.K.Bae, J.Um, C.M.Spooner and J.H.Reed, �Cyclostationary Approaches to Signal Detection and Classification in Cognitive Radio� IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, Dublin, Ireland, pp. 212-215, 2007.
[9] L.Thanayankizil, A.Kailas, �Spectrum Sensing Techniques (II): Receiver Detection and Interference Management�, 2008.
[10] M.Subhedar and G.Birajdar, �Spectrum Sensing Techniques in Cognitive Radio Networks�, International Journal of Next-Generation Networks (IJNGN) Vol.3, No.2, 2011.
[11] S.Kapoor, SVRK.Rao and G.Singh, �Opportunistic Spectrum Sensing by Employing Matched Filter in Cognitive Radio Networks�, International Conference on Communication Systems and Network Technologies, 2011.
[12] S.Mishra, A.Sahai and R.W. Brodersen, �Cooperative Sensing among Cognitive Radios�, IEEE ICC proceedings, 2006.
[13] S.S.Jeng, J.M.Chen, H.Z.Lin and C.W.Tsung, �Wavelet-Based Spectrum Sensing for Cognitive Radios using Hilbert Transform�, World Academy of Science, Engineering and Technology, 2011.
[14] S.S.Prasad, R.Gandhiraj, K.P.Soman, �Multi-User Spectrum Sensing based on Multi-Taper Method for Cognitive Environments�, International Journal of Computer Applications (0975 � 8887) Volume 22� No.9, 2011.
[15] T.Yucek and H.Arslan, �A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications�, IEEE Communication Surveys and Tutorials, vol.11, no.1, pp: 116-130, 2009.
[16] X.Chen, S.Nagaraj, �Entropy Based Spectrum Sensing in Cognitive Radio�, Wireless Telecommunications Symposium, 2008.
[17] Y.L.Zhang, Q.Y.Zhang and T.Melodia, �A Frequency-Domain Entropy-Based Detector for Robust Spectrum Sensing in Cognitive Radio Networks�, IEEE communications letters, vol. 14, no. 6, 2010.
[18] Z.Quan, S.J.Shellhammer, W.Zhang and A.H.Sayed, �Spectrum Sensing by Cognitive Radios at Very Low SNR� IEEE "GLOBECOM" proceedings, 2009.

N.K. Randhawa, A.V. Buttar, "Sensing of Spectrum Holes in Cognitive Radio Networks: A Survey," International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.28-34, 2014.

MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key. Many real world tasks are expressible in this model, as shown in the paper. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The run-time system takes care of the details of partitioning the input data, scheduling the program`s execution across a set of machines, handling machine failures, and managing the required inter-machine communication. This allows programmers without any experience with parallel and distributed systems to easily utilize the resources of a large distributed system. Our implementation of MapReduce runs on a large cluster of commodity machines and is highly scalable: a typical MapReduce computation processes many terabytes of data on thousands of machines. Programmers find the system easy to use: hundreds of MapReduce programs have been implemented and upwards of one thousand MapReduce jobs are executed on Google`s clusters every day. Due to the exponential growth of information technology, tremendous amount of data is generated. It is important to sort meaningful information from the scattered big data. So Data mining plays a vital role in many of these applications [1]. In order to speed up the mining process we go for parallel and distributed processing. However, sorting distributedly is not an easy task since in distributed environment, irregular and imbalanced computation loads may cause the overall performance to be greatly degraded. Load balance among processors is thus very important to parallel and distributed mining. In this work, a new sorting is proposed using Mapreduce technique over the hadoop framework for distributed processing. A popular free implementation is Apache Hadoop. The Hadoop stack is a data processing platform. It combines elements of databases, data integration tools and parallel coding environments into a new and interesting mix. One advantage Hadoop has over data integration tools is that it�s accessible to a variety of programming languages, which means it can be used for any arbitrary parallel coding, like complex analytics.

Big data, Structured Big data, Hadoop, HDFS MapReduce, PI

[1] Mahesh Maurya, Sunita Mahajan, " Performance analysis of mapreduce Programs on Hadoop cluster", World Congress on Information and Communication Technologies pp. 506-510, March, 2012.

