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In Wireless Sensor Networks (WSNs), classical clustering protocols assume that all nodes are equipped with the same amount of energy. In addition, the extension to multi-level of SEEC is presented. The performance of the proposed protocol is examined and compared by existing homogeneous and heterogeneous protocols. Simulation results show that the proposed protocol provides a longer/more stability period, more energy efficiency and higher average throughput than the existing protocols

Wireless sensor network, Cluster Head, Lifetime network, stability

[1] Zheng, Jun, and Abbas Jamalipour. “Wireless sensor networks: a networking perspective” John Wiley & Sons Publications, 2009.
[2] Tripathi, Anand Mohan, and P. Velmurugan. "An Improved Stable Election Based Routing Protocol with Threshold Sensitiveness for Wireless Sensor Network." International Journal of Computer Science and Mobile Computing, Vol.3 Issue.5, May- 2014, pg. 280-287.
[3] Chen, Jong-Shin, Zeng-Wei Hong, Neng-Chung Wang, and San-Heui Jhuang. "Efficient cluster head selection methods for wireless sensor networks."Journal of Networks Journal, Vol 5, No 8 (2010), 964-970, Aug 2010.
[4] Ramesh, K., and Dr K. Somasundaram. "A comparative study of clusterhead selection algorithms in wireless sensor networks”, International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.4, November 2011.
[5] Al Islam, ABM Alim, et al. "Stable sensor network (ssn): a dynamic clustering technique for maximizing stability in wireless sensor networks."Wireless sensor network 2.07 (2010): 538.
[6] Kaur, Gaganpreet, Dheerendra Singh, and Sukhpreet Kaur. "Pollination based optimization for feature reduction at feature level fusion of speech & signature biometrics." Reliability, Infocom Technologies and Optimization (ICRITO)(Trends and Future Directions), 2014 3rd International Conference on. IEEE, 2014.
[7] Katiyar, Vivek, Narottam Chand, and Surender Soni. "Clustering algorithms for heterogeneous wireless sensor network: A survey." International Journal of Applied Engineering Research , 2010, pp. 273-287.
[8] Sharawi, Marwa, et al. "Flower pollination optimization algorithm for wireless sensor network lifetime global optimization." International Journal of Soft Computing and Engineering Vol- 04, Issue-03, pp. 54-59, 2014
[9] Xiangning, Fan, and Song Yulin. "Improvement on LEACH protocol of wireless sensor network." Sensor Technologies and Applications, SensorComm 2007. International Conference on. IEEE, 2007.
[10] Farouk, Fifi, Ramy Rizk, and Fayez W. Zaki. "Multi-level stable and energy-efficient clustering protocol in heterogeneous wireless sensor networks" Wireless Sensor Systems, IET Vol- 04, Issue-04, pp. 159-169, 2014.
[11] Mishra, Neeraj Kumar, Vikram Jain, and Sandeep Sahu. "Survey on recent clustering algorithms in wireless sensor networks." International Journal of Scientific and Research Publications, Vol- 03, Issue-04 ,2013.
[12] Vidya, K. S., and M. Arun Anoop. "Lifetime Enhanced Cluster Based Routing in Wireless Sensor Networks." International Journal of Engineering Science Invention, Vol- 02, Issue-07, pp. 69-72, 2013.
[13] Javaid, N., Qureshi, T., Khan, A., Iqbal, A., Akhtar, E., Ishfaq, M.: ‘EDDEEC: enhanced developed distributed energy-efficient clustering for heterogeneous wireless sensor networks’, Proc. Comput. Sci. , 19, pp. 914–919, 2013.
[14] Ali, M., Dey, T., Biswas, R.: ‘ALEACH: advanced LEACH routing protocol for wireless microsensor networks’. Proc. Fifth Int. Conf. on Electrical and Computer Engineering (ICECE), pp. 909–914, .

Atul Rana, Manju Bala and Varsha , "Review Paper on MSEEC: Energy Efficient Clustering Protocol in HWSN," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.71-75, 2016.

Refactoring is one of the most important activity in software development. It is done to improve the design of the software, to make the software easier and better to understand and to help us in writing programs faster. After the software is refactored, it is important to note the behaviour of that software. In this paper, we propose refactorings that we can apply of Aspect Oriented Programs. In the last paper some of the refactorings were introduced. Here we are introducing the results of the refactorings introduced and the systems considered for Aspect Oriented Programming using Aspect. This research paper is in continuation with the previous one. Initially we introduce the refactorings identified, then the Systems that are used for applying these refactoring are mentioned. Then the tool is discussed and finally the analysis of the system is presented.

