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Vehicular ad hoc networks (VANET) have turned into an extremely well-known research application to enhance activity wellbeing. The spread of crisis message is viewed as a critical use of VANET. Unicast and multicast method of correspondence used to impart for general messages. To pass on crisis message messages to every one of the vehicles, broadcasting is the reasonable method of correspondence. At the point when a mischance happens, the messages must be conveyed to all the forthcoming vehicles with the goal that the clog and automobile overload can be kept away from. The message can assist the drivers with enabling smooth and safe driving by giving the drivers in different hazard activity conditions. In this paper proposed a reliable adaptive broadcasting protocol for VANET in which uniform and non-uniform segmentations are used to get less latency.

VANET, Broadcasting, ITS, RSU, RTB, CTB, Flooding, and Segmentation

[1]. Fogue, Manuel, Piedad Garrido, Francisco J. Martinez, Juan-Carlos Cano, Carlos T. Calafate, and Pietro Manzoni. "An adaptive system based on roadmap profiling to enhance warning message dissemination in VANETs." IEEE/ACM Transactions on Networking (TON) 21, no. 3 (2013): 883-895.
[2]. Tseng, Yu-Chee, Sze-Yao Ni, Yuh-Shyan Chen, and Jang-Ping Sheu. "The broadcast storm problem in a mobile ad hoc network." Wireless networks 8, no. 2-3 (2002): 153-167.
[3]. Wisitpongphan, Nawaporn, Ozan K. Tonguz, Jayendra S. Parikh, Priyantha Mudalige, Fan Bai, and Varsha Sadekar. "Broadcast storm mitigation techniques in vehicular ad hoc networks." IEEE Wireless Commun. 14, no. 6 (2007): 84-94.
[4]. Slavik, Michael, and Imad Mahgoub. "Spatial distribution and channel quality adaptive protocol for multihop wireless broadcast routing in VANET." IEEE Transactions on Mobile Computing 12, no. 4 (2013): 722-734.
[5]. Bi, Yuanguo, Lin X. Cai, Xuemin Shen, and Hai Zhao. "A cross layer broadcast protocol for multihop emergency message dissemination in inter-vehicle communication." In Communications (ICC), 2010 IEEE International Conference on, pp. 1-5. IEEE, 2010.
[6]. ur Rehman, Sabih, M. Arif Khan, Tanveer A. Zia, and Lihong Zheng. "Vehicular ad-hoc networks (VANETs)-an overview and challenges." Journal of Wireless Networking and Communications 3, no. 3 (2).
[7]. Shen, Xia, Xiang Cheng, Liuqing Yang, Rongqing Zhang, and Bingli Jiao. "Data dissemination in VANETs: A scheduling approach." IEEE Transactions on Intelligent Transportation Systems 15, no. 5 (2014): 2213-2223.
[8]. Chen, Chen, Xin Wang, Weili Han, and Binyu Zang. "A robust detection of the sybil attack in urban vanets." In Distributed Computing Systems Workshops, 2009. ICDCS Workshops` 09. 29th IEEE International Conference on, pp. 270-276. IEEE, 2009.
[9]. He, Xinxin, Hang Zhang, Tao Luo, and Weisen Shi. "Network capacity analysis for cellular based cognitive radio VANET in urban grid scenario." Journal of Communications and Information Networks 2, no. 2 (2017): 136-146.
[10]. Jesudoss, Auxeeliya, SV Kasmir Raja, and Ashraph Sulaiman. "Stimulating truth-telling and cooperation among nodes in VANETs through payment and punishment scheme." Ad Hoc Networks 24 (2015): 250-263.
[11]. Kesting, Arne, Martin Treiber, and Dirk Helbing. "Connectivity statistics of store-and-forward intervehicle communication." IEEE Transactions on Intelligent Transportation Systems 11, no. 1 (2010): 172-181.
[12]. Saleet, Hanan, Rami Langar, Kshirasagar Naik, Raouf Boutaba, Amiya Nayak, and Nishith Goel. "Intersection-based geographical routing protocol for VANETs: a proposal and analysis." IEEE Transactions on Vehicular Technology 60, no. 9 (2011): 4560-4574.
[13]. Yan, Gongjun, Stephan Olariu, and Michele C. Weigle. "Providing VANET security through active position detection." Computer communications 31, no. 12 (2008): 2883-2897.
[14]. Goli-Bidgoli, Salman, and Naser Movahhedinia. "A trust-based framework for increasing MAC layer reliability in cognitive radio VANETs." Wireless Personal Communications 95, no. 3 (2017): 2873-2893.
[15]. Moridi, Elham, and Hamid Barati. "RMRPTS: a reliable multi-level routing protocol with tabu search in VANET." Telecommunication Systems 65, no. 1 (2017): 127-137.
[16]. De Felice, Mario, Eduardo Cerqueira, Adalberto Melo, Mario Gerla, Francesca Cuomo, and Andrea Baiocchi. "A distributed beaconless routing protocol for real-time video dissemination in multimedia VANETs." Computer Communications 58 (2015): 40-52.
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Himanshu Gupta, Chander Diwakar, "Reliable Adaptive Broadcasting Protocol for VANET," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.577-581, 2018.