[2] Jeffrey Dean and Sanjay Ghemawat �mapreduce: Simplified Data Processing On Large Clusters�, Google, Inc., Usenix Association OSDI �04: 6th Symposium on Operating Systems Design and Implementation, 2009.
[3]Http://En.Wikipedia.Org/Wiki/Mapreduce
[4] Http://en.wikipedia.org/wiki/Apache_Hadoop
[5]Aditya B. Patel, Manashvi Birla, Ushma Nair, �Addressing Big Data Problem Using Hadoop and Map Reduce�, 2012 NIRMA University International Conference On Engineering, Nuicone-2012, 06-08december, 2012.

R. Murugesh, I. Meenatchi, "A Study Using PI on: Sorting Structured Big Data In Distributed Environment Using Apache Hadoop MapReduce," International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.35-38, 2014.

A Mobile Ad hoc network (MANET) is an intelligent automated dynamically distribution of wireless Mobile independent nodes they either connect straightforwardly or utilizing halfway node(s) without any predefined infrastructure. If there is no predefined infrastructure then networks get unprotected to number of attacks and elevated amount security turns into a real concern. The first section discusses brief introduction, features and routing protocols of MANET. The second section discusses the vulnerabilities in MANET. Mobile ad-hoc network (MANET) is one of the most necessary fields for study, development and research of wireless networks. Mobile Ad Hoc Networks (MANETs) has become one of the most frequent areas of research because of the security challenges it faces to its related protocols. The third section discusses the security challenges in routing protocols in MANET. The final section discusses Intrusion Detection Techniques (IDT), IDS architecture and conceptual model of IDS agent. MANET nodes are extensively changing & joining the mobile network. It is not possible to record the freed accomplished by node(s) in a dynamic network. Some of these nodes can become rogue and can become danger as these nodes belong to the trusted zone. This challenge is overcome by assigning a temporary id to each node. The paper proposes a novel algorithm to generate and assign a unique id for the nodes that are freed.

Mobile Ad Hoc Networks, attacks, IDS, Routing Protocols, Schema, Temporary UID Algorithm

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[6] Mayank Kumar and Tanya Singh, A survey on Security Issue in Mobile Ad-hoc Network & Solutions, International Journal of Computer Science and Engineering, pages 68-72, March 2014.
[7] Yongguang Zhang and Wenke Lee, Security in Mobile Ad-Hoc Networks, in Book Ad Hoc Networks Technologies and Protocols (Chapter 9), Springer, 2005.
[8] Panagiotis Papadimitraos and Zygmunt J. Hass, Securing Mobile Ad Hoc Networks, in Book The Handbook of Ad Hoc Wireless Networks (Chapter 31), CRC Press LLC, 2003.
[9] Yi-an Huang and Wenke Lee, A Cooperative Intrusion Detection System for Ad Hoc Networks, in Proceedings of the 1st ACM Workshop on Security of Ad hoc and Sensor Networks, Fairfax, Virginia, 2003, pp. 135 � 147.
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[20] Jim Parker, Anand Patwardhan, and Anupam Joshi, Detecting Wireless Misbehavior through Cross-layer Analysis, in Proceedings of the IEEE Consumer Communications and Networking Conference Special Sessions (CCNC�2006), Las Vegas, Nevada, 2006.
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M. Kumar, Muskan, Rohtash, "Security Challenges in Routing Protocols and a Proposed Schema in MANET," International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.39-44, 2014.

The Voting process is heart of democracy and India is largest democracy in the world where every citizen above 18 years has right to vote. For good democracy, a voting system should be correct, transparent and fully authentic. Biometrics technology is very advanced and more accurate in secure and feasible authentication to the voters. The proposed voting system is mainly for those people who are not capable to come to the voting booth. This electronic voting machine is more secured and better than exiting voting process. The advancement in wireless and web technologies given rise to the new applications in e-Government services such as online tax filing, license renewal, and benefits claims. The proposed work uses android mobile OS to develop an application and fingerprint supported biometric control information to make voting process more secure. Using android smart mobile device makes the system even more robust.

Electronic Voting, Mobile Voting, Android, Open Source OS, Fingerprinting Technology

