Volume-04 , Special Issue-07 , Dec - 2016 Go Back

Energy efficiency is the important work for wireless sensor network. Every node has limited energy .So to design Routing protocol in WSN ones should take care of less energy consumption. Already many routing algorithm has developed which result is less energy consumption. In this paper we have discussed all well-known PEGASIS routing algorithms based on grid which always focus on low energy consumption. Each algorithm is described in detail with their pros and cons along with their design issue .

Wireless Sensor Network, PEGASIS, PDCH, EEPB, IEEPB,MH-PEGASIS, PEGASIS-ANT

[1]. S. Lindsey,. and C.S. Raghavendra, C.S. “PEGASIS: Power-efficient gathering in sensor information systems”. In IEEE proceeding on aerospace, 3, 1125-1130.
[2]. Meenu, and Vandana, “Modified PEGASIS in WSN to increase Network Lifetime,” in International Journal of Computer Applications (0975-8887), Volume 52- No. 19, August 2012.
[3]. J. Rana, S Vhatkar, and M. Atique, “Comparative Study of PEGASIS and PDCH Protocols in Wireless Sensor Network,” in International Journal of Computer Applications (0975-8887).
[4]. Singhal, Vishakha, and Shrutika Suri. "Comparative study of hierarchical routing protocols in wireless sensor networks." International Journal of Computer Science and Engineering 2.5 (2014): 142-147.
[5]. Nathiya, R., and S. G. Santhi. "Energy Efficient Routing with Mobile Collector in Wireless Sensor Networks (WSNs)." International Journal of Computer Sciences and Engineering 2 (2014): 36-43.
[6]. S. Vhatkar, J Rana, and M. Atique, “Performance Evaluation and QOS Analysis of EEPB and PDCH Routing Protocols in Wireless Sensor Networks,” IOSR Journal of Computer Enginering(IOSR-JCE) e-ISSN: 2278-0661,p-ISSN:2278-8727, Volume 17, Issue 5, ver. IV(Sep.-Oct. 2015), PP 101-109.
[7]. Feng Sen, Qi Bing and Tang Liangrui, “An Improved Energy-Efficient PEGASIS-Based Protocol in Wireless Sensor Networks,” in Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), vol. 4, pp. 2230-2233, Shanghai, 2011.
[8]. Z. Aliouat and M. Aliouat, “Efficient Management of Energy Budget for PEGASIS Routing Protocol,” in 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), pp. 516-521, Sousse, March 2012.
[9]. Atul Rana, Manju Bala and Varsha , "Review Paper on MSEEC: Energy Efficient Clustering Protocol in HWSN", International Journal of Computer Sciences and Engineering, Volume-04, Issue-05, Page No (71-75), May -2016
[10]. P. Singh, S. Singh, “A Review: Power efficient Gathering in Sensor Information system(PEGASIS) protocol for WSN,” in International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056,p-ISSN:2395-0072,Volume 2, Issue 03,june-2015.
[11]. Sharma, Shamneesh, Dinesh Kumar, and Keshav Kishore. "Wireless Sensor Networks-A Review on Topologies and Node Architecture." International Journal of Computer Sciences and Engineering 1.2 (2013): 19-25.
[12]. Sujata Agrawal, K.D. Kulat and M. B.Daigavane, "Evaluation of Routing Algorithm for Ad-hoc and Wireless Sensor Network Protocol", International Journal of Computer Sciences and Engineering, Volume-01, Issue-02, Page No (11-18), Oct -2013
[13]. Obulapu Hiteshreddy, Pardeep Singh and Siddharth Chahuan, "A Review on Cluster Based Data Aggregation Protocols in Wireless Sensor Network", International Journal of Computer Sciences and Engineering, Volume-03, Issue-08, Page No (37-45), Aug -2015,
[14]. Sanchita Gupta and Pooja Saini, "Modified Pairwise Key Pre-distribution Scheme with Deployment Knowledge in Wireless Sensor Network", International Journal of Scientific Research in Network Security and Communication, Volume-01, Issue-02, Page No (21-23), May -Jun 2013
[15]. Amr M. Kishk, Nagy W. Messiha, Nawal A. El-Fishawy, Abdelrahman A. Alkafs, Ahmed H. Madian, "Proposed Jamming Removal Technique for Wireless Sensor Network", International Journal of Scientific Research in Network Security and Communication, Volume-03, Issue-02, Page No (1-14), Mar -Apr 2015

Kangka Chakravarty and Utpal Barman, "An Energy Balanced Algorithm of PEGASIS Protocol in WSN", International Journal of Computer Sciences and Engineering, Vol.04, Issue.07, pp.53-57, 2016.

