Volume-6 , Issue-5 , May - 2018 Go Back

In spite of various advantages of using signed – digit number system, so far reverse conversion has remained a major performance bottleneck of signed – digit arithmetic. Yet, the sign – magnitude output algorithm(s) for reverse conversion of signed – digit number system is known to be extensible to provide radix – complement output at constant additional time. In other words, the additional delay due to the carry that may otherwise propagate once again, may be easily eliminated. This is supposed to nullify the negative aspects of reverse conversion on arithmetic units working on signed – digit number system in longer run. Thus significant performance enhancement of signed – digit number system(s) may be possible. However, as shown in this paper, the existing digit – parallel algorithm for sign – magnitude to radix – complement output transformation can not work correctly. So a modified scheme is proposed and its correctness is proved.

Signed – Digit Number Systems, Reverse Conversion, Digit – Parallel Transformation, Conventional Form

[1] A. Avizienis, “Signed - digit number representation for fast parallel arithmetic”, IRE Transactions on Electronic Computers, Vol. 10, Issue 3, pp.389 – 400, 1961.
[2] I. Koren, Computer Arithmetic Algorithms, 2nd ed, University Press, Oxford, 2003.
[3] G. Smitha, A. H. Fahmy, A. P. Vinod, “Redundant Adders Consume Less Energy”, In Proceedings of IEEE APC on Circuits and Systems, Singapore, pp.422-425, 2006.
[4] D. Crookes and M. Jiang, “Using signed - digit arithmetic for low power multiplication”, Electronics Letters, Vol. 43, No. 11, pp. 613 – 614, 2007.
[5] D.S. Phatak, S. Kahle, H.Kim, J.Lue, “Hybrid Signed Digit Representation for Low Power Arithmetic Circuits”, In Proceddings of Low Power Workshop in Conjunction with ISCA. Barcelona, Spain, pp.1 – 7, 1998.
[6] Y.He, C.–H. Chang, “A Power - Delay Efficient Hybrid Carry - Lookahead/ Carry - Select Based Redundant Binary to Two`s Complement Converter”, IEEE Transactions on Circuits and Systems – I, Vol. 55, No.1, pp.336 – 346, 2008.
[7] S.K. Sahoo, A. Gupta, A.R. Asati, C. Shekhar, “A Novel Redundant Binary Number to Natural Binary Number Converter”, Journal of Signal Processing Systems, Vol.59, pp.297-307, 2010.
[8] M.S. Chakraborty, “Reverse Conversion Schemes for Signed – digit Numbers Systems: A Survey”, Journal of Institute of Engineers of India, Series B, Vol. 97, Issue 4, pp.589 – 593, 2016.
[9] M.S. Chakraborty, A.C Mondal, “Reverse Conversion of Signed – Digit Number Systems: Transforming Radix – Complement Output”, IJEECS, Vol. 4, No. 3, pp.665 – 669, 2016.
[10] M.S. Chakraborty, S.K. Sao, A.C. Mondal, “Equivalence of Reverse Conversion of Binary Signed-Digit Number System and Two’s-Complement to Canonical Signed-Digit Recording”, IEEE International Conference on Recent Advancement of Information Technology (RAIT), IIT (ISM), Dhanbad, India, Vol. 2, pp.662 – 666, 2018.
[11] T. Stouraitis, and C. Chen, “Fast Digit-Parallel Conversion of Signed-Digit into Conventional Representations”, Electronics Letters, Vol. 27, Issue 11, pp.964-965, 1991.
[12] T. Srikanthan, S.K. Lam, and M. Suman, “Area–Time Efficient Sign Detection Technique for Binary Signed–digit Number System”, IEEE Transactions on Computers, Vol.53, Issue 1, pp.69-72, 2004.

M.S. Chakraborty, "Reverse Conversion of Signed – Digit Number System: Fast Transformation of Sign – Magnitude Output," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.454-457, 2018.

With the advancement in technology, the emerging complexity of the systems require the development of a more intelligent system that can tackle the requirements of system/ software architectures in an efficient manner. The term ‘autonomic computing’ refers to the computing system that operates on its own or with the involvement of minimum human activity and paved the way for the system designers and system developers to develop such intelligent systems that can have adjusting capability. It completely revolutionized the area of research in the context of computing technologies. The goal of this paper is to provide insight overview of autonomic computing, followed by the challenges involved in its realization, and then applications and future application scope is discussed with the addressing of key issues.

