iosr-JCE   International Conference on Advances in Engineering & Technology – 2014 (ICAET-2014)

Abstract: In this paper we considered the method of describing the telecommunication system providing VoD services using hierarchical structure with optimization and security features. Today we have seen that many times, during the downloading process of various videos, there will be disturbance or hanging and failures due to the low bandwith and other technical problems. In this paper we are proposing some methodologies to remove such type of failures by using the concepts of optimization of bandwidth which describes the relationship between the structural elements at each hierarchical level of the multi-layer graph. Video Transferring is resource (like band-width) consuming task and it require an optimal configuration of the system. The proposed hierarchical structure makes it possible to consider the telecommunication system as a whole and avoid any failure in the local optimum when solving optimization problem as well as providing some security features. Also some techniques are proposed for band-width reduction.

Keywords : Video on Demand, Proxy nodes, Topology synthesis, Multi-Layer graph.

[1] D. V. Ageyev, "Simulation of modern telecommunication systems with multi-layer graphs usag"], Problemi telekomunikaci}, no} (1), pp. 23 34, 2010, http://pt. joumal. kh.ua/ 2010/1/1/ lOl_ ageyev _simulation. Htm
[2] D. V. Ageyev "The method of describing the structure of modern telecommunication systems using multi-layer graph", Eastern European Journal of Enterprise Technolopgies, No 6/4 (48), pp. 56-59, 2010.
[3] D. V. Ageyev, "Method of designing telecommunication systems using flow model for multi-layer graph", Problemi telekomunikaci}, N02(2), pp. 7 - 22, 2010, http://pt. journal. kh. ua/20l0/2/2/ 102_ ageyev _layer. htm.
[4] Micha Pioro, "Deepankar Medhi Routing, Flow, and Capacity Design in Communication and Computer Networks". Elsevier, 2004, 765 p.
[5] SongYuan PAN, Qing GUAN, Sheng XU, "Optimizing Video Processing Algorithm with Multidimensional DMA Based on Multimedia DSP" ICCP 2010 Proceedings.

Abstract: This paper proposes Android Based Tracking for EMS (Emergency Medical Services)on cloud, that directs the emergency patients to most nearest and appropriate hospital for his emergency in an unknown area. It also describes amobile system that enables electronic healthcare data storage, update and retrieval using Cloud Computing. It is observed that people in unknown area are in severe danger if they didn't able to find hospital quickly. In emergency case a single minute counts. So it is very important that automatic applications must be used for decision making, Maintain up to date status of the hospital and saving the time which can save life of the patient. The proposed system locates nearest available hospital, contacts its ambulance emergency system, accesses a Electronic Health Record of emergency patient that can critically assist in pre-hospital treatments. The system will identify availability of the nearest available specialized hospital all through EMS server which provides continuous information about the incoming patient to the hospital. Keywords –Emergency Medical Service, Hospital Tracking, Electronic Health Record, Architectural Model.

[1]Yuanyuan Du, Yu Chen, Dan Wang, Jinzhao Liu, Yongqiang Lu," An Android-Based Emergency Alarm and Healthcare Management System" 978-1- 61284-704-7/11/$26.00 ©2011IEEE.

[2]Li-Linchen," An Emergency Medical Service Support System For Patients In Rural Areas - An Example From Taiwan" Proceedings of the 2012 International Conference on Machine Learning and Cybernetics, Xian, 15-17 July, 2012.

[3]Hsiao-Hsien Rau, Chien-Yeh Hsu, Ajit Kumar, Ni-Chun Hung," Identification Of Variables To Decide Optimal Hospital For Emergency Patients" 978-1-4244-9666-2/11/$26.00 ©2011 IEEE.

[4] Inkyung Sung Taesik Lee," Modeling Requirements For An Emergency Medical Service System Design Evaluator" Proceedings of the 2012 Winter Simulation Conference C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A.M. Uhrmacher.

[5] Abdelmajid Khelil," Pa2Pa: Patient to Patient Communication for Emergency Response Support"2011 IEEE 13th international conference on E-Health networking,Application and services.

[6]Charalampos Doukas, Thomas Pliakas, and Ilias Maglogiannis," Mobile Healthcare Information Management utilizing Cloud Computing and Android OS" 32nd Annual International Conference of the IEEE EMBS Buenos Aires, Argentina, August 31 - September 4, 2010.

[7]Armstrong, N. , Nugent C.D. , Moore G. ,Finlay D.D.," Developing smartphone applications for people with Alzheimer's disease, Information Technology and Applications in Biomedicine"2010 10th IEEE International Conference on, 3-5 Nov. 201.

Abstract: Phishing is nothing but an attempt made by an individual or group to thieve personal confidential information such as password, credit card information, Transaction Number etc. from unsuspecting victims for identity theft and fraudulent activities. Since the importance of smart phones is increased day to day as more applications are deployed and executed. In this paper, a new approach named as "An Efficient Anti phishing method based on Visual Cryptography using cloud technique by smart phones" to solve the problem of phishing. The visual cryptography is explored to preserve the privacy image Captcha by decomposing it into two shares that are stored in cloud (data severs) such that, when original Captcha can be revealed when the both are available at same time. Since users are unable to carry the Captcha place to place so a concept of Image Captcha conversion into String with the help of cloud is revealed which can be used as the password.