Feature extraction is an important part of any image classification scheme. It provides more informative and compact values derived from the original data. In this paper two conventional and widely used techniques known as principal component analysis (PCA) and discrete wavelet transform (DWT) are used for feature extraction. Both techniques are based on entirely different approaches. The results for the two techniques are analyzed and compared. The classification is performed with a benchmark classifier support vector machine. The experiments are carried out on a publically available datasets. The results have shown that DWT has performed better than PCA under the tested scenario.

Classification, Feature extraction, Discrete Wavelet Transform (DWT), Principal Component Analysis (PCA)

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[3] Joliffe, I., “Principal Component Analysis,” Springer-Verlag, New York, 2002.
[4] M. Khalil, H. Ayad, and A. Adib, “Performance evaluation of feature extraction techniques in MR-Brain image classification system,” Procedia Computer Science, vol. 127, pp. 218-225, 2018.
[5] Ş. Öztürk and B. Akdemir, “Application of feature extraction and classification methods for histopathological image using GLCM, LBP, LBGLCM, GLRLM and SFTA,” Procedia Computer Science, vol. 132, pp. 40-46, 2018.
[6] J. Yue, Z. Li, L. Liu, and Z. Fu, “Content-based image retrieval using color and texture fused features,” Mathematical and Computer Modelling, vol. 54, pp. 1121-1127, 2011.
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[14] Chang, C.-C., and Lin, C.-J., “LIBSVM: a library for support vector machines,” ACM Transactions on Intelligent Systems and Technology, vol. 2, no. 3, pp. 27:1-27:27, 2011.

B. Kumar, "Feature Extraction Using Principal Component Analysis and Discrete Wavelet Transform for Image Classification," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.582-586, 2018.

In this paper, two security layers are added on the data using cryptography and steganography algorithms. The data is encrypted using lightweight RECTANGLE algorithm. Next, the data is hiding is done using steganography algorithm. In the steganography scheme, the edges of the cover image are determine using Canny Edge detection technique which can extract inclusive range of edges. Further, worked on theory of color which plane is more suitable for maximum/minimum data hiding. The encrypted data is splitted into 3:2:3 ratio and hide in the edges of the RGB plane simultaneously. The performance analysis is done based on PSNR and embedding capacity. The experimental results show that the Improved technique is secure, consume lesser area, less embedding capacity, and provide high PSNR. Further, data extraction is possible without communicating any extra information with stego image.