With the availability of huge number of products, it became quite difficult for a customer to judge the quality about the product. Publicly available opinions are very important for decision making process. With the increasing number of reviews and comments for a particular product it became difficult to get an optimized opinion for that product. In this paper, we will study various reviews and the quality of the reviews from a huge number of positive and negative opinions on the product. All the reviews will be analysed on the basis of sentiment and will give a final opinion on the product. It will help every buyer to take a quick decision and gain a precise opinion for the products.

Optimized opinion; Quality; Sentiment

[1] Zheng-Jun Zha, Member, IEEE, Jianxing Yu, Jinhui Tang, Member, IEEE, Meng Wang, Member, IEEE, and Tat-SengChua,Product Aspect Ranking and Its Applications.
[2] GeorgLackermair, Daniel Kailer, KenanKanmaz, Importance of Online Product Reviews from a Consumer’s Perspective.
[3] Minqing Hu and Bing Liu Department of Computer Science University of Illinois at Chicago, Mining and Summarizing Customer Reviews.
[4] DrS Vijayarani, Ms J Ilamathi,Ms. Nithya,Preprocessing technique for text mining-An overview.
[5] Theresa Wilson, JanyceWiebe, Paul Hoffmann, Recognizing Contextual Polarity in Phrase-level Sentiment analysis.
[6] WalaaMedhat, Ahmed Hassan, HodaKorashy, Sentiment analysis algorithms and applications: A survey.
[7] Lina L. Dhande, Dr. Prof. Girish K Patnaik,Analysing sentiments of movie review data using naïve bayes neural classifier.
[8] ChetanKaushik and Atul Mishra Computer Engg. Department, YMCA University of Science & Technology, Faridabad, A Scalable, Lexicon Based Technique For Sentiment Analysis.
[9] Ms. Gaurangi Patil1, Ms. Varsha Galande2, Mr. VedantKekan3, Ms. Kalpana Dange4, Sentiment Analysis Using Support Vector Machine.
[10] Haiyang Sui,Christopher Khoo,Syin Chan, Sentiment Classification of Product Review using SVM and Decision Tree Induction.
[11] Vijay Murari T 1, Sunil 2, Suchitra V3, Asst. Professor, Dept. of Computer Science, NMAMIT, Nitte, India, Survey on Product Recommendation Using Customer Reviews Based on Opinion Mining.
[12] S. Chandra Kala and C. SindhuDepartment of Computer Science and Engineering, Velammal Engineering College, India, Opinion Mining and Sentiment Classification: A Survey.
[13] Anascollomb, CrinaCostea, DamienJoyeux, OmarHasan, LionelBrunie,Study and Comparision of Sentiment Analysis methods for Reputation Evaluation.
[14] MaiteTaboada,Julian Brooke, Milan Tofiloski, Kimberly Voll, Manfred Stede, Lexicon-Based Methods for Sentiment Analysis.

PinkySaikiaDutta*1, AvishekSaha, AmarendraSharma, AbhishekSarmah, JugalKishorTalukdar, "Customer Opinion from various E-commerce sitesusing Data Mining techniques: A Survey", International Journal of Computer Sciences and Engineering, Vol.04, Issue.07, pp.58-61, 2016.

This paper presents a survey of man-in-the-middle attacks in communication networks and methods of protection against them. Man in the middle attack allows the attacker to gain unauthorized entry into the connection between two devices and listen to the network traffic. This paper focuses on the areas where man-in-the-middle attack can occur and the different methods with which we can defense against the attack.