Keywords: Cloud,Phishing, String, Share, Security, Smart phones, Visual Cryptography.

[1] Thiyagarajan, P.; Venkatesan, V.P.; Aghila,G."Anti-Phishing Technique using Automated Challenge Response Method'", in Proceedings of IEEE- International Conference on Communications and Computational Intelligence, 2010.

[2] Sun Bin.; Wen Qiaoyan.; Liang Xiaoying.; "A DNS based Anti-Phishing Approach," in Proceedings of IEEE- Second International Conference on Networks Security, Wireless Communications and Trusted Computing, 2010

[3] JungMin Kang, DoHoon Lee, "Advanced White List Approach for Preventing Access to Phishing Sites", 2007 International Conference on Convergence Information Technology, ICCIT 2007, p 491-496, 2007.

[4] Nirmal, K.; Ewards, S.E.V.; Geetha, K.; "Maximizing online security by providing a 3 factor authentication system to counter-attack 'Phishing'", in Proceedings of IEEE- International Conference on Emerging Trends in Robotics and Communication Technologies, 2010. [5] Tianyang Li.; Fuye Han.; Shuai Ding and Zhen Chen.; "LARX: Large-scale Anti-phishing by Retrospective Data-Exploring Based on a Cloud Computing Platform", in Proceedings of IEEE- 20th International Conference on Computer Communications and Networks, 2011.

[6] M.Naor and A. Shamir, "Visual cryptography," in Proc. EUROCRYPT, 1994, pp. 1–12. International Journal of Distributed and Parallel Systems (IJDPS) Vol.3, No.1, January 2012 218

. [7] T. Monoth and A. P. Babu, .Recursive Visual Cryptography Using Random Basis Column Pixel Expansion, in Proceedings of IEEE International Conference on Information Technology, 2007, pp. 41- 43. [8] C. M. Hu and W. G. Tzeng, .Cheating Prevention in Visual Cryptography,. IEEE Transaction on Image Processing, vol. 16, no. 1, Jan-2007,pp. 36-45.

[9] "The NIST Definition of Cloud Computing". National Institute of Standards and Technology, Retrieved 24 July 2011.

[10]. Jaya "Securing Cloud Data and Cheque Truncation System with Visual Cryptography" International Journal of Computer Applications (0975 – 8887) Vol. 70– No.2, May 2013

Abstract: The Privacy preserving routing is crucial in Mobile ad-hoc network for this require stronger privacy protection. An unobservable secure routing protocol provides complete unlinkability and content unobservability on Mobile Ad-hoc Network. An Unobservable Secure Routing Protocol also helpful to prevent wormhole attack on privacy protection that is based on group signature & public key encryption with multipath RREQ and their timestamp. This technique detect suspicious node with the network, trying to become isolate all suspicious node or any suspicious route, will not consider for transmission & traffic is transmitted via another shortest path.

KEYWORDS :routing protocols, security, privacy, wormhole attack.

[1] Zubair Ahmad Khan‖Wormhole Attack: A New detection technique‖, @2012 IEEE
[2] Pushpraj Niranjan,Prashant Srivastava,Raj Kumar Soni, Ram Pratap ―Detection of wormhole attack using Hop-count time delay analysis‖, IJSRP,vol2,issue4,2012
[3] Zhinguo Wan,Kui Ren, Ming Gu ―USOR: An unobservable Secure On-Demand Routing Protocol for Mobile Ad Hoc Networks‖ Procedding IEEE Transaction on Wireless Communication,vol11,No.5,May 2012
[4] Soo-Young Shin,Eddy Hartono Halim,‖Wormhole Attacks Detection in Manet using route redundancy and Tim-based Hop Calculation‖, ICTC 2012,IEEE
[5] P.Thamizharasi, D.Vinoth,‖ Unobservable Privacy –Preserving Routing in MANET‖, IJESE 2013, vol 2, Issue-3, Jan.
[6] Y. Hu, A. Perrig, and D. B. Johnson, ―Packet Leashes: A Defense Against Wormhole Attacks in Wireless Ad Hoc Networks,‖ Proceedings of IEEE INFOCOM 2003, vol. 3, pp. 1976-1986, April 2003.
[7] N. Karthikeyan, B. Bharathi, S. Karthik, ― Performance Analysis of the Impact of Broadcast Mechanisms in AODV, DSR and DSDV‖, Proceedings of the 2013 International Conference on PRIME 2013

Abstract: One of the most active research areas for computer science and telecommunication researcher is the wireless sensor networks. Usually after the deployment of sensor nodes in the hazardous, hostile or remote areas, these nodes work on their own. These sensors nodes will have to perform their function with scare and none replenish able power resources. One of the main design objectives for these networks is Energy efficiency. This paper presented the obstacle and challenges in the design and development of power aware medium access control protocol for wireless sensor networks.

Keywords: Energy Efficiency, Medium Access Control, Wireless Sensor Network.

[1] Salman Faiz Solehria , Sultanullah Jadoon: Medium Access Control Protocol for Wireless Sensor Network – a Survey, International Journal of Video & Image Processing and Network Security IJVIPNS-IJENS Vol: 11 No: 03. (June 2011).

[2] I. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci: A Survey on Sensor Networks, IEEE Communication Magazine, pp. 102-114 (August 2002).