Autonomic computing, Smart Grid, Optimal Grid, ANS, DSI

[1] S. Dobson, R. Sterritt, P. Nixon, M. Hinchey, “ Fulfilling the Vision of Autonomic Computing”, Journal Computer, Vol. 43, No.1, pp.35-41, 2010.
[2] J. O. Kephart, D. M. Chess, “ The Vision Of Autonomic Computing”, Journal Computer, Vol. 36, No. 1, pp. 41-50, 2003.
[3] S. R. White, J. E. Hanson, I. Whalley, D. M. Chess, J. O. Kephart, “An Architectural Approach to Autonomic Computing” In the Proceedings of 2004 the International Conference on Autonomic Computing (ICAC’04),New York, USA, 2004.
[4] N. Raveedran, A. S. Thanamani, “Autonomic Cloud Services to Enhance Secure Data Services for Digital Library”, American Research Journal of Computer Science and Information Technology (ARJCSIT) , Vol.1, pp. 1-10.
[5] M. Parashar, S. Hariri, “ Autonomic Computing: An Overview”, Springer, pp. 247-259, 2005.
[6] M. Salehie, L. Tahvildari, “ Autonomic Computing: Emerging Trends and Open Problems”, In the Proceedings of 2005 DEAS ’05 Proceedings of 2005 workshop on Design and evolution of autonomic application software, USA, pp.1-7,2005.
[7] I. Naveen, V. Sowjanya, ‘ Self Protection in Autonomic Computing’, International Journal of Emerging Research in Management & Technology , Vol. 4 No.12, pp. 213-217, 2015.
[8] S.K. Chauhan, A. Sharma “AUTONOMIC COMPUTING: A LONG TERM VISION IN COMPUTING”, Journal of Global Research in Computer Science, Vol. 3 No.5, pp.65-67, 2012.

A. Ahuja, "A Survey on the Challenges in Autonomic Computing," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.458-463, 2018.

There are the numbers of techniques available in the literature for the detection of denial of service attack but the effective and efficient detection of this attack in the wireless domain remains open challenges. Recently the detection of distributed denial of services attacks is the major problem in the wireless domain. In this paper, a novel technique has been designed for the detection of distributed denial of service attack in wireless networks. The proposed technique was implemented using NS2 simulator.

DDoS attack, Ids attack, ad-hoc network attack

Kaufman Charlie, Perlman Radia, Speciner Mike. Network Security: Private Commu¬nication in a Public World, 2nd ed., USA, Prentice Hall PTR, 2002.
[2]. J. Levington M. Unlocking the secret of wireless security. In Oen, p. 23 United Kingdom, Wilmington Business Publishing, Sept. 2002.
[3]. J. Mirkovic, M. Robinson, P. Reiher and G. Oikonomou, "Distributed defense against DDoS attacks" University of Delaware, CIS Department Technical Report CIS-TR-2005-02, pp. 1-12, 2005.
[4]. A. Challita, M.E. Hassan, S. Maalouf, A. Zouheiry, "A Survey of DDoS Defense Mechanisms", Department of Electrical and Computer Engineering, American University of Beirut, 2004
[5]. M. Robinson, J. Mirkovic, M. Schnaider, S. Michel and P. Reiher. "Challenges and principles of DDoS defense."In ACM SIGCOMM. 2003.
[6]. W. Znaidi, M. Minier, and J.P. Babau, "Detecting wormhole attacks in wireless networks using local neighborhood information." In Proceedings of IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1-5, 2008
[7]. Y. Xu, G. Chen, J. Ford and F. Makedon, "Distributed wormhole attack detection in wireless sensor networks." In Proceedings of the First Annual IFIP Working Group InternationalConference on Critical Infrastructure Protection, 2007.
[8]. K.S. Win, "Analysis of detecting wormhole attack in wireless networks", In World Academy °f Science, Engineering and Technology, pp. 422-428, 2008.
[9]. Y. C. Hu, Y. Chun, A. Perrig, and D.B. Johnson, "Packet leashes: a defense against wormhole attacks in wireless networks." InIEEETwenty-Second Annual Joint Conference of the Computer and Communications, Vol. 3, pp. 1976-1986, 2003.
[10]. H. Ronghui, M. Guoqing, W. Chunlei and F. Lan, "Detecting and locating wormhole attacks in wireless sensor networks using beacon nodes", World Academy of Science, Engineering and Technology, Vol. 3, 2009.
[11]. R.Z. El Kaissi, A. Kayssi, A. Chehab, and Z. Dawy, "DAWWSEN: A defense mechanism against wormhole attacks in wireless sensor networks", Ph.D. Dissertation, American University of Beirut, Department of Electrical and Computer Engineering, 2005.
[12]. S. Choi, D.Y.Kim, D.Y. Lee and J. Jung, "WAP: Wormhole attack prevention algorithm in mobile ad-hoc networks." In IEEE International Conference onSensor Networks, Ubiquitous and Trustworthy Computing, pp. 343-
[13]. T.V. Phuong, N.T. Canh, Y.K. Lee, S. Lee and H. Lee, "Transmission time-based mechanism to detect wormhole attacks", In 2nd IEEE Asia-Pacific Service ComputingConference, pp. 172-178, 2007.
[14]. V.S.S. Sriram, A.P. Singh, and G. Sahoo, AZ"Methodology for Securing Wireless LANs against Wormhole Attack", International Journal of Recent Trends in Engineering, Vol. 1, no. 1,2009.
[15]. Network Simulator, http://www.isi.edu/nsnam/ns
[16]. M. Shojaei, N. Movahhedinia, and B.T. Ladani, "DDoS attack detection in IEEE 802.16based networks", Wireless Networks, Vol. 20, Issue 8, pp. 2543-2559, 2014.
[17]. M. GhasemiGol, A. Ghaemi-Bafghi, M. Moghaddam and H. Sadoghi-Yazdi, “Anomaly detection and foresight response strategy for wireless sensor networks", Wireless Networks, Vol. 21, Issue 5, pp. 1425-1442, 2014.
[18] T.V.P. Sundararajan, S. M. Ramesh, R. Maheswar and K. R. Deepak, "Biologically inspired artificial intrusion detection system for detecting wormhole attack in MANET", Wireless Networks, Vol. 20, Issue 4, pp. 563-578, 2014
[19] G. Koutepas, F. Stamatelopoulos and B. Maglaris, "Distributed management architecture for cooperative detection and reaction to DDoS attacks", Journal of Network and Systems Management, Vol. 12, Issue 1, pp. 73-94, 2004.
[20]. T. Thapngam, S.Yu, W. Zhou and S.K. Makki, "Distributed Denial of Service (DDoS) detection by traffic pattern analysis" Peer-to-Peer Networking and Applications, Vol. 7, Issue 4, pp. 346-358, 2014.
[21]. G. Lee, W. Kim, K. Kim S. Oh and D. Kim, "An approach to mitigate DoS attack based on routing misbehavior in wireless ad hoc networks", Peer-to-Peer Networking and Applications, Vol. 8, Issue 4, pp. 684-693, 2013.
[22]. K. Verma, H. Hasbullah, and A. Kumar, "Prevention of DoS attacks in VANET”, Wireless personal communications, Vol. 73, Issue 1, pp. 95-126, 2013.
[23]. P. Rutravigneshwaran “A Study of Intrusion Detection System using Efficient Data Mining Techniques” Volume-5, Issue-6, pp. 5-8, 2017
[24]. A.Vani “Detection and Elimination of Wormhole Attacks in a MANET Vol.5, Issue.5, pp.35-40, October (2017