Man-in-the-middle attack, attacker, victim, ARP Cache Poisoning, DNS spoofing, Session Hijacking

[1] Kapil M Jain & Manoj V Jain, International Journal of Science Technology and Engineering, Man in the Middle Attack survey, March 2016.
[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, Vol-9, No.4, pp (106-111), April 2011.ISSN: 1947-5500,
[3] Pushpendra Kumar Pateriya, Analysis on Man in the Middle attack on SSL, International Journal Of Computer Application, 23 May 2012.
[4] Animesh Dubey, Ravindra Gupta, Gajendra Singh, Survey and Analysis of Client Side Detection of Content Sniffing Attack, March,2013
[5] Margaret Rouse, Hijacking, 2012.
[6] Shivlal Mewada, Pradeep Sharma, S.S Gautam, “Exploration of Efficient Symmetric AES Algorithm”, 2016 Symposium on Colossal Data Analysis and Networking (CDAN), pp(1-5), Mar, 2016. Doi: 10.1109/CDAN.2016.7570921,
[7] S. Kak, Quantum information and entropy, 2007.
[8] G. N. Nayak and S. G. Samaddar, different flavours of man-in-the-middle-attack, consequences and feasible solutions, 2010.
[9] B. Issac, Secure ARP and secure DHCP protocols to Mitigate Security Attacks. International Journal of network security 8, 2009.
[10] Tanmay Patange, How to defend yourself against MITM or Man-in-the-Middle attack, October 2013.
[11] http://destroyadware.com/articles/security/3-effective-ways-defend-man-middle-attack-mitm/, 3 effective ways to defend against a Man-in-the-Middle Attack (MITM)
[12] Rachna Jain, Sushila Madan and Bindu Garg, "Analyzing Various Existing Security Techniques to Secure Data Access in Cloud Environment", International Journal of Computer Sciences and Engineering, Volume-03, Issue-01, Page No (130-135), Jan -2015,
[13] Trend Micro, What is the Man-In-The-Middle attack and how can I protect myself from them? , 28 November 2012.
[14] Michael Gregg, How new technologies are reshaping MITM attacks, 23 July 2013.
[15] Dinu P S, Deepa S Kumar, Dr. M Abdul Rehman, Preventing SQL injection Attacks Using Cryptography Methods, 5 May 2015.

Manjula Kalita, Sukanya Dutta and Ayesha Yesmin, "A Survey on Man in the Middle Attack: Classification, Defense Mechanisms and Challenges", International Journal of Computer Sciences and Engineering, Vol.04, Issue.07, pp.62-66, 2016.

This paper represents a method to recognize the human walking individuals by their gait using Principal Component Analysis (PCA). Human Gait is used as principal identifying feature to generate the unique gait sequence for each individual. Gait is an important biometric feature which delineates the way of locomotion. The generation of binary silhouette frames of walking subjects is the initial step in this method. Some distinguishable gait features, viz., centroid, aspect ratio, orientation, height and width are extracted from the silhouette frames to acquire feature vectors. Then, the PCA is employed over the generated feature vectors to condense the information contained and produces the principal components which are used as gait sequences or signatures to represent each walking individuals. Finally the generated gait sequences are recognized by using a minimum distance classifier based on eluclidean distance. A classification rate of 93% is achieved from the proposed human recognition method which is tested using CASIA dataset.