Refactoring, Aspect Oriented Programming, AOP, Pointcut, Joinpoint, Refactoring Advice Aspect Oriented Programming, Aspect Oriented Concerns, AspectJ, Concerns, Aspect, Aspect Mining

[1] A. Rani and H. Kaur, "Refactoring Methods and Tools", International Journal of Advanced Research in Computer Science and Software Engineering, vol. 2, no. 12, pp. 256- 260, 2012.
[2] Puneet Jai Kaur, Sarita Rani, “Impact of Aspect Oriented Programming on Software Maintainability - A
Descriptive Study, University Institute of Engineering and Technology, Panjab University, Sector 25, Chandigarh, International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS), IJETCAS 14-340; 2014
[3] Pradeep Kumar Singh, Om Prakash Sangwan, Amar Pal Singh Amrendra Pratap, “An Assessment of Software Testability using Fuzzy Logic Technique for Aspect-Oriented Software”, I.J. Information Technology and Computer Science, 2015, 03
[4] Freddy Munoz,Benoit Baudry, Romain Delamare, Yves Le Traon “Inquiring the Usageof Aspect-Oriented Programming: An Empirical Study”
[5] Tom Mens, Tom Tourw´e “A Survey of Software Refactoring”, IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. XX, NO. Y, MONTH 2004
[6] Eduardo Figueiredo,Alessandro Garcia, Carlos Lucena, AJATO: an AspectJ Assessment Tool
[7] Muhammad Sarmad Alia, Muhammad Ali Babar,, Lianping Chen, Klaas-Jan Stol, Information and Software Technology, 52 , 871–887(2010)
[8] Terry Hon, A Simple, Modern AspectJ Compiler
[9] Sven Apel, and Don Batory,” How AspectJ is Used:”
An Analysis of Eleven AspectJ Programs”, Technical Report, Number MIP-0801, Department of Informatics and Mathematics,University of Passau, Germany,April 2008
[10] Khine Zar Ne Winn,”Quantifying and Validation of Changeability and Extensibility for Aspect-Oriented Software”, International Conference on Advances in Engineering and Technology (ICAET'2014) March 29-30, 2014 Singapore
[11] Piyush Chandi,” A Survey : Code Optimization using Refactoring”, International Journal on Computer Science and Engineering (IJCSE), Vol. 5 No. 05, May 2013

Geeta Bagade, Shashank Joshi, "Analysis of Aspect Oriented Systems: Refactorings using AspectJ," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.76-80, 2016.

The term Big data is very popular recently in all the domains. Every where and every body talking about big data numerously. The goal of this paper is to describe what is big data and how it can be used in various applications. The rising number of applications serving millions of users and dealing with terabytes of data need to a faster processing paradigms. Recently, there is growing enthusiasm for the notion of big data analysis. Big data analysis becomes a very important aspect for growth productivity, reliability and quality of services. Processing of big data using a powerful machine is not efficient solution. So, companies focused on using Hadoop software for big data analysis. This is because Hadoop designed to support parallel and distributed data processing. Hadoop provides a distributed file processing system that stores and processes a large scale of data. The author tries to give the introduction about Hadoop and Map Reduce architecture. The main goal of this paper is applications of big data in various domains and how to build decision support system using big data. Big data have applications in many fields such as Business, Technology, Health Care, Smart cities etc. These applications will allow people to have better services, better customer experiences, and also to prevent and detect illness much easier than before.

Big Data, Cloud Computing, Data Mining, Business, Hadoop and Map Reduce

[1] Anchalia, P.P.; Koundinya, A.K.; Srinath, N.K., "MapReduce Design of K-Means Clustering Algorithm," International Conference onInformation Science and Applications (ICISA), pp.1,5, 24-26 June 2013, doi:10.1109/ICISA.2013.6579448.
[2] “Big Data, Big Impact: New Possibilities for International Development.” World Economic Forum (2012): 1-9. Vital Wave Consulting. Jan. 2012
[3] Big data: The next frontier for innovation, competition, and productivity. James Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, and Angela Hung Byers. McKinsey Global Institute. May 2011.
[4] C.Lam, “Hadoop in Action”, Manning Publications Co., USA,ISBN:9781935182191, Dec. 2010.
[5] King, Gary. “Ensuring the Data-Rich Future of Social Science.” Science Mag 331 (2011) 719-721. 11 Feb, 2011 Web.
[6] Keim, Daniel, Huamin Qu, and Kwan-Liu Ma. "Big-Data Visualization." Computer Graphics and Applications, IEEE 33.4 (2013): 20-21.
[7] Lakew, Ewnetu Bayuh. Managing Resource Usage and Allocations in Multi-Cluster Clouds. 2013, http://www8.cs.umu.se/~ewnetu/papers/lic.pdf
[8] Monga, Inder, Eric Pouyoul, and Chin Guok. Software-Defined Networking for Big-Data Science-Architectural Models from Campus to the WAN. High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion:. IEEE, 2012.
[9] Russom, “ Big Data Analytics”, TDWI Research, 2011.
[10] Richa Gupta, Sunny Gupta, Anuradha Singhal, (2014), “Big Data:Overview”, IJCTT, 9 (5). [11]S.Perera, T.Gunarathne, “Hadoop MapReduce Cookbook”, Packt Publishing, ISBN:1849517282,Jan. 2013.
[11] Turn Big Data into Big Value, A Practical Strategy, Intel White Paper,2013.
[12] T. H. Davenport and J. Dyche, "Big Data in Big Companies," May 2013, 2013.
[13] Wei Fan and Albert Bifet “ Mining Big Data:Current Status and Forecast to the Future”,Vol 14,Issue 2,2013
[14] Wu, Xindong, et al. "Data mining with big data." Knowledge and Data Engineering, IEEE Transactions on 26.1 (2014): 97-107.