[3] Wei Ye, J.Heidemann and D. Estrin: An Energy- Efficient MAC Protocol for Wireless Sensor Networks, IEEE INFOCOM, New York, Vol. 2, pp. 1567-1576 (June 2002).

[4] Tijs van Dam, Koen Langendoen: An Adaptive Energy Efficient MAC Protocol for Wireless Networks, in Proceedings of the First ACM Conference on Embedded Networked Sensor Systems (November 2003).

[5] Changsu Suh, Young-Mi Song, Young-Bee Ko, and We Duke Cho: Energy Efficient & Delay Optimized MAC for Wireless Sensor Networks, in Proceedings of the Workshop in the Seventh International Conference on Ubiquitous Computing (Ubicomp'05) (September 2005).

[6] Rajesh Yadav, Shirshu Varma and N.Malaviya: Optimized Medium Access Control for Wireless Sensor Network, IJCSNS International Journal of Computer Science and Network Security, Vol. 8, No.2, pp. 334 -338 (February 2008).

[7] V. Rajendran, K. Obraczka and J.J. Gracia- Luna-Aceves: Energy Efficient, Collision Free Medium Access Control for Wireless Sensor Networks, in ACM International Conference on Embedded Networked Sensor Systems (SenSys), pp. 181-192 (November 2003).

[8] L. Bao and J.J. Garcia-Luna-Aceves: A New Approach To Channel Access Scheduling for Ad Hoc Network, in Seventh Annual International Conference on Mobile Computing and Networking, pp. 210-221 (2001).

[9] M. Ali, Saif, A. Dunkels, T. Voigt, K. Romer, K. Langendoen, J. Polastre, Z. A. Uzmi: Medium Access Control Issues in Sensor Networks, ACM SIGCOMM Computer Communication Review, Vol. 36, No. 2 (April 2006). [10] K. Sohrabi, J.Gao, V.Ailawadhi and G.J.Pottie: Protocols for Self Organization of a Wireless Sensor Network, IEEE Personal Communication, Vol. 7, Issue 5, pp. 16-27 (October 2000).

Abstract: Human brain mainly works on electric signals transmitting all over the body to send the information in order to operate the body parts. Even while rotating eye ball body increases or decreases the resistance near eye area. This variation in electric signals can be measured using electrodes or the myoelectric sensors. By implementing these signals processor we can interface different devices to control on demand. Hence proposed system is designed to control computer and hardware system using brain waves electric signals. Proposed systems will detection the variations in electric signal strength through voltage level near the eye area and generates a wireless radio frequency signals in order to control the robotic prototype model. By implementing this system we can further extend it to bio enabled human body parts to control through brain waves.

Keywords: Brain–computer interface (BCI),Electrocorticography (EOG), Electroencephalography(EEG), Mind-Machine Interface (MMI), Brain–Machine Interface (BMI)

[1] Z. Hong and T. He, "Achieving Range-Free Localization Beyond Connectivity," Proc. Seventh ACM Conf. Embedded Network Sensor Systems (Senses), 2009.

[2] Jie Liu and Ping Zhou, Senior Member, IEEE, "A Novel Myoelectric Pattern Recognition Strategy for Hand Function Restoration After Incomplete Cervical Spinal Cord Injury" ieee transactions on neural systems and rehabilitation engineering, vol. 21, no. 1, january 2013

[3] H. Krebs, L. Dipietro, S. Levy-Tzedek, S. Fasoli, A. Rykman-Berland, J. Zipse, J. Fawcett, J. Stein, H. Poizner, A. Lo, B. Volpe, and N. Hogan, "A paradigm shift for rehabilitation robotics," IEEE Eng. Med. Biol. Mag., vol. 27, no. 4, pp. 61–70, Jul./Aug. 2008.

[4] C. Pang, G. Sheen, Y. Zhang, Y. Li, and K. Tan, "Beep Beep: A High Accuracy Acoustic Ranging System using COTS Mobile Devices," Proc. Fifth Int'l Conf. Embedded Networked Sensor Systems (Sensys), 2007.

[5] A. T. Au and R. F. Kirsch, "EMG-based prediction of shoulder and elbow kinematics in able-bodied and spinal cord injured individuals," IEEE Trans. Rehabil. Eng., vol. 8, no. 4, pp. 471–80, Dec. 2000.

[6] J. G. Hincapie and R. F. Kirsch, "Feasibility of EMG-based neural net- work controller for an upper extremity neuroprosthesis," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 17, no. 1, pp. 80–90, Feb. 2009.

[7] L. Dipietro, M. Ferraro, J. J. Palazzolo, H. I. Krebs, B. T. Volpe, and N. Hogan, "Customized interactive robotic treatment for stroke: EMG- triggered therapy," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 13, no. 3, pp. 325–334, Sep. 2005.

Abstract: Brain Fingerprinting is a technique used to find the unique brain-wave pattern generated by brain when a person encounters a familiar stimulus. It is based on fact that brain is central to all human acts. Brain is always there, planning, executing and recording the objects to which we encounters in the form of image, video or text. So my research says that, if we think about very personal object then something unique related to that strikes in our mind and unique brain-wave will be generated by our brain which can be used as passwords. As no one can read our mind or personal object in this case, it will be the most unbreakable password.