Canny Edge Detection, RECTANGLE, PSNR, Multi-Layer Security

[1] Rajendran, Sujarani, and ManivannanDoraipandian. "Chaotic Map Based Random Image Steganography Using LSB Technique." International Journal of Network Security, vol. 19, no. 4, pp. 593-598, 2017.
[2] Amrital Singh and Harpal Singh, “An improved LSB based image steganography technique for RGB images,” IEEE International Conference on Electrical, Computer and Communication Technologies, August 2015.
[3] Panghal, Sandeep, Sachin Kumar, and Naveen Kumar. "Enhanced Security of Data using Image Steganography and AES Encryption Technique." International Journal of Computer Applications Recent Trends in Future Prospective in Engineering & Management Technology 2016.
[4] Patel, Komal, SumitUtareja, and Hitesh Gupta. "Information hiding using least significant bit steganography and blowfish algorithm." International Journal of Computer Applications, vol. 63, no. 13, 2013.
[5] Ramaiya, Manoj, Naveen Hemrajani, and Anil Kishore Saxena. "Secured steganography approach using AES." International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR), vol. 3, pp. 185-192, 2013.
[6] Zhang, Wentao, et al. "RECTANGLE: a bit-slice lightweight block cipher suitable for multiple platforms." Science China Information Sciences vol. 58, no.12, pp. 1-15, 2015.
[7] Li, Li, et al. "A color Images steganography method by multiple embedding strategy based on Sobel operator." 2009 International Conference on Multimedia Information Networking and Security. IEEE, 2009.
[8] Bassil, Youssef. "Image steganography based on a parameterized canny edge detection algorithm." arXiv preprint arXiv:1212.6259, 2012.
[9] Chen, Wen-Jan, Chin-Chen Chang, and T. Hoang Ngan Le. "High payload steganography mechanism using hybrid edge detector." Expert Systems with applications, vol. 37, no. 4, pp. 3292-3301, 2010.
[10] Goodarzi, Mahdi Hassani, ArashZaeim, and Amir Shahab Shahabi. "Convergence between fuzzy logic and steganography for high payload data embedding and more security." Telecommunication Systems, Services, and Applications (TSSA), 2011 6th International Conference on. IEEE, 2011.
[11] Kousik Dasgupta, J.K. Mandal, and Paramartha Dutta, “Hash based Least Significant Bit Technique for Video Steganography,” International Journal of Security, Privacy, and Trust Management, vol. 1, pp. 1-11, April 2012.
[12] Debiprasad Bandyopadhyay, Kousik Dasgupta, J.k. Mandal, Paramartha Dutta, “A Novel Secure Image Steganography Method Based on Chaos Theory in Spatial Domain,” International Journal of Security, Privacy, and Trust Management, vol. 3, pp. 11-22, February 2014.
[13] G. R. Manjula and AjitDanti, “A Novel Hash Based Least Significant Bit (2-3-3) Image Steganography in Spatial Domain,” International Journal of Security, Privacy, and Trust Management, vol. 4, pp. 11-20, Februry2015.
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[15] Muhammad, Khan, et al. "Image steganography for authenticity of visual contents in social networks." Multimedia Tools and Applications, vol. 76, no. 18, pp. 18985-19004, 2017.

A. Kaur, J. Kaur, "Improving Two-Layer Data Security in Image Steganography," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.587-591, 2018.

The mobile ad hoc networks is the decentralized type of network in which mobile nodes can join or leave network when they want. Due to such nature of the network security and quality of service are the major issues. This research work is based on quality of service in the network. The AODV is the efficient routing protocol for the path establishment from source to destination. Due to movement of the mobile nodes, link failure may occur which reduce network performance. In this research work, AODV protocol will be further improved which recover path in case of link failure from source to destination. The proposed protocol is implemented in NS2 and simulation results show high performance of proposed algorithm as compared to existing algorithm.