[1] Election Commission of India. Election laws. http://eci.nic.in/eci_main/ElectoralLaws/electoral_law. asp.
[2] A. K. Agarwala, D. T. Shahani, and P. V. Indiresan. Report of the expert committee for evaluation of the upgraded electronic voting machine (EVM). Sept. 2006.http://www.scribd.com/doc/6794194/ Expert-Committee-Report-on-EVM, pages 2�20.
[3] Electronic Voting (2009), Available from http://www.hwskioskprinter.com/terminology_electronicvoting.pdf
[4] Hari K. Prasad_ J. Alex HaldermanyRopGonggrijp Scott Wolchoky Eric Wustrowy Arun Kankipati_ Sai Krishna Sakhamuri_ VasavyaYagati_ _Netindia, Security Analysis Of India�s Electronic Voting Machines Hyderabad Y The University Of Michigan April 29, 2010
[5] D. Ashok Kumar, T. Ummal Sariba Begum A Novel design of Electronic Voting System Using Fingerprint International Journal Of Innovative Technology & Creative Engineering (Issn: 2045-8711) Vol.1 No.1 January 2011
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[7] Xiao, Q., and H. Raafat (1991). "Fingerprint image post processing: A combined statistical and structural approach." Pattern Recognition, 24(10), 1991: 985-992.
[8] Giampiero E.G. (2007):�E-Voting through the Internet and with Mobile Phones�, Statistical Office Canton Zurich, Switzerland
[9] Speckmann, B (2008). The Android mobile platform. Michigan: Eastern Michigan University, 2008.
[10] Mike Cleron, �Androidology: Architecture overview,� http://www.youtube.com /watch? v=Mm6Ju0xhUW8, November 2007.
[11] WWW.developer.android.com

P.S. Ghatol, N. Mahale, "Biometrics Technology based Mobile Voting Machine," International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.45-49, 2014.

Cryptography is one of the important sciences in the current era. It is a science of secret writing. It is the art of protecting the information by transforming it into an unreadable format in which a message can be concealed from the casual reader and only the intended recipient will be able to convert it into original text .Cryptography renders the message unintelligible to outsider by various transformations. Data Cryptography is the scrambling of the content of data like text, image, audio and video to make it unreadable or unintelligible during transmission. Its main goal is to keep the data secure from unauthorized access. The importance of cryptography comes from the intensive digital transactions which we daily perform on the internet and other communication channels. Visual cryptography, an emerging cryptography technology, uses the characteristics of human vision to decrypt encrypted images. It needs neither cryptography knowledge nor complex computation. For security concerns, it also ensures that hackers cannot perceive any clues about a secret image from individual cover images. A visual cryptography scheme encodes a black and white secret image into n shadow images called shares which are distributed to the n participants. Such shares are such that only qualified subsets of participants can �visually�� recover the secret image. Elliptical curves are mathematical NP-hard problems, which are proofed to be intractable in term of complexity. Cryptography has efficiently utilized the strength EC in developing several cryptosystems such as key agreement protocols, digital signatures and others. Elliptic Curve Cryptography (ECC) usage is with smaller key to give high security and high speed in a low bandwidth. ECC is considered as the best method for upcoming applications. There are number of existing cryptographic approaches. In this present work, we have defined a hybrid cryptography approach with the combination of biometric key concept and the Elliptical Curve Cryptography (ECC). ECC is a public key cryptography having equal and attractive significance over RSA algorithm with smaller key size. It is based on geometric elliptical curve design algorithm. In this work, the authentication of the user will be verified based on the user information as well as the signature. It means the cryptography will be performed over the text information as well as on digital signature. This two layer scheme will improve the security for the authentication. The proposed algorithm is implemented on both text and image for encoding and decoding purpose. All the implementation work has been done in MATLAB R2009 using general MATLAB toolbox and image processing toolbox. Encryption time, decryption time and size of encrypted data have been taken as parameter for evaluation of performance of algorithm.

Elliptic Curve Cryptography (ECC), Cryptography, Biometric Image, Text, Encryption, Decryption.

[1]. Farshid Delgosha, and Faramarz Fekri, �Public-Key Cryptography Using Paraunitary Matrices� IEEE transaction on signal processing, vil. 54, no. 9, September 2006.
[2]. Sean O�Melia and Adam J. Elbirt, �Enhancing the Performance of Symmetric-Key Cryptography via Instruction Set Extensions� transaction on very large on very large scale integration system, Vol. 18, No. 11, November 2010.
[3]. Zhimin Chen and Patrick Schaumont, �A Parallel Implementation of Montgomery Multiplication on Multicore Systems: Algorithm, Analysis, and Prototype� IEEE Transaction on computers, Vol. 60, No. 12, December 2011.
[4]. Daniel Page and Frederik Vercauteren , �A Fault Attack on Pairing-Based Cryptography� IEEE Transaction on computers, Vol. 55, No. 9, September 2006.
[5]. Zhi Zhou, Gonzalo R. Arce, Giovanni Di Crescenzo, �Halftone Visual Cryptography� IEEE Transaction on image processing, Vol. 15, No. 8, August 2006.
[6]. Ohood S. Althobaiti1 and Hatim A. Aboalsamh, �An Enhanced Elliptic Curve Cryptography for Biometric�.
[7]. Gururaja.H.S., M.Seetha, Anjan.K.Koundinya, �Design and Performance Analysis of Secure Elliptic Curve Cryptosystem� International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 8, August 2013.
[8]. Vaibhav Choudhary, Kishore Kumar, Pravin Kumar and D.S. Singh, �Modified Pixel Sieve Method for Visual Cryptography� Indian Journal of Computer Science and Engineering, Vol. 1 No. 4 321-326.