Keywords –Brain-Waves, EFG, MERA, MERMER

[1] Prof. Dinesh Chandra Jain and Dr. V.P. Pawar, The Brain Fingerprinting Through Digital. Electroencephalography Signal Technique, International Journal on Computer Science and Engineering, IJCSE11-03-03-047.

[2] Dr. Farwell and Smith SS, Brain Fingerprinting, Journal of Forensic Sciences, 2001.

[3] Farwell LA and Smith SS, Using Brain MERMER Testing To Detect Concealed Knowledge Despite Efforts To Conceal Journal of Forensic Sciences 2001.

[4] Vrushen Pawar, S.C.Meherotra and Arun Marwale, Digital EEG through sensitivity analysis of Electrography signal to human expression, IEEE Transaction MAN and Sybaritic, Manuscript Number SMCA06-08-0244,USA 2007.

[5] Frances M.Dyro, The EEG Handbook, Clinical Neurophysiology, Laboratory Massachusetts, London,1989.

Abstract: Intrusions have been a major problem in terms of computing resources such as grid computing, ubiquitous computing ,cloud computing, distributed computing and so on. Intrusions are hard to detect but there has been a lot of work done on detecting and removing the intrusions .The focus of intrusion detection should be mainly on detecting the intrusions at the system resources and at the network level for a predefined network. This paper mainly focuses on cloud computing a method which is infrastructure less and provides free system resources to the users. As clouds are distributed in nature , it becomes an easy target for the intruders to exploit the vulnerabilities of the network. The solution proposed for years is the use of intrusion detection system at various levels depending on the applications for which the detection is to be provided. The paper covers the study of intrusion detection system implemented in cloud environment for dealing with various security issues related to cloud. The various parameters considered for comparison are detection technique, types of attacks addressed, advantages, disadvantages and performance.

KEYWORDS: CIDSS, Cloud Computing, Flow matrix, IDS, KF Sensor, Log management.g

Introduction to Cloud Computing white paper Dialogic , 2010 Sanjay Ram M , Velmurugan N and Thirukumaran S, "Effective Analysis of Cloud Based Intrusion Detection System" , IJCAIT, Vol 1-issue 2, September 2012. Thoran Rodrigues, "Cloud Security: Technology, Processes, Responsibility", The Enterprise Cloud, May 29,2012. M. Sudha and M. Monica, "Investigation on Efficient Management of Workflows in Cloud Computing Environment", IJCSE, Vol. 2, No. 05, 2010. Soumya Mathew and Ann Preetha Jose, "Securing Cloud from Attacks based on Intrusion Detection System", IJARCCE, Vol. 1, Issue 10, December 2012. Amirreza Zarrabi and Alireza Zarrabi, "Internet Intrusion Detection System Service in Cloud", IJCSI, Vol. 9, Issue 5, No. 2, September 2012. M. Kuzhalisai and G. Gayathri, "Enhanced Security in Cloud with Multi-Level Intrusion Detection System", IJCCT, Vol. 3, Issue 3, 2012.

Abstract: In many countries the amount of crime incidents that is reported per day is increasing significantly. Concerning about India, the department of Police is the major organization of preventing crimes. In general, Indian police stations utilize paper-based information storing systems and they don't employ computer based applications up to a great coverage. Due to this utilization of paper-based systems police officers have to spend a lot of time as well as human resources to analyze existing crime information and to identify suspects for crime incidents. So the requirement of an efficient way for crime investigation has arisen. Business Intelligence practices are one aspect of crime investigation, for which numerous techniques are available. This paper highlights the use of business intelligence techniques, clustering and classification for effective investigation of crimes. Further the paper aims to identify suspects by analyzing existing evidences in situations where any witness or forensic clues are not present.

Keywords -Business Intelligence, Classification, Clustering, Crime Identification, Data Mining

[1] Karel, JANEČKA, Hana, HŮLOVÁ, "Using Spatial Data Mining to Discover the Hidden Rules in the Crime Data", GIS Ostrava 2011, 23. – 26. 1. 2011, Ostrava
[2] Malathi. A, Dr. S. Santhosh Baboo, "An Enhanced Algorithm to Predict a Future Crime using Data Mining, International Journal of Computer Applications",(0975 – 8887)Volume 21– No.1, May 2011
[3] Jeroen S. de Bruin, Tim K. Cocx, Walter A. Kosters, Jeroen F. J. Laros and Joost N. Kok,"Data Mining Approaches to Criminal Career Analysis",Leiden Institute of Advanced Computer Science (LIACS)
[4] Sara Hajian, Josep Domingo-Ferrer and Antoni Mart´ınez-Ballest´," Discrimination Prevention in Data Mining for Intrusion and Crime Detection",IEEE 2011.
[5] Fatih OZGUL, Claus ATZENBECK, Ahmet CELIK , Zeki ERDEM," Incorporating data sources and methodologies for crime data mining", IEEE 201,176-180.
[6] Chung-Hsien Yu1, Max W. Ward1, Melissa Morabito2, and Wei Ding1," Crime Forecasting Using Data Mining Techniques", 11th IEEE International Conference on Data Mining Workshops,IEEE 2011,779-786.
[7] Revatthy Krishnamurthy, J. Satheesh Kumar," Survey of Data Mining Techniques on Crime Data Analysis", International Journal of Data Mining Techniques and Applications, December 2012,117-120.
[8] Fang Jin, Wei Wang, Yi Xiao, Zhenhe Pan,"Proposal of Crime Data Mining Project".
[9] Prof. Hanmant N. Renushe, Prof. Prasanna R. Rasal, Prof. Abhijit S. Desai," Data Mining Practices for Effective Investigation of Crime", International Journal Computer Technology & Applications,2012, 865-870.
[10] Devesh Bajpai , "Emerging Trends in Utilization of Data Mining in Criminal Investigation: An Overview", Journal of Environmental Science, Computer Science and Engineering & Technology, June-August, 2012,124-131,