PCA, Gait, Silhouette, Feature Vector Human Recognition, CASIA dataset

[1]. Dong Ming, Cong Zhang, Yanru Bai, Baikun Wan, Yong Hu and KDK Luk, “Gait Recognition Based on Multiple Views Fusion of Wavelet Descriptor and Human Skeleton Model”, IEEE International Conference on Virtual Environments, Human-Computer Interfaces and Measurements Systems, pp. 246-249, 2009.
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[6]. Sa-Mun KIM, Dae-Jong Lee, HO-Hyun Lee, Myung-Geun Chun, “Person Recognition Using Gait and Face features on thermal images”, The Transactions of Korean Institute of Electrical Engineering, vol. 65(2), pp. 130-135, 2016.
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[20]. Chiraz BenAbdelkader, Ross Cutler and Larry Davis,
“View-Invariant Estimation of Height and Stride for Gait
Recognition”, Biometric Authentication, European Conference on Computer Vision: International. Workshop, vol.4, pp. 155-167, 2002.
[21]. Jinyan Chen, Jiansheng Liu, ”Average Gait Differential Image Based Human Recognition”, The Scientific World Journal, vol. 2014, pp. 1-8, 2014.
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Recognition for Human Identification”, Computer Science
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[23]. Hu Ng, Hau-Lee Tong, Wooi-Haw Tan and Timothy TzenVun Yap, ”Human Identification Based on Extracted Gait Features”, International Journal on New Computer Architectures and Their Applications, vol. 1, pp. 358-370, 2011.
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Surveillance Video Using Gait Biometric cues”, International Conference on Fuzzy Systems and Knowledge Discovery, pp. 1877-1881, 2012.
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Pranjit Das and Sarat Saharia, "Human Gait Recognition Based on Principal Component Analysis", International Journal of Computer Sciences and Engineering, Vol.04, Issue.07, pp.67-70, 2016.

Much of technology advances in the field of temperature measurement have led to a huge variety of sensors and measuring instruments now being available for making accurate measurements at relatively low costs. This paper makes an attempt to do a study on improving the accuracy of temperature measurement using most popular temperature measurement sensors and implementing in a microcontroller based measurement system, that will help to choose the correct method and sensor for specific application of temperature measurement.

RTD(Resistance Temperature Detector), ADC(Analog to Digital Converter), CJC(cold junction compensation), I2C(Inter Integrated Circuit), PWM(Pulse Width Modulation), PRT(Platinum Resistance Thermometer)

[1] Performing High Performance Temperature Measurements, http://www.ni.com, September 2015
[2] Garry Prentice, Temperature Measurement Accuracy Guidelines, Flow Control Magazine, http://www.flowcontrolnetwork.com, July 2015
[3] K.A Akpado, C.O Ezeagwu, A. Ejiofor, A.O Nwokeke, Design, Modeling and Simulation of a Microcontroller Based Temperature Control in a Ventilation System, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering Vol. 2, Issue 7, July 2013.
[4] TMP275, Datasheet TMP275: 0.5°C Digital out temperature sensor, SBOS363D-June2006-Revised August 2007.
[5] S.Jayasri, D.Karthika, "Microcontroller Based Traffic and Road Condition Monitoring Alert System Using Internet of Things", International Journal of Computer Sciences and Engineering, Volume-04, Issue-04, Page No (272-279), Apr -2016
[6] D. Ibrahim, Microcontroller Based Temperature Monitoring and Control, Elsevier Science & Technology Books, 2002, pp. 2–61
[7] S.Rajesh Kumar, S.Rameshkumar, Industrial Temperature Monitoring and Control System Through Ethernet LAN, International Journal Of Engineering And Computer Science ISSN:2319-7242, Volume 2 Issue 6 June, 2013 Page No. 1988-1991

Jayanta Kumar Nath and Himadri Baruah, "Study on Accurate Temperature Measurement Using Different Sensors and Microcontroller Based System", International Journal of Computer Sciences and Engineering, Vol.04, Issue.07, pp.71-73, 2016.

In this data-rich world, people are running out of information. This can be a matter of risk for the person who needs immediate remedies regarding their poor health. To unfold this hurdle, the concept of data mining is the best suited. Here, the traditional approaches have been replaced by smart technologies. The main purpose of data mining application in healthcare system is to develop an automated tool for identifying and disseminating relevant healthcare information. In this paper, we present a methodology for Prediction of diseases based on user input symptoms. It predicts probable diseases by mining data sets and provides suggested doctors and remedial solutions for Effective Treatment. It will also guide the users by giving tips to live a healthy life. We have discussed in detail on the existing Data mining techniques with data mining algorithms and its application tools which are more valuable for healthcare services.