M. Kumarasamy and G. N. K. Suresh Babu, "Applications of Big Data in various Domains," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.81-85, 2016.

These days, the quantity of vehicles has expanded exponentially, yet the bedrock limits of roads and transportation frameworks have not created in an identical approach to proficiently adapt to the quantity of vehicles going on them. There has been huge exploration on Traffic Management Systems utilizing sensor networks to evade congestion, guarantee urgency for emergency vehicles and lower the Average Waiting Time of automobiles at junctions. In order to solve the problem we have developed a distributed embedded electronic system that can considerably solve the problem of ambulances and other emergency vehicles getting jammed at traffic signal lights. The fundamental idea driving this plan is to give a smooth stream to the emergency vehicles like ambulances to achieve the healing facilities in time and along these lines minimizing the delay owing to traffic congestion.

Smart; Traffic; Ambulance; Zig Bee; Micro Controller; Congestion; Delay; Emergency

[1] Yang, Zhaosheng, and Deyong Guan. "Study on the scheme of traffic signal timing for priority vehicles based on navigation system." Vehicle Electronics Conference, 2001. IVEC 2001. Proceedings of the IEEE International. IEEE, 2001.
[2] Sundar, Rajeshwari, Santhoshs Hebbar, and Varaprasad Golla. "Implementing Intelligent Traffic Control System for Congestion Control, Ambulance Clearance, and Stolen Vehicle Detection." Sensors Journal, IEEE 15.2 (2015): 1109-1113.
[3] Kale, Sarika B., and Gajanan P. Dhok. "Design of intelligent ambulance and traffic control." Int. J. Comput. Electron. Res 2.2 (2013).
[4] Bharadwaj, Richa, et al. "Efficient dynamic traffic control system using wireless sensor networks." Recent Trends in Information Technology (ICRTIT), 2013 International Conference on. IEEE, 2013.
[5] Sathya, G., et al. "Automatic Rescue System for Ambulance and Authoritative Vehicles." International Journal of Engineering Research and Technology. Vol. 2. No. 4 (April-2013). ESRSA Publications, 2013.
[6] Mathew, Joseph, and P. M. Xavier. "A survey on using wireless signals for road traffic detection." IJRET 3.1 (2014): 97-102.
[7] Nellore, Kapileswar, and Gerhard P. Hancke. "A survey on urban traffic management system using wireless sensor networks." Sensors 16.2 (2016): 157.
[8] Chowdhury, Tandrima, Smriti Singh, and S. Maflin Shaby. "A Rescue System of an advanced ambulance using prioritized traffic switching."Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on. IEEE, 2015.
[9] Athavan, K., et al. "Automatic Ambulance Rescue System." Advanced Computing & Communication Technologies (ACCT), 2012 Second International Conference on. IEEE, 2012.
[10] Pavan Talluri, Anil Kumar M. "Intelligent Traffic System Which Respond To Emergencies." International Journal of Engineering Trends and Technology (IJETT) 4: 1132-1133.
[11] XBeeDatasheet https://www.sparkfun.com/datasheets/Wireless/Zigbee/XBee-Datasheet.pdf
[12] https://www.me.umn.edu/courses/me2011/arduino/
[13] https://docs.digi.com/display/XCTU/XCTU+Overview
[14] https://www.arduino.cc/
[15] punam rajput and prasad kulkarni, "a survey on wireless malevolent access point detection methods for wlan", international journal of computer sciences and engineering, volume-04, issue-04, page no (48-50), apr -2016, e-issn: 2347-2693
[16] Kerav Shah, Gourav Inani, Darshan Rupareliya, Rupesh Bagwe and Bharathi H N, "RFID Based Toll Automation System", International Journal of Computer Sciences and Engineering, Volume-04, Issue-04, Page No (51-54), Apr -2016, E-ISSN: 2347-2693

Saqib ul sabha, Shashikant Dewangan and Syed Tahir Ahamad, "A Smart Distributed Wireless Traffic Management System for Emergency Vehicles Using Zig Bee," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.86-89, 2016.

An appropriate clustering algorithm for grouping sensor nodes can increase the energy efficiency of WSN’s. Here, This paper is proposing a new regional energy aware clustering method using isolated nodes for WSNs, called Regional Energy Aware Clustering with the Isolated Nodes ( REAC-IN ). In REAC-IN, CH's are selected based on weight. To prolong network lifetime, the regional average energy and there distance between these sensors and the sink are used to determine that whether the isolated node sends its data to CH node in the previous round or to the sink. The simulation results of the current study revealed that the REAC-IN out performs other clustering algorithms.