Abstract: This work proposes to develop and implement a model of an efficient unmanned Metro Train using train scheduling software with automated control system. Model developed for Metro Train with sensors, control system and GPS to control train remotely and prevent trains from disaster. Through the exchange of information between train and computer server control unit, the train schedule software produces more reliable and precise core train control data , trains starts moving or stop according to generated data instructions. This generated data instructions will stored in terminal stations as in cache, this cache can be used as a backup if computer server get down. If two trains come on same track or two trains become in front of each other then train will be automatically stop, this activity can be seen on computer's screen. The integrated date allows us to calculate permitted speed and generate supervising profile that ensures the safety of automatic train protection.

Keywords -unmanned Metro Train, sensors , control system, GPS

[1] Jih-Wen Sheu,Wei-Song Lin,"Adaptive Optimal Control for Designing Automatic Train Regulation for Metro Line,"IEEE Trans.Control System Technology,vol.20,no.5,Sep-2012.

[2] Dewang Chen, Yidong Li,"Online Learning Algorithm for Train Automatic Stop Control Using Precise Location Data of Balises,"IEEE Trans.Intelligent Trasportation System,vol.35,no.7,Mar-2013.

[3]W.S. Lin,"Automatic train regulation for metro lines using dual heuristic dynamic programming",IEEE, June-2010.

[4] H.Dong,B.Gao,"Fuzzy-PID soft switching speed of automatic train operation system,"IEEE Control System Technology,vol.25,no.5,June-2010.

[5] F.Y. Wang,"Agent-based control for networked traffic management systems," IEEE Intell.Syst.,vol20,no.5,Oct.2005

[6] Xiaoqing Zeng, Masayuki Matsumoto,"Integration of Automatic Train Control System", IEEE 2002.

[7] Bascetta, L., "Anti-collision systems for robotic applications based on laser Time-of-Flight sensors", IEEE 2010

Abstract: The problem of identifying and isolating misbehaving nodes that refuses to forward packets in wireless ad hoc networks. In this paper integration of reputation module, route discovery module and audit module are discussed. This system effectively and efficiently isolates both continuous and selective packet droppers. 2ACK and Principle of flow of conservation (PFC) techniques are used for detection of misbehaving link and misbehaving node simultaneously. The 2ACK technique detects the misbehaving link but it cannot decide which node is misbehaving from that link. Hence, that information from 2ACK technique is given to principle of flow of conservation (PFC) technique for detection of misbehaving node. As misbehaving nodes are listed from wireless ad hoc network route discovery is carried out by avoiding that misbehaving nodes.

Keywords: Ad hoc networks,Link misbehavior, Node misbehavior, Packet dropping, Reputation system, Wireless communications.

[1] Yu Zhang, Loukas Lazos and William Jr. Kozma. "AMD: Audit-based Misbehavior Detection in Wireless Ad Hoc Networks", IEEE transactions on mobile computing, vol. x, no. x, 2012.

[2] Shirina Samreen, G. Narasimha. "An Efficient Approach for the Detection of Node Misbehaviour in a MANET based on Link Misbehaviour", 2013 3rd IEEE International Advance Computing Conference (IACC), IEEE 2012.

[3] Rahul Raghuvanshi, Rekha Kaushik , Jyoti Singhai. "A Review of Misbehaviour Detection and Avoidance Scheme in Adhoc Network" , IEEE 2011. [4] Sonja Buchegger. "Self-Policing Mobile Ad Hoc Networks by Reputation Systems", IEEE Communications Magazine, July 2005. [5] Yanbin Liu, Yang Richard Yang. "Reputation Propagation and Agreement in Mobile Ad-Hoc Networks",IEEE 2003.

[6] Q. He, D. Wu, and P. Khosla. "SORI: A secure and objective reputation-based incentive scheme for ad hoc networks", IEEE 2004. [7] Vasantha.V,Dr.Manimegalai.D. "Mitigating Routing Misbehaviors using Subjective Trust Model in Mobile Ad hoc Networks", IEEE 2007. [8] Xi Zhang, Xiaofei Wang, Anna Liu, Quan Zhang and Chaojing Tang." Reputation-based Scheme for Delay Tolerant Networks", International Conference on Computer Science and Network Technology, IEEE 2011. [9] K. Liu, J. Deng, P. Varshney, and K. Balakrishnan. "An acknowledgment based approach for the detection of routing misbehavior in manets", IEEE transactions on mobile computing, vol. 6, no. 5, May 2007.

[10] Ahmet Burak Can,and Bharat Bhargava. "SORT: A Self-ORganizing Trust Model for Peer-to-Peer Systems", IEEE transactions on dependable and secure computing, vol. 10, no.1, January/February 2013.