A. Kukreja, Ayushi , "Design and Evaluation of Performance for Text and Image Cryptography Using Biometric Key and ECC," International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.50-55, 2014.

Mobile ad hoc network (MANET) is a collection of mobile nodes that communicate with each other without any fixed infrastructure or a central network authority. From a security design perspective, MANETs have no clear line of defense; i.e. no built-in security. Thus, the wireless channel is accessible to both legitimate network users and malicious attackers. Since MANET requires a unique, distinct, and persistent identity per node in order for their security protocols to be viable, Sybil attacks pose a serious threat to such networks. A Sybil attacker can either create more than one identity on a single physical device in order to launch a coordinated attack on the network or can switch identities in order to weaken the detection process, thereby promoting lack of accountability in the network. Here a lightweight scheme is used to detect the new identities of Sybil attackers without using centralized trusted third party or any extra hardware, such as directional antennae or a geographical positioning system. Through the help of extensive simulations, it is able to demonstrate that this scheme detects Sybil identities with good accuracy even in the presence of mobility.

Legitimate Network, Sybil Identity, Received Signal Strength

[1]. Douceur J R (2002), �The Sybil attack�, Revised Papers from the First International Workshop on Peer-to-Peer Systems, Vol.6, No.9, pp.251 -260.
[2]. Capkun S, Hubaux J P and Buttyan L (2006), �Mobility helps peer-to-peer security�, IEEE Trans. Mobile Comput., Vol. 5, No. 1, pp.43 -51.
[3]. Piro C, Shields C and Levine B N (2006), �Detecting the Sybil attack in mobile ad hoc Networks�,Proceeding. Securecomm Workshops, pp.1 -11.
[4]. Chen Y, Yang J, Trappe W and Martin R P (2010), �Detecting and localizing identity- based attacks in wireless and sensor networks�, IEEE Trans. Veh. Technol., Vol. 59, pp.2418 -2434.
[5]. Abbas S, Merabti M, Llewellyn-Jones D, Kifayat K (2013), �Lightweight Sybil Attack Detection in MANETs�, IEEE Systems Journal, Vol.7 , No.2 pp.236-248.
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H. Muthukrishnan, S. Anandamurugan, "Light Weight Security Attack in Mobile Ad Hoc Network (MANET)," International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.56-61, 2014.

In the contemporary world Spring Application Framework is the most prevalently used application framework due to its IoC (Inversion of Control) property. Many of the Spring developers simply do programming with less concern towards optimized processing. Though Spring Framework offers sundry ways of programming techniques to reach the same end, certain practices are pre requisite to ensure that consequences will be prolific. This paper proposes miscellaneous, simple, reliable, flexible and easy techniques to make programs more efficient. The exploration in this paper would serve as a benchmarking tool for assessing best programming practices. Experimental results of analysis designate that maintainability, flexibility and reusability are enhanced.

Spring Best Practices; Spring Tuning; Spring Tactics; Spring Core; Spring Framework Tactics; Efficient Spring Practices

[1] Rod Johnson, Juergen Hoeller, Alef Arendsen, Thomas Risberg, Colin Sampaleanu, �Professional Java Development with the Spring Framework�, Wiley Publishing, Copyright 2005.
[2] Willie Wheeler, �Spring in Practice�, Manning Publications, Copyright 2013.
[3] Gary Mak, Josh Long, Daniel Rubio, �Spring Recipes�, 2nd Edition, Apress Publications.Copyright 2010.
[4] http://en.wikipedia.org/wiki/Spring_Framework reffered on 27th December, 2013.

V.K. Myalapalli, "High Performance Spring Programming," International Journal of Computer Sciences and Engineering, Vol.2, Issue.8, pp.62-69, 2014.