REAC-IN, DEEC, EM Algorithm

[1] Jenq-Shiou Leu, Member, IEEE, Tung-Hung Chiang, Min-Chieh Yu, and Kuan-Wu Su, “Energy Efficient Clustering Scheme for the Prolonging of the Lifetime of Wireless Sensor Network With Isolated Nodes”. Vol:-19 No-2 Feb-2015.
[2] Giorgos Fagas, Luca Gammaitoni, Douglas Paul and Gabriel Abadal Berini, ISBN 978-953-51-1218-1, Published: February 12, 2014
[3] Mrs. Manisha S.Bhende/InternationalJournal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue 3,May-Jun2012, pp.1680-1684
[4] Jin Wang, Zhongqi Zhang , Feng Xia, Weiwei Yuan 3 and Sungyoung Lee An Energy Efficient Stable Election-Based Routing Algorithm for Wireless Sensor Networks 2013 . ISSN 14303
[5] Dr. Firas Ali Al-Juboori1, Eng. Sura F. Ismail2 IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 2, No 1, March 2013
[6] Soojin Lee, Yunho Lee and Sang-Guun Yoo,. A Specification Based Intrusion Detection Mechanism for the LEACH Protocol. Information Technology Journal, 11: 40-48 2012.
[7] Amrinder kaur, Sunil saini ,'Simulation of the Low Energy Adaptive Clustering Hierarchy Protocol for the Wireless Sensor Network' july 2013.
[8] Abbasi , Mohamed Younis and Ameer Ahmed, . "A survey on clustering algorithms for wireless sensor networks. " Computer communications 30.14 (2007): 2826-2841.
[9] Qureshi, T. N., et al. "BEENISH: Balanced Energy Efficient Network Integrated Super Heterogeneous Protocol for the Wireless Sensor Networks." Procedia Computer Science 19 (2013): 920-925.
[10] Vidya K S , Arun Anoop et al . 'Lifetime Enhanced Cluster Based on Routing in the Wireless Sensor Networks Computer Science', International Journal of Engineering Science Invention(IJESIRD) , ISSN (Online): 2319 – 6734, ISSN (Print): 2319 – 6726 www.ijesi.org Volume 2 Issue 7 June. 2013 PP.69-72.
[11] Multi-level stable and energy-efficient clustering protocol in heterogeneous wireless sensor networks Fifi Farouk1, Rawya Rizk1, Fayez W. Zaki2.-2014
[12] Energy Efficient Clustering Scheme for Prolonging the Lifetime of the Wireless Sensor Network With Isolated Nodes. Jenq-Shiou Leu, Member, IEEE, Tung-Hung Chiang, Min-Chieh Yu, and Kuan-Wu Su Feb-2015
[13] W-LEACH Based Dynamic Adaptive Data Aggregation Algorithm for Wireless Sensor Networks Hanady M. Abdulsalam and Bader A. Ali.
[14] Guard Beacon: An Energy-Efficient Beacon Strategy for Time Synchronization in the Wireless Sensor Networks Yongrui Chen, Fei Qin, and Weidong Yi June-2014
[15] An Efficient and Robust Data Compression Algorithm in the Wireless Sensor Networks Yao Liang, Senior Member, IEEE, and Yimei Li Mar-2014
[16] Maximum Lifetime Scheduling for Target Coverage and the Data Collection in the Wireless Sensor Networks Zaixin Lu, Wei Wayne Li , Senior Member , IEEE, and Miao Pan , Member, IEEE Mar-2015
[17] Toward Energy-Efficient Trust System Through Watchdog Optimization for WSNs Peng Zhou, Siwei Jiang , Athirai Irissappane , Jie Zhang , Jianying Zhou , and Joseph Chee Ming Teo Mar-2015.
[18] Pattern-Reconfigurable Antennas and the Smart Wake-Up Circuits to DecreasePower Consumption in WSN Nodes Luca Catarinucci , Sergio Guglielmi , Riccardo Colella and Luciano Tarricone Dec-2014
[19] Channel and Energy Modeling for the Self-Contained Wireless Sensor Networks in Oil Reservoirs Hongzhi Guo, Student Member, IEEE, and Zhi Sun, Member, IEEE Apr-2014
[20] Han, L.: ‘LEACH-HPR: An energy efficient routing algorithm for Heterogeneous WSN’. Proc. IEEE Int. Conf. on Intelligent Computing and Intelligent Systems (ICIS), October 2010,
[21] Tuah, N., Ismail, M., Jumari , K.: “ Energy- efficient improvement for heterogeneous wireless sensor networks “ , Inf. Technol. J., 2012, 11, (12), pp. 1687–1695

Jagdeep Singh, Manju Bala and Varsha , "REAC-IN Regional Energy Aware Clustering Protocol in Wireless Sensor Network," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.90-94, 2016.

Solid-State Drive (SSD) is also known as Solid-State Disk it contains no moving components. Attraction for SSD is due to its high throughput and scalability. It distinguishes from traditional magnetic disks like hard disk drives which contains movable head and spinning disk. SSDs are electronic circuit built on NAND-Flash/NOR-Flash and PCM. Solid-State Drive uses non-volatile memory for storage and retrieval of data or information in the form of sectors and/or pages and shows better performance than hard disks. Maximum IO performance of the used memory technology can be achieved using a properly written software device driver, which can effectively utilizes underlying hardware resources and extracts the maximum performance from the storage device. This paper is a survey on key literature on IO performance of SSD and block driver. It deals with the effort that defines what characteristics an effective solid state drive should have. The paper also discusses trends and categories in research and questions that are further open for investigation.