Data Mining, E-health care, Prediction, Effective remedies

[1] Han, J, Kamber, M.: “Data Mining Concepts and Techniques”, Morgan Kaufmann Publishers, 2006
[2] K. Srinivas, B. Kavitha Rani and Dr. A. Govardhan, ―Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks International Journal on Computer Science and Engineering (2010).
[3] ShwetaKharya, ―Using Data Mining Techniques for Diagnosis and Prognosis of Cancer Disease‖, International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.2, April 2012.
[4] Arvind Sharma and P.C. Gupta ―Predicting the Number of Blood Donors through their Age and Blood Group by using Data Mining Tool| International Journal of Communication and Computer Technologies Volume 01 – No.6, Issue: 02 September 2012.
[5] M. Durairaj, V. Ranjani- Data Mining Applications in Healthcare Sector: A Study International Journal of Scientific& Technology Research Volume 2, Issue 10, October 2013
[6] Gitanjali J., C.Ranichandra, M. Pounambal, ―APROIRI algorithm based medical data mining for frequent disease identification, ‖ Univ. VIT, Vellore, 4, April 4, 2014, Vol 2.
[7] S. Nagaparameshwara Chary, B.Ram, "Analysis of Classification Technique Algorithms in Data mining- A Review", International Journal of Computer Sciences and Engineering, Volume-04, Issue-06, Page No (180-185), Jun -2016,
[8] Priyanka Vijay Pawar, MeghaSakharamWalunj, PallaviChitte, Estimation based on Data Mining Approach for Health Analysis,International Journal on Recent and Innovation Trends in Computing and Communication
[9]. David Page and Mark Craven,― Biological Applications of Multi Relational Data Mining‖.

Pinky Saikia Dutta, Sunayana Dutta, Tridisha Das, Sweety Buragohain, Susmita Sarma, "A Survey on Smart Health Care Using Data Mining", International Journal of Computer Sciences and Engineering, Vol.04, Issue.07, pp.74-79, 2016.

Wood is an anisotropic biological material with a multitude use. The paper describes variation of strain of wood samples due to the change in relative humidity (RH). The strain developed due to change in RH is measured by strain gauge method. In this paper, the strain is measured in longitudinal (L) and tangential (T) direction. For that purpose strain gauge is attached in the prescribed direction and the strain developed due to change in RH is recorded by data acquisition system. The developed data acquisition recorded ambient temperature, RH with temperature compensated and strain of the wood samples in different L and T direction. Strain anisotropies of two wood samples of different thickness are tested at different relative humidity conditions and the results are reported in the paper. Experimental results show that the strain developed in the wood sample is anisotropic.

MPLAB-IDE, RISC Processor, Measurement System

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Kunjalata Kalita and Nipan Das, "Determination of Variation of Strain Anisotropy of Wood due to change in Relative Humidity", International Journal of Computer Sciences and Engineering, Vol.04, Issue.07, pp.80-84, 2016.

In recent years there has been development of systems to make human life easier. One of the emerging fields is wireless sensor networking. There have been many development in the last few years to make smart farming worldwide popular and several research works has been done by researchers to find the most efficient routing protocol as the sensor nodes used in smart farming have limited energy and thus its a challenge to utilize that limited energy efficiently for a long period of time. To address these issues we propose a new routing algorithm called Single Stage Chain Routing Protocol.

CCM, PEGASIS, SPCRP and WSN

[1] R.Nathiya and S.G.Santhi, "Energy Efficient Routing with Mobile Collector in Wireless Sensor Networks (WSNs)", International Journal of Computer Sciences and Engineering, Volume-02, Issue-02, Page No (36-43), Feb -2014
[2] Lindsey, Stephanie, and Cauligi S. Raghavendra. "PEGASIS: Power-efficient gathering in sensor information systems." Aerospace conference proceedings, 2002. IEEE. Vol. 3. IEEE, 2002.
[3] Hiteshreddy, Obulapu, Pardeep Singh, and Siddharth Chahuan. "A Review on Cluster Based Data Aggregation Protocols in Wireless Sensor Network." (2015).
[4] Jigish Rana, Sangeeta Vhatkar, Mohommad Atique, “Comparative Study of PEGASIS and PDCH Protocols in Wireless Sensor Network”, International Journal of Computer Applications (0975 – 8887) International Conference and Workshop on Emerging Trends in Technology (ICWET 2015).
[5] S L Mewada and Umesh Kumar Singh, “Measurement Based Performance of Reactive and Proactive Routing Protocols in WMN”, Int. Journal of advanced research in Computer Science and Software Engineering, Vol. 1, No. 1, pp(1-4), Dec.-2011
[6] Vishakha Singhal and Shrutika Suri, "Comparative Study of Hierarchical Routing Protocols in Wireless Sensor Networks", International Journal of Computer Sciences and Engineering, Volume-02, Issue-05, Page No (142-147), May -2014.
[7] Sujata Agrawal, K.D. Kulat and M. B.Daigavane, "Evaluation of Routing Algorithm for Ad-hoc and Wireless Sensor Network Protocol", International Journal of Computer Sciences and Engineering, Volume-01, Issue-02, Page No (11-18), Oct -2013