AODV, Link failure, Ns2

[1] S.Desilva, and R.V.Boppana, “Mitigating Malicious Control Packet Floods In Ad Hoc Networks,” Proceedings of IEEE Wireless Communications and Networking Conference 2005, , vol. -4, pp. 2112- 2117, March 2005.
[2] Radwan S, Abujassar. Mitigation fault of node mobility for the MANET networks by constructing a backup path with loop free: enhance the recovery mechanism for pro-active MANET protocol. Wireless Networks, 2016, 22(1): vol -5 pp. 119 -133.
[3] Manish Bhardwaj. Enhance Life Time of Mobile Ad-hoc Network Using WiTriCity and Backpressure Technique. Procedia Computer Science, 2015, 57: pp. 1342-1350 vol-6 .
[4] Budyal V R, Manvi S S. ANFIS and agent based bandwidth and delay aware any cast routing. Journal of Network and Computer Applications, 2014; 39: pp. 140-151,vol-16.
[5] Dhirendra Kumar Sharma, Amar NathPatra, Chiranjeev Kumar. An improvement in performance of mobile ad hoc networks using modified route maintenance.Computers& Electrical Engineering, 2016, pp. 56: 300-312.
[6] DeepikaVodnala, Phani Kumar S, SrinivasAluvala. An efficient backbone based quick link failure recovery multicast routing protocol. Perspectives in Science, 2016, 8: pp. 135-137.
[7] Pratik Gite, “Link Stability Prediction for Mobile Ad-hoc Network Route Stability”, International Conference on Inventive Systems and Control, 2017.
[8] Kavitha T, Muthaiah R, “ INSTANT ROUTE MIGRATION DURING LINK FAILURE IN MANETS”, International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 8, August 2017
[9] ChandaDhakad, Anand Singh Bisen, “Efficient Route Selection By Using Link Failure Factor In MANET”, International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), 2016
[10] JyotiUpadhyaya, NitinManjhi, “Energy Based Delay with Link Failure Detection in MANET”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 6, Issue 6, June 2016
[11] Mohammad M. Kadhum, “Analytical Modelling Of Communication Overhearing For Route Failure Recovery In Mobile Ad Hoc Networks”, International Journal of Advanced Computational Engineering and Networking, ISSN: 2320-2106, Volume-4, Issue-8, Aug.-2016
[12] DeepikaVodnala, S. Phani Kumar, Srinivas Aluvala, “An Efficient Backbone Based Quick Link Failure Recovery Multicast Routing Protocol”, IEEE, 2016
[13] Lubdha M. Bendale, Roshani. L. Jain, Gayatri D. Patil, "Study of Various Routing Protocols in Mobile Ad-Hoc Networks", International Journal of Scientific Research in Network Security and Communication, Vol.06, Issue.01, pp.1-5, 2018
[14] Amol B.Suryawanshi, Baljit Kaur Saini, "Survey on Various Routing Protocols in Ad-hoc Networks", International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.174-178, 2017

Rajesh Kumar Patel, Saurabh Singh, Kaushal Sinha, "Novel Technique for Link Recovery in Mobile Ad hoc Networks," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.592-595, 2018.

Denial-Of-Service (DOS) is one of the foremost dangerous attacks. It’s a sort of meter attack. This framework is to judge the network’s performance under these attacks with numerous network parameters. IAFV is used to browse the characteristics of the network supported time delay output and packet delivery quantitative relation. The objective of the planned technique is to check the performance metrics underneath completely different attacks. Varied relevant parameters as well as output time delay and packet delivery quantitative relation square measure evaluated. The planned technique deploys exclusive nodes known as DPS nodes employed in the network to watch the behavior of the nodes endlessly. Once the DPS hub distinguishes a hub with relate strange conduct it will report that hub as a wormhole hub to the system by communicating a message. Every single open message will be surrendered by the system from the wormhole hub. A bundle drop assault or dark opening assault might be a style of dissent of-benefit assault inside which a switch that estimated to transfer parcels rather disposes of them. This ordinarily occurs from a switch changing into traded off from assortment of different causes. The planned strategies measures are enforced using NS2 machine and also the results are mentioned.

Botnet, DDoS, Wormhole, IFAV, Attacks

[1] Parmar Amisha ,V.B.Vaghelab,"Detection and Prevention of Wormhole Attack in Wireless Sensor Network using AOMDV protocol", In proceedings of the 2016 International Conference on Communication, Computing and Virtualization, India , pp: 700 – 707,2016.
[2] Arathy K Sa, Sminesh C Na,"Black Hole Attacks in MANET", A Novel Approach for Detection of Single and Collaborative, Global Colloquium in Recent Advancement and Effectual Researches in Engineering, Science and Technology (RAEREST 2016), pp: 264 – 271, 2016.
[3] Tariq Ahamad, "Detection and Defense Against Packet Drop Attack in MANET", International Journal of Advanced Computer Science and Applications, (IJACSA), Vol. 7, No. 2, pp: 328 – 331, 2016.
[4]. M. Rajesh Babu, G. Usha, "A Novel Honeypot Based Detection and Isolation Approach (NHBADI) To Detect and Isolate Black Hole Attacks in MANET", Wireless Personal Communications , pp: 1 – 15, Feb 2016.
[5] Aaditya Jain,"Performance Analysis of DSR Routing Protocol With and Without the Presence of Various Attacks in MANET", International Journal of Engineering Research and General Science Volume 4, Issue 1, pp: 454 – 461, 2016.