Dynamic Block Driver, NVMe, Solid state drive, block layer, latency

[1] Eleni Bougioukou, Athina Ntalla, Aspa Palli, Maria Varsamou and Theodore Antonakopoulos, “Prototyping and Performance Evaluation of a Dynamically Adaptable Block Device Driver for PCIe-based SSDs”, IEEE 2014
[2] Matias Bjørling, Jens Axboe, David Nellans, Philippe Bonnet, “Linux Block IO: Introducing Multi-queue SSD Access on Multi-core Systems”, SYSTOR ACM, 2013
[3] Amro Awad, Brett Kettering, and Yan Solihin,” Non-Volatile Memory Host Controller Interface Performance Analysis in High-Performance I/O Systems”, IEEE, 2015
[4] Sivashankar, Dr. S. Ramasamy, “Design and Implementation of Non-Volatile Memory Express”, International Conference on Recent Trends in Information Technology, IEEE, 2014
[5] Mojtaba Tarihi, Hossein Asadi, Alireza Haghdoost, Mohammad Arjomand, and Hamid Sarbazi-Azad, “A Hybrid Non-Volatile Cache Design for Solid-State Drives Using Comprehensive I/O Characterization”, IEEE, 2015.
[6] Hiroko Midorikawa, Hideyuki Tan, Toshio Endo, “An Evaluation of the Potential of Flash SSD as Large and Slow Memory for Stencil Computations”, IEEE, 2014
[7] Shuichi Oikawa, Satoshi Miki, “Future Non-Volatile Memory Storage Architecture and File System Interface”, First International Symposium on Computing and Networking, 2013
[8] Myoungsoo Jung, “Exploring Design Challenges in Getting Solid State Drives Closer to CPU”, IEEE, 2013
[9] M. Wu and W. Zwaenepoel, “envy: a non-volatile,
main memory storage system,” in Proceedings of
the 6th International Conference on Architectural
Support for Programming Languages and Operating
Systems, ser. ASPLOS VI. New York, NY,
USA: ACM, 1994, pp. 86–97. [Online]. Available:
http://doi.acm.org/10.1145/195473.195506
[10] Nguyen, A. ; Satish, N. ; Chhugani, J. ; Changkyu Kim; Dubey, P., “3.5-D Blocking Optimization for Stencil Computations on Modern CPUs and GPUs”, High Performance Computing, Networking, Storage and Analysis, 2010

Raman Kumar Kharch, Vijay D. Katkar and Kedar Kulkarni, "Study on Block Device Driver and NVMe their Implementation Impacts on Performance," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.95-98, 2016.

MANET (Mobile Ad-Hoc Network) is self-directed and infrastructure less network. MANETs contains mobile nodes that are free to move in the network. Nodes can be the devices like mobile phones, PDA, MP3 players and personal computers which are participating in network. MANET has the dynamic topology due to the node movement. Transmissions of the packet between the mobile devices are overcome by the Routing Protocol. Selfish node is a major problem in MANET. Selfish nodes are nodes that do not participate in forwarding process. This paper presents types of MANET protocols along with security issues that MANET faces. The major consideration of this paper is about the behavior and detection methods of selfish node in MANET.

MANET, Routing Protocol, Security Principals

[1] Dipali D. Punwatkar and Kapil N. Hande, "A Review of Malicious Node Detection in Mobile Ad-hoc Networks", International Journal of Computer Sciences and Engineering, Volume-02, Issue-02, Page No (65-69), Feb -2014
[2] Umesh Kumar Singh, Shivlal Mewada, Lokesh Laddhani and Kamal Bunkar, “An Overview & Study of Security Issues in Mobile Ado Networks”, International Journal of Computer Science and Information Security (IJCSIS) USA, Vol-9(4), pp (106-111), April 2011
[3] ayank Kumar and Tanya Singh, "A Survey on Security Issue in Mobile AD-HOC Network and Solutions", International Journal of Computer Sciences and Engineering, Volume-02, Issue-03, Page No (71-75), Mar -2014
[4] M.Madhumathi, S. Sindhuja, “ A Survey on Collaborative contact-based Selfish node detection in Mobile ad hoc Network”, International Journal of Advanced Research in Computer Engineering & Technology, Volume 4 Issue 10, October 2015
[5] Nikunjkumar Varnagar, prof. Amit Lathigara, “Review Paper of Selfish Node Detection in MANET”, International Journal of Advance Research in Computer Science and Management Studies, Volume 3, Issue 2, February 2015
[6] G.Satyavathy and P. Anitha, "A Collaborative Contact-Based Watchdog CoCoWa for Detecting Selfish Nodes with Trust Model", International Journal of Computer Sciences and Engineering, Volume-03, Issue-09, Page No (120-123), Sep -2015

Jagmeet kaur and Prabhjit singh, "Detecting Selfish node in MANET- A Review," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.99-104, 2016.