Abstract: Data mining is a new and rapidly growing field. It draws ideas and resources from multiple disciplines, including machine learning, statistics, database research, high performance computing and commerce. This explains the dynamic, multifaceted and rapidly evolving nature of the data mining discipline. While there is a broad consensus that the abstract goal of data mining is to discover new and useful information in data bases this is where the consensus ends and the means of achieving this goal are as diver seas the communities contributing. The foundations of all data mining methods, however, are in mathematics. Any moderately sized treatment of data mining techniques necessarily has to be selective and maybe biased towards a particular approach. Data mining techniques are used to find patterns, structure or regularities and singularities in large and growing data sets.

Keywords: ANN, AI, Data mining , Data Models, ,Pattern .

[1] Introduction to Data Mining and Knowledge Discovery, Third Edition ISBN: 1-892095-02-5, Two Crows Corporation,10500 Falls Road, Potomac, MD 20854 (U.S.A.), 1999.

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[10] Davis, J.T., A. Episcopos (2001). "Predicting Direction Shifts on Canadian–U.S. Exchange Rates with Artificial Neural Networks,"

Abstract: The Adhoc networks becomes very popular everyone is using these networks because of which we need to maintain up-to-date positions of their immediate neighbors for making effective forwarding decisions. Periodic broadcasting of beacon packets that contain the geographic location coordinates of the nodes is a popular method used by most geographic routing protocols to maintain neighbor positions. We propose the Adaptive Position Update (APU) strategy for geographic routing, which dynamically adjusts the frequency of position updates based on the mobility dynamics of the nodes and the forwarding patterns in the network. Our theoretical analysis, which is validated by NS2 simulations of a well known geographic routing protocol, Greedy Perimeter Stateless Routing Protocol (GPSR), shows that APU can significantly reduce the update cost and improve the routing performance in terms of packet delivery ratio and average end-to-end delay in comparison with periodic beaconing and other recently proposed updating schemes. And Also comparing the performance and simulations of two on-demand routing protocols DSR and AODV for this APU strategies. KEYWORDS: Ad hoc On Demand Distance Vector (AODV), Distance Source Routing (DSR), Mobile Ad Hoc Network (MANET).

1. Quanjun Chen, Member, IEEE, Salil S. Kanhere, Member, IEEE, and Mahbub Hassan, Senior Member, IEEE. Adaptive Position Update for Geographic Routing in Mobile Ad-hoc Networks. IEEE TRANSACTIONS ON MOBILE COMPUTING, 1536-1233/12, 2012 IEEE.
2. Michele Zorzi, Senior Member, IEEE, and Ramesh R. Rao, Senior Member, IEEE. Geographic Random Forwarding (GeRaF) for Ad Hoc and Sensor Networks: Energy and Latency Performance. IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 2, NO. 4, OCTOBER-DECEMBER 2003.
3. Zygmunt J. Haas, Senior Member, IEEE and Ben Liang, Student Member, IEEE. IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 7, NO. 2, APRIL 1999.
4. Ljubica Blazevic, Member, IEEE, Jean-Yves Le Boudec, Fellow, IEEE, and Silvia Giordano, Member, IEEE. IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 4, NO. 2, MARCH/APRIL 2005.
5. Robert J. Hall, Member, IEEE Computer Society "An Improved Geocast for Mobile Ad Hoc Networks" IEEE TRANSACTIONS ON MOBILCOMPUTING, VOL. 10, NO. 2, FEBRUARY 2011
6. Song Guo, Student Member, IEEE, Oliver Yang, Senior Member, IEEE, and Yantai Shu, Member, IEEE "Improving Source Routing Reliability in Mobile Ad Hoc Networks" IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 16, NO. 4, APRIL 2005
7. Xiaojing Xiang, Member, IEEE, Xin Wang, Member, IEEE, and Zehua Zhou, Member, IEEE. Self-Adaptive On-Demand Geographic Routing for Mobile Ad Hoc Networks. IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 11, NO. 9, SEPTEMBER 2012.

Abstract: In the system and source code development, we develop a source code and documentation is mainly in natural language. The Continuous and frequent development require proper requirements change management Traceability is essential for management of change and analysis of its impact. This research paper presents a technique in the domain of traceability we believe that the application-domain knowledge that programmer's process when writing the code is often captured by the mnemonics for identifiers, the analysis of these mnemonics can help to associate high-level concepts with program concepts and vice-versa. . We propose a method based on information retrieval for traceability links between source code and free text documents. Here we use information retrieval techniques for establishing a links between source code and requirement, documentation and latent semantic indexing, is used to automatically identify traceability links from system code.

Keywords:Traceability, Requirement, Requirement Traceability techniques, Traceability Links, Information Retrieval.