M. Lalli, G. Karuthammal, "Performance Based Evaluation of Botnet, Black hole, Wormhole Attack in MANET," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.596-602, 2018.

Sentiment Analysis (SA) is the computational study of opinions, sentiments and emotions expressed in text in order to determine the thoughts of people in the direction of certain objects and facts. The opinions of people have a major influence in our every day decision-making process. In recent days, the people are sharing their opinions in the form of blogs, tweets, face book messages, news groups, comments and reviews. The proposed Dictionary Based Support Vector Machine Feature Selection (DBSVMFS) model extracts sentiment features using Support Vector Machine (SVM) weight method to improve the performance of SA. Different levels of pre-processing methods are applied to reduce the features. A set of sentiment features Adjectives, Adverbs and Verbs are extracted by using WordNet based POS (Part-Of-Speech). Feature selection using SVM weight method is applied to select the most important features. SVM classifier is used for sentiment classification and the experimental results prove the effectiveness of the proposed model by improving sentiment classification accuracy.

Sentiment Analysis, Classification, Support Vector Machine, Feature Selection, Part-Of- Speech

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[5]. Rajwinder Kaur , Prince Verma, “Sentiment Analysis of Movie Reviews: A Study of Machine Learning Algorithms with Various Feature Selection Methods”, International Journal of Computer Sciences and Engineering, Volume-5, Issue-9 E-ISSN: 2347-2693,.pp.113-121, 2017.
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K. Bhuvaneswari, R. Parimala, "Dictionary Based SVM Feature Selection for Sentiment Classification," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.603-607, 2018.

In this paper, a real time data acquisition system based on wireless sensor network is implemented using XBee Digi modules and open source hardware platform Arduino. This wireless sensor nodes are deployed in Fan and Pad Polyhouse. This system consists of two sensor nodes and a base station. These two sensor nodes are deployed at different location in polyhouse. The concept of Arduino UNO is used here to design nodes. Each node is equipped with Atmega 328 micro controller, XBee S2 module and DHT11 sensors. Both sensor nodes sense the temperature and relative humidity and then the collected information are sent to the sink node for storing with specific node ID. Each node also can store its own data using small memory at node level. Arduino Integrated Development Environment (Arduino IDE) is used here to upload programs to Arduino Hardware. The proposed system has been tested for three days and it is observed that results are satisfactory. It indicates that this system can be very useful for greenhouse monitoring and can control various physical parameters in the field as future work.