In vehicular ad-hoc networks for authentication Public Key Infrastructure (PKI) was used as Vehicular Signature application. Using PKI scheme integrity of message and identity of senders can be verified. In this scheme task of Road Side Unit (RSU) is to verify received messages one by one, and if this is the case then it is difficult to guess the identity of a vehicle by RSU i.e. from which vehicle particular message is being sent. So Proxy Based Batch Authentication Scheme is being proposed in order to reduce computational overhead of RSU in distributed computing system. In PBAS, each proxy vehicle authenticates multiple messages simultaneously using verification function at the same time, so that RSU can independently verify the outputs given by each proxy vehicles within its range.

Proxy vehicle; Proxy based authentication; Privacy preservation; Vehicular ad-hoc network

[1] Chim T.W, Yiu, S.M, Hui Li, “VSPN: VANET-Based Secure and Privacy Preserving Navigation”, IEEE Transactions on Computers, vol.63, no.2, (2014):pp.510-524
[2] Xiaoyan Zhu, Shunrong Jiang, Liangmin Wang and Hui Li, “Efficient Privacy-Preserving Authentication for Vehicular Ad Hoc Networks”, IEEE Transactions on Vehicular Technology, vol.63, no.2,(2014): pp.907-919
[3] Richard Gilles Engoulou, Martine Bellaïche, Samuel Pierre, Alejandro Quintero “VANET security surveys”, in Computer Communications, vol.44, no.4,(2014): pp 1–13
[4] Lamba S; Sharma M., “An Efficient Elliptic Curve Digital Signature Algorithm (ECDSA)”, International Conference on Machine Intelligence and Research Advancement (ICMIRA), (2013): pp.179-183
[5] Wasef, A.; Xuemin Shen, “EMAP: Expedite Message Authentication Protocol for Vehicular Ad Hoc Networks”, IEEE Transactions on Mobile Computing, vol.12, no.1,(2013): pp.78-89
[6] Xiaodong Lin; Xu Li, “Achieving Efficient Cooperative Message Authentication in Vehicular Ad Hoc Networks”, IEEE Transactions on Vehicular Technology, vol.62, no.7, (2013):pp.3339-3348
[7] Shi-Jinn Horng; Shiang-Feng Tzeng; Yi Pan; Pingzhi Fan; Xian Wang; Tianrui Li; Khan, M.K., “ b-SPECS+: Batch Verification for Secure Pseudonymous Authentication in VANET ”, IEEE Transactions on Information Forensics and Security, vol.8, no.11,(2013): pp.1860-1875
[8] IEEE Standard for “Wireless Access in Vehicular Environments Security Services for Applications and Management Messages”, on IEEE Std 1609.2-2013 (Revision of IEEE Std 1609.2-2006) , (2013):pp.1-289
[9] Rongxing Lu; Xiaodong Lin; Zhiguo Shi; Shen, X.S., “A Lightweight Conditional Privacy-Preservation Protocol for Vehicular Traffic-Monitoring Systems” IEEE in Intelligent Systems , vol.28, no.3(2013): pp.62-65
[10] Dietzel, S.; Petit, J.; Heijenk, G.; Kargl, F., “ Graph-Based Metrics for Insider Attack Detection in VANET Multihop Data Dissemination Protocols”, IEEE Transactions on Vehicular Technology, vol.62, no.4,(2013): pp.1505-1518
[11] Xiaojun Li; Liangmin Wang, “A Rapid Certification Protocol from Bilinear Pairings for Vehicular Ad Hoc Networks” in Trust, Security and Privacy in Computing and Communications (TrustCom), 2012 IEEE 11th International Conference on , (2012):pp.890-895
[12] Rongxing Lu; Xiaodong Li; Luan, T.H.; Xiaohui Liang; Xuemin Shen, “ Pseudonym Changing at Social Spots: An Effective Strategy for Location Privacy in VANETs” , IEEE Transactions on Vehicular Technology , vol.61, no.1,( 2012): pp.86-96
[13] Kyung-Ah Shim, “ CPAS : An Efficient Conditional Privacy-Preserving Authentication Scheme for Vehicular Sensor Networks”, IEEE Transactions on Vehicular Technology, vol.61, no.4, (2012):pp.1874-1883
[14] Jiun-Long Huang; Lo-Yao Yeh; Hung-Yu Chien, “ ABAKA: An Anonymous Batch Authenticated and Key Agreement Scheme for Value-Added Services in Vehicular Ad Hoc Networks”, in Vehicular Technology, IEEE Transactions on , vol.60, no.1, pp.248-262, Jan. 2011
[15] Lingbo Wei; Jianwei Liu; Tingge Zhu, “ On a Group Signature Scheme Supporting Batch Verification for Vehicular Networks”, in Multimedia Information Networking and Security (MINES), 2011 Third International Conference on ,( 2011):pp.436-440
[16] T. W. Chim, S. M. Yiu, C. K. Hui, and O. K. Li, “SPECS: Secure and privacy enhancing communications schemes for VANETs”, Ad Hoc Networks, vol.9, Issue.2,(2011): pp.189-203
[17] Isaac, J.T.; Zeadally, S.; Camara, J.S., “Security attacks and solutions for vehicular ad hoc networks”, IEEE Transaction in Communications, vol.4, no.7,(2010):pp.894-903
[18] Yipin Sun; Rongxing Lu; Xiaodong Lin; Xuemin Shen; Jinshu Su, “An Efficient Pseudonymous Authentication Scheme With Strong Privacy Preservation for Vehicular Communications”, IEEE Transactions on Vehicular Technology, vol.59, no.7, (2010):pp.3589-3603
[19] Ghassan Samara, Wafaa A. H. Al-Salihy, R. Sures., ”Security analysis of vehicular ad hoc networks (VANET)”, in IEEE Conf. Network Applications Protocols and Services (NETAPPS), (2010):pp.55-60
[20] Wasef, A.; Rongxing Lu; Xiaodong Lin; Xuemin Shen, “Complementing public key infrastructure to secure vehicular ad hoc networks [Security and Privacy in Emerging Wireless Networks]” , IEEE Transaction on Wireless Communications, vol.17, no.5,( 2010): pp.22-28
[21] Wasef, A.; Yixin Jiang; Xuemin Shen, ”DCS: An Efficient Distributed-Certificate-Service Scheme for Vehicular Networks” IEEE Transactions on Vehicular Technology, vol.59, no.2,(2010): pp.533-549
[22] C. Zhang; R. Lu; X. Lin; P. Ho; X. Shen., “An efficient identity-based batch verification scheme for vehicular sensor networks”, IEEE INFOCOM in Proc.,(2008):pp. 246-250