Utpal Barman, Pranoy Bhowmick, Kunal Gunjan Talukdar, Mrinal Goswami, Amit Mundra, "Single Stage Chain Routing Protocol (SCRP) For Wireless Sensor Networks", International Journal of Computer Sciences and Engineering, Vol.04, Issue.07, pp.85-88, 2016.

This paper presents a study on feature extraction techniques for image processing which is an important research subject in the field of computer vision. Representation and Feature extraction is an important step for multimedia processing. It manages how to concentrate perfect features that can mirror the intrinsic content of the picture. Feature extraction strategy extracts the distinct components from the picture like edges, corners and so on which can be used to match the similarity for estimation of relative transformation between the images. So in this paper we focus our study on the different methods used for image feature extraction, texture feature extraction and shape feature extraction.

Color feature, Color Histogram, Feature extraction, ,Haralik texture feature, Hu-Moment Shape Features, Tamura texture feature

[1] Dong ping Tian,” A Review on Image Feature Extraction and Representation Techniques”, International Journal of Multimedia and Ubiquitous Engineering Vol. 8, No. 4, July, 2013
[2] R.Venkata Ramana Chary1, Dr.D.Rajya Lakshmi2 and Dr. K.V.N Sunitha“Feature Extraction Methods For Color Image Similarity”, Advanced Computing: An International Journal (ACIJ), Vol.3, No.2, March 2012
[3] N.Krishnaraj, "Feature Extraction Techniques in Keystroke Dynamics for Securing Personal Devices", International Journal of Computer Sciences and Engineering, Volume-03, Issue-03, Page No (98-101), Mar -2015
[4] Neelima Bagri1 and Punit Kumar Johari2, “A Comparative Study on Feature Extraction using Texture and Shape for Content Based Image Retrieval”, International Journal of Advanced Science and Technology Vol.80 (2015), pp.41-52.
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[10] Priyarani S. Jagatap and Rupali R. Jagtap, "Electrocardiogram (ECG) Signal Analysis and Feature Extraction: A Survey", International Journal of Computer Sciences and Engineering, Volume-02, Issue-05, Page No (1-3), May -2014
[11] S. Mori Tamura and T. Yamawaki, “Textural Features Corresponding to Visual Perception”, IEEE Transactions on Systems, Man and Cybernetics, vol. smc-8, no. 6, (1978) June, pp. 460-473.

Shrabani Medhi, Chandraleena Ahmed and Rabi Gayan, "A Study on Feature Extraction Techniques in Image Processing", International Journal of Computer Sciences and Engineering, Vol.04, Issue.07, pp.89-93, 2016.

This paper proposes an advanced remote monitoring system for the farmers to monitor the various environmental parameters required for the growth of crops. This method is cost effective and an improvisation of old techniques. It mainly measures the ambient temperature and relative humidity, using temperature and humidity sensor DHT11 and sends the data wirelessly to remote location using Zigbee based Wireless sensor network and is also displayed on LCD. An application is developed in LABVIEW to acquire the data corresponding to temperature and relative humidity graphically in real time.

Embedded System, AT89S52 Microcontroller, LCD, DHT11, Zigbee WSN, Graphical user interface(GUI), LABVIEW (Laboratory Virtual Instruments Engineering Workbench)

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