[1] Glean S.Stout "Requirement Traceability" Research paper on Traceability publish in spring cluster 2001.
[2] N. Ali, Y.-G. Gue´he´neuc, and G. Antoniol, "Trust-Based Requirements Traceability," Proc. 19th IEEE Int'l Conf. Program Comprehension, S.E. Sim and F. Ricca, eds., pp. 111-120, June 2011.
[3] G. Antoniol, G. Canfora, G. Casazza, A.D. Lucia, and E. Merlo, "Recovering Traceability Links between Code and Documentation,"IEEE Trans. Software Eng., vol. 28, no. 10, pp. 970-983, Oct. 2002.
[4] Marcus and J.I. Maletic, "Recovering Documentation-to- Source-Code Traceability Links Using Latent Semantic Indexing,"Proc. 25th Int'l Conf. Software Eng., pp. 125-135, 2003
[5] J.H. Hayes, A. Dekhtyar, S.K. Sundaram, and S. Howard,"Helping Analysts Trace Requirements: An Objective Look," O.C.Z. Gotel and C.W. Finkelstein, "An Analysis of the Requirements Traceability Problem," Proc. First Int'l Conf. Proc. 12th IEEE Int'l Requirements Eng. Conf., pp. 249-259, 2004.
[6] J.I. Maletic and M.L. Collard, "TQL: A Query Language to Support Traceability," Proc. ICSE Workshop Traceability in Emerging Forms of Software Eng., pp. 16-20, 2009
[7] R. Wu, H. Zhang, S. Kim, and S. Cheung, "Relink: Recovering Links between Bugs and Changes," Proc. 19th ACM SIGSOFT Symp. and 13th European Conf. Foundations of Software Eng., pp. 15-25, 2011
[8] N. Ali, Y.-G. Gue´he´neuc, and G. Antoniol, "Requirements Traceability for Object Oriented Systems by Partitioning Source Code," Proc. 18th Working Conf. Reverse Eng., pp. 45-54, Oct. 2011.
[9] M. Eaddy, T. Zimmermann, K.D. Sherwood, V. Garg, G.C.Murphy, N. Nagappan, and A.V. Aho, "Do Crosscutting Concerns Cause Defects?" IEEE Trans. Software Eng., vol. 34, no. 4, pp. 497-515, July/Aug. 2008.
[10] De Lucia, M. Di Penta, R. Oliveto, A. Panichella, and S.Panichella, "Improving IR-Based Traceability Recovery Using Smoothing Filters," Proc. 19th IEEE Int'l Conf. Program Comprehension,pp. 21-30, June 2011.

Abstract: Computing Clusters (CC) consisting of several connected machines, could provide a high-performance, multiuser, timesharing environment for executing parallel and sequential jobs. In order to achieve good performance in such an environment, it is necessary to assign processes to machines in a manner that ensures efficient allocation of resources among the jobs. Here we present the algorithm that suited the best for cluster computation by the use of artificial neural network approach and find out the efficient output by using the gridsim. The Grid Modeling and Simulation (GridSim) toolkit provides a comprehensive facility for simulation of application scheduling in different Grid computing environments. The toolkit supports modeling and simulation of heterogeneous Grid resources (both time and space shared), users and application models. It provides primitives for creation of application tasks, mapping of tasks to resources and their management.

Keywords - Needleman-Wunsch, Parallel Algorithm, Parallelization, Gridsim toolkit..

[1] http://www.gridbus.org/gridsim/ [2] Implementation of Parallel Algorithms on Cluster of Workstations. Shrimankar D D, Sathe S R. Department o/Computer Science and Engineering Visvesvaraya National Institute of Technology Nagpur, Maharashtra, lndia, 2012. [3] Decypher Co. Decypher smith waterman solution, 2003 [4] S. F. Altschul et al. Gapped blast and psi-blast: a new generation of protein database search programs. Nucleic Acids Research, 25(17):3389-3402, 1997.
[5] Pairwise Sequence Comparison [online], Lab of Bioinformatics, Institute of Computing Technology (ICT), Chinese Academia of Sciences (CAS). Available: http://www.bioinfo.org.cn/lectures/index-13.html
[6] Rong X, Jan 2003, Pairwise Alignment - CS262 - Lecture 1 Notes [online], Stanford University. Available: http://ai.stanford.edu/~serafim/cs262/Spring2003/Notes/1.pdf

[7] DNA Sequence Comparison [online], The BioWall by Swiss Federal Institute of Technology in Lausanne (EPFL). Available: http://lslwww.epfl.ch/biowall/VersionE/ApplicationsE/SequenceE.html
[8] Krishna N. and Akshay L. and Dr. Rajkumar B., 2002, Alchemi v0.6.1 Documentation [online], University of Melbourne. Available: http://alchemi.net/doc/0_6_1/index.html

[9] Local DNA Sequence Alignment in a Cluster ofWorkstations: Algorithms and Tools, Alba Cristina M. A. Melo, Maria Emilia M. T. Walter, Renata Cristina F. Melo, Marcelo N. P. Santana, Rodolfo B. Batista Department of Computer Science University of Brasilia, Brazil

[10] GridSim: A Toolkit for the Modeling and Simulation of Global Grids, Manzur Murshed, Gippsland School of Computing and IT Monash University, Gippsland Campus Churchill, Vic 3842, Australia Rajkumar Buyya School of Computer Science and Software Eng. Monash University, Caulfield Campus Melbourne, Vic 3145, Australia

Abstract: The development in home automation is moving forward towards the future in creating the ideal smart homes environment. Optionally, home automation system design also been develop for certain situation which for those who need a special attention such as old age person, sick patients, and handicapped person. A brain–computer interface (BCI), often called a mind-machine interface (MMI), or sometimes called a brain–machine interface (BMI), it is a direct communication pathway between the brain and an external device. A brain–computer interface (BCI) is a device that enables severely disabled people to communicate and interact with their environments using their brain waves. Most research investigating BCI in humans has used scalp-recorded electroencephalography or intracranial electrocorticography. The use of brain signals obtained directly from stereotactic depth electrodes to control a BCI has not previously been explored. In this paper, we present a smart home automation system using brain–computer interface. The scope of this research work will include the control and monitoring system for home appliances from Graphical User Interface (GUI) using brain–computer interface that use an input source and being control wirelessly. The research methodology involved is application of knowledge in the field of radio frequency communication, microcontroller and computer programming. Finally, the result will be observed and analyze to obtain better solution in the future.