Godavari H. kudlikar, Sunita S. Barve, "PBAS: Batch Authentication Scheme for Vehicular Ad Hoc Network using Proxy Vehicle," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.105-110, 2016.

This paper comprehensively surveys the research work in the field of Stock Market Prediction Models that employ Multilayer Perceptron Feed-Forward Artificial Neural Networks. It examines the proposed and/or implemented predictive models by outlining the network configurations of the experimental setups as well as the methodologies utilized to train and improve their prediction accuracies.

Artificial Neural Networks; Multilayer Perceptron; Back Propogation

[1] Suraiya Jabin, “Stock Market Prediction Using Feed-Forward Artificial Neural Network”, Int. Journal of Computer Applications, Vol.99, Issue-9, 2014, pp.4-8.
[2] Mayankkumar B. Patel, and Sunil R. Yalamalle, “Stock Price Prediction Using Artificial Neural Network”, Int. Journal of Innovative Research in Science, Engineering and Technology, Vol.3, Issue-6, 2014, pp.13755-13762.
[3] H. R. Pawar, P. G. Gaikwad, U. G. Bombale, D. D. Jagtap, and S. Durugkar, “Intelligence Stock Forecasting Using Neural Network”, Int. Journal of Computer Sciences and Engineering, Vol.2, Issue-4, 2014, pp.103-106.
[4] A. Victor Devadoss, and T. Antony Alphonnse Ligori, “Stock Prediction Using Artificial Neural Networks”, Int. Journal of Data Mining Techniques and Applications, Vol.2, 2013, pp.283-291.
[5] Selvan Simon, and Arun Raoot, “Accuracy Driven Artificial Neural Networks In Stock Market Prediction”, Int. Journal on Soft Computing, Vol.3, Issue-2, 2012, pp.35-44.
[6] Mahdi Pakdaman Naeini, Hamidreza Taremian and Homa Baradaran Hashemi, “Stock Market Value Prediction Using Neural Networks”, CISIM, IEEE, 2010, pp.132-136.
[7] M. Thenmozhi, “Forecasting Stock Index Returns Using Neural Networks”, Delhi Business Review, Vol.7, Issue-2, 2006, pp.59-69.
[8] Yochanan Shachmurove, and Dorota Witkowska, “Utilizing Artificial Neural Network Model to Predict Stock Markets”, CARESS Working Paper #00-11, 2000, pp.1-25.
[9] G. Zhang, B. E. Patuwo, and M. Y. Hu, “Forecasting with Artificial Neural Networks: The State of the Art”, Int. Journal of Forecasting, Issue-14, 1998, pp.35-62.
[10] H. Mizuno, M. Kosaka, H. Yajima, and N. Komoda, “Application of Neural Network to Technical Analysis of Stock Market Prediction,” Studies in Informatics and Control, Vol.7, Issue-3, 1998, pp.111-120.
[11] Y. Yoon, and G. Swales, “Predicting Stock Price Performance,” Proceeding of the 24th Hawaii International Conference on System Sciences, Issue-4, 1997, pp.156-162.
[12] M. Kaastra, and M. Boyd, “Designing a Neural Network for Forecasting Financial and Economic Time Series”, Neurocomputing, Issue-10, 1996, pp.215-236.
[13] Chung-Ming Kuan, and Tung Liu, “Forecasting Exchange Rates Using Feedforward and Recurrent Neural Networks”, Journal of Applied Econometrics, Vol.10, Issue-4, 1995, pp.347-364.
[14] D. Witkowska, “Neural Networks as a Forecasting Instrument for the Polish Stock Exchange,” Int. Advances in Economic Research, Vol.1, Issue-3, 1995, pp.232-241.
[15] Darmadi Komo, Chein-I Chang, and Hanseok KO, “Neural Network Technology for Stock Market Index Prediction”, Int. Symposium on Speech, Image Processing and Neural Networks, 1994, pp.13-16.
[16] C. M. Kuan, and H. White, “Artificial Neural Networks: An Econometric Perspective,” Econometric Views, Vol.13, Issue-1, 1994, pp.1-91.
[17] R. G. Hoptroff, “The Principles and Practice of Time Series Forecasting and Business Modelling Using Neural Nets”, Neural Computing and Applications, Issue-1, 1993, pp.59-66.
[18] L. Kryzanowski, M. Galler, and W. David, “Using Artificial Neural Networks to Pick Stocks”, Financial Analysts Journal, Vol.49, Issue-4, 1993, pp.21-27.
[19] G. Grudnitzky, and L. Osburn, “Forecasting S&P and Gold Futures Prices: An Application of Neural Networks”, Journal of Futures Markets, Vol.13, Issue-6, 1993, pp.631-643.
[20] R. R. Trippi, and D. DeSieno, “Trading Equity Index Futures with a Neural Network,” Journal of Portfolio Management, Vol.19, Issue-1, 1992, pp.27-33.
[21] T. Kimoto, K. Asakawa, M. Yoda, and M. Takeoka, "Stock Market Prediction System with Modular Neural Network", Proceedings of the Int. Joint Conference on Neural Networks, 1990, pp.1-6.