Arduino, XBee, DHT11 sensor, Wireless Sensor Network, Polyhouse

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[2] A. V. Zade , S. Harwani, P. Bawankule, “A Smart Green House Automation System by Wireless Sensor Networks”, International Journal of Research in Advent Technology, Vol.5, Issue 3, pp.48-50, 2017
[3] K. L. Krishna, J.Madhuri, K. Anuradha, “A ZigBee based Energy Efficient Environmental Monitoring Alerting and Controlling System”, International Conference On Information Communication And Embedded Systems , Chennai, India, 2016, E-ISBN 978-1-5090-2552-7
[4] J. C. Patil, A. B. Diggikar, “Zigbee based Agricultural Greenhouse Monitoring Using Wireless Sensor Network”, International Journal of Innovations & Advancement in Computer Science, Vol. 4, Issue 6, pp. 95-99, 2015
[5] Ruchika, Ruchi, Taneja, “Smart Agriculture Monitoring Through IOT (Internet of Things)”, International Journal for Scientific Research & Development, Vol. 3, Issue 05, pp. 817-819, 2015, ISSN (online): 2321-0613
[6] M. P. Aher, N. Kyatanavar, M. A. Sayyad, “Advanced WSN Based Green House Monitoring and Controlling with GSM Terminal“, International Journal of Advanced Research and Innovative Ideas in Education, Vol. 1 Issue 4, 2015, ISSN(O)-2395-4396
[7] D. O. Shirsath, P. Kamble, R. Mane, A. Kolap, R. S. More, “IOT Based Smart Greenhouse Automation Using Arduino”, International Journal of Innovative Research in Compter Science & Technology, Vol.5, Issue 2, pp. 234-238, 2017, ISSN 2347-5552
[8] R. Piyare , S. Lee, “Performance Analysis of XBee ZB Module Based Wireless Sensor Networks”, International Journal of Scientific & Engineering Research, Vol. 4, Issue 4, pp. 1615-1621, 2013, ISSN 2229-551
[9] K. Mor, S. Kumar, “Evaluation of QoS Metrics in Ad-Hoc Wireless Sensor Networks using Zigbee”, International Journal of Computer Sciences and Engineering, Vol. 6, Issue 3, pp. 90-94, 2018, ISSN: 2347-2693
[10] A. Saravanan A. Subhashini, “ZIGBEE Controlled Industrial Robot for Controlling the Fire in a Sensitive Way“, International Journal of Computer Sciences and Engineering, Vol. 6, Issue 7, pp. 1082-1084, 2018, ISSN: 2347-2693
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B. A. Parbat, R. K. Dhuware, "Real Time Data Acquisition System for WSN Using Arduino for Polyhouse," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.608-612, 2018.

Salient object segmentation is useful for supervised learning process. The challenging issues of this work is small flying object Segmentation in different lighting condition in the sky images using Morphological Closing and reconstruction techniques. In the proposed method, detection of regional maximal in grey level image with specified connectivity and removing of borders, filled holes. Finally, identifies flying object and gives fast processing and effective results. Experimental results on dataset demonstrates the proposed techniques performs well against existing methods.

Birds, Grayscale reconstruction, Morphological operation

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Sandeep, M. Suresha, "Segmentation of Salient Flying Objects in Complex Sky Scene using Reconstruction Morphological Operations," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.613-619, 2018.

Fingerprint matching is most widely used mean of person identification or verification since last two decades. The issues related to efficient matching under transformation requires lots of attention of the research community. This paper presents rotational invariant directional features computed directly from gray values of fingerprint images and referred as Local Directional Pattern (LDP). Single hidden Layer Feed Forward Neural Network (SLFNN) is proposed to be used for classification. Network is trained using four different training algorithms to determine the suitability of these algorithms. The results show that these features are very discriminatory under rotation and also the efficiency of SLFNN for matching. It is also evident that Resilient Propagation (RP) algorithm is much faster and gives best performance as compared to other training algorithms.

Fingerprint Matching, Image based matching, Region of Interest, Ressiliant Propagation, Rotation Invariant

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Ravinder Kumar, "Rotation Invariant Fingerprint Matching based on Gray values using SLFNN," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.620-628, 2018.

Mobile Ad hoc Networks (MANETs) are a class of infrastructure less networks that are created through a number of autonomous wireless and mobile nodes. The inherent characteristics of such networks create the support of multimedia applications very challenging. In previous researches, the capacity and delay in MANETs was analyzed via considering the correlation of node mobility. Explored the characteristics of correlated mobility and figured out the essential relationships among the scheduling parameters and the network performance. However, the reliability and link stability for transmitting the packets is needed in MANET to achieve Quality of Service (QoS) support in terms of available bandwidth, high throughput and stable jitter. Hence, QoS aware metric for routing is incorporated with the Correlated Mobility (CM). In this method, Link Stability Factor(LSF) is estimated by considering received signal strength, the appropriate contention count and hop count. On the basis of the estimated LSF, stable link is determined. After that, the node with the highest LSF is elected as a reliable forwarding node. So, the proposed method improves QoS performance. The simulation results proved that our proposed methods are providing better results.

QoS aware routing, Link Stability Factor, Contention Count, Signal Strength, Capacity-Delay Tradeoff

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N. Sivapriya, T.N. Ravi, R.Mohandas, "Enhanced Optimal CDT with Appropriate Contention Count based on CNM in MANET," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.629-636, 2018.