Keywords -Smart home, Microcontroller, Home automation, Brain Computer Interface

[1] R.A.Ramlee, D.H.Z.Tang, M.M.Ismail ",Smart Home System for Disabled People Via Wireless Bluetooth" . 2012 [2] Jer-Vui Lee, Yea-Dat Chuah and Kenny T.H. Chieng "Smart Elderly Home Monitoring System with an Android Phone" 2013 Vol. 7, No. 3, May, 2013

[3] Safiyya Rusli, Mehrdad Dianati "Mobile Access to Smart Home Network"2012 [4] Malik Sikandar Hayat Khiyal, Aihab Khan, and Erum Shehzadi "SMS Based Wireless Home Appliance Control System (HACS) for Automating Appliances and Security" 2009 IJAIR

[5] Md. Raihaan Kamarudin., Md. Aiman F. Md. Yusof. " Low Cost Smart Home Automation via Microsoft Speech Recognition" 2013 IJENS Vol:13 No:03

[6] Z. Zenn Bien, Jun-Hyeong Do, Jung-Bae KimKwang-Hyun Park and Dimitar Stefanov "User-friendly interaction/interface control of intelligent home for movement-disabled people"

[7] T. Kirankumar, B. Bhavani "A Sustainable Automated System for Elderly People Using Voice Recognition and Touch Screen Technology, IJSR 2013

[8] Shriram K Vasudevan,Sivaraman R,Subashri V,Murali N " Design and Development of an Embedded System for Monitoring the Health Status of a Patient" 2013

[9] Anido Rifon, L.E.; Rivas Costa, C.; Gomez Carballa, M.;Valladares Rodriguez, S.;Fernandez Iglesias. "Improving the quality of life of dependent and disabled people through home automation and tele-assistance

Abstract: Cloud computing provides a framework for supporting end users easily attaching powerful services and applications through Internet. Denial of- Service (DoS) attack or Distributed Denial-of-Service (DDoS) are major security issues in cloud environment. The best solution to protect the cloud from these attacks is use of IDS. IDS have become popular cloud security technology to detect cyber attacks in wide variety of networks. In this paper we will discuss comparative study of various existing integrated intrusion detection systems available to secure cloud. The cloud networks have their own characteristics which are the reason for threats to the security in cloud, cloud intrusion detection system is better solution to achieve a higher level of security maintaining its uniqueness. The cloud intrusion detection system is the most widely used technique where the system consists of IDS connected over the network in combination with Apriori, Bayesian, and Classification algorithms. The paper discusses architectures of cloud Intrusion Detection System and techniques to detect them

Keywords – Cloud Computing, Data Mining, DDoS, IDS.

[1] Anand Kannan and Gerald Q. Maguire, Ayush Sharma and Peter Schoo,"Genetic Algorithm based Feature Selection Algorithm for Effective Intrusion Detection in Cloud Networks" , IEEE, 2012.
[2] Chirag Modi, Dhiran Patel, Avi Patel, Muttukrishanan Rajarajan, "Integrating Signature Apriori based Network Intrusion Detection System (NIDS) in Cloud Computing", ICCCS,2012..
[3] Chirag Modi, Dhiran Patel, Avi Patel, Muttukrishanan Rajarajan, "Bayesian Classifier and Snort based Network Intrusion Detection System in Cloud Computing", IEEE,2012.
[4] Hisham A. Kholidy, Abdelkarim Erradi, Sherif Abdelwahed, Fabrizio Baiardi ," HA-CIDS: A Hierarchical and Autonomous IDS for Cloud Systems."IEEE, 2012.
[5] Chirag Modi, Dhiran Patel, "A Novel hybrid- Network Intrusion Detection System in Cloud Computing", IEEE,2013..
[6] Panagiotis Kalagiakos and Margarita Bora, "Cloud Security Tactics: Virtualization and the VMM", IEEE, 2012.
[7] Praveen Kumar, Bhaskar Naik,"A survey on Cloud Intrusion detection System".IJSWS, 2013.
[8] Chirag Modi, Dhiran Patel, Bhavesh Borisaniya, Hiren Patel."A Survey of Intrusion Detection Techniques in Cloud", JNCA, 2013.
[9] Pradeep Kumar Tiwari and Dr. Bharat Mishra ," Cloud Computing Security Issues, Challenges and Solution " ,IJETAE, Volume 2, Issue 8, August 2012.
[10] Chirag Modi, DhirenPatel, BhaveshBorisaniya, HirenPatel , Avi Patel , MuttukrishnanRajarajan, "A survey of intrusion detection techniques in Cloud ", JNCA, 2013.