A. Rao, S. Hule, H. Shaikh, E. Nirwan and P. M. Daflapurkar, "Survey: Stock Predictive Models Using Multilayer Perceptron," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.111-113, 2016.

The web crawler is the central component of a search engine which works like an indexer, finds out hyperlinks, computes keyword density of each web page and stores the visited links for the future use. Today's world is mobile world! Aodhan Cullen, CEO, StatCounter stated that “Mobile has grown rapidly from 17.1% to 28.5% in past 12 months. Mobile usage has already overtaken desktop in several countries including India, South Africa and Saudi Arabia[1]”. Due to increasing use of mobile, there is a need to develop a search crawler which will mainly focus on the mobile devices and provide them quality results in less time. The proposed system, “Mobile Optimized Search Crawler” is a crawler that mainly focuses on providing quick and relevant results to the mobile users. It gives more priority to the websites which are optimized for mobile devices than the websites which are not. It uses more than 50 factors to determine the relevancy of page, giving more weightage to the mobile-optimized factor so that mobile users get websites which are user-friendly and rich in knowledge.

Search engine; Search Crawler; Keyword density; Mobile-optimized website

[1] “StatCounter”, http://gs.statcounter.com/press/mobile-internet-usage-soars-by-67-perc , 19 Dec, 2015.
[2] “Search Engine”,
http://websearch.about.com/od/enginesanddirectories/a/searchengine.htm , 15 July, 2015.
[3] Feng Zhao, Jingyu Zhou, Chang Nie, Heqing Huang and Hai Jin, “SmartCrawler : A two-stage crawler for efficiently harvesting deep-web interfaces”, Services Computing, IEEE Transactions, Volume-PP, Issue-99, DOI-10.11.09, 2015.
[4] Mehdi Bahrami, Mukesh Singhal and Zixuan Zhuang, “A Cloud-based Web Crawler Architecture”, Intelligence in Next Generation Networks (ICIN), 2015 18th International Conference, Page No (216-233), 17-19 Feb 2015.
[5] Pavalam S.M, S.V. KumarRaja, M. Jawhar and Felix K. Akorli, “Web crawler in mobile systems”, International Journal of Machine Learning and Computing, Volume-02, Issue-04, Page No (531-534), August 2012.
[6] Vladislav Shkapenyuk and Torsten Suel, “Design and implementation of a high-performance distributed Web crawler”, Data Engineering, 2002. IEEE Proceedings. 18th International Conference, Page No (357-368), 2002.
[7] Hardik P. Trivedi, Gaurav N. Daxini, Jignesh A. Oswal, Vinay D. Gor and Swati Mali, “An Approach to Design Personalized Focused Crawler”, International Journal of Computer Sciences and Engineering, Volume-02, Issue-03, Page No (144-147), March 2014.
[8] “Google Ranking Factors: The Complete List”,
http://www.backlinko.com/google-ranking-factors ,
2 Feb, 2016.
[9] “Apache Hadoop”, http://www.hadoop.apache.org ,
10 March, 2016.
[10] “Apache HBase”, http://www.hbase.apache.org ,
10 March, 2016.
[11] “Apache Spark”, http://www.spark.apache.org ,
14 March, 2016.
[12] “Java Servlets”,
http://docs.oracle.com/javaee/5/tutorial/doc/bnafd.html ,
14 March, 2016.
[13] “Java Server Pages”,
http://docs.oracle.com/javaee/5/tutorial/doc/bnagx.html ,
15 March, 2016.

Kukreja Kajal, Gavali Nishigandha and Khedlekar Gandhali, "Implementation of Mobile Optimized Search Crawler," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.114-117, 2016.