Sanjeev Kumar, Nishant Agnihotri, "Design of a Novel Technique for Denial of Service Attack Detection in Wireless Network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.464-468, 2018.

In today’s world where wireless technology is dominating the world, new methods are being invented each day to make wireless communication fast and efficient. One of the most popular one is Wi-Fi. It is available in almost every office, college, airport, railway station, restaurants, etc. It provides easy and quick access to internet whenever we are in need. But along with its easy availability and advantages, there are some disadvantages also. Wi-Fi requires a proper infrastructural setup and consumes more power. Moreover, it makes use of radio waves for data transmission that is harmful to our health. So, to make wireless communication more efficient and overcome disadvantages of Wi-Fi, researchers have introduced new technology called Li-Fi. It uses Light Emitting Diodes as a light source to transmit data, which makes it cheaper and more operative compared to Wi-Fi. Though Li-Fi is not being used commercial yet but in near future it is surely going to hit the wireless communication industry. In this paper, we are going to study about both Wi-Fi and Li-Fi along with which a detailed comparison between both of these technologies has been done.

Wi-Fi, Li-Fi, Wireless communication, Visible Light Communication, radio waves, light source

[1] S Dadral, “A Sneak Peek Into Future Generation, 7G :A Survey”, International Journal of Advanced Research in Computer Science, Vol. 9, No.1, pp. 399-402, January-February 2018, DOI: http://dx.doi.org/10.26483/ijarcs.v9i1.5357.
[2] Neeraj Chhabra, “Comparative Analysis of Different Wireless Technologies”, International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue 5, pp. 13-17, December 2013.
[3] Md. Biplob Hossain, Md. Selim Hossain, Md. Mahasin Ali, et.al, “Evaluation and Critical Technical Study of Li-Fi Compared with Wi-Fi and WiMax Technology”, American Journal of Engineering Research (AJER), Vol. 4, Issue 9, pp. 63-71, 2015.
[4] Prof. Vaishali Jadhav, “A Study on Li-Fi-Light Fidelity Technology”, International Journal of Scientific and Engineering Research, Vol. 5, Issue 6, pp. 709-710, June-2014.
[5] Naman Jain, Ved Sharma, “ Li-Fi-A Change Towards Future”, International Journal of Engineering Research and General Science, Vol. 3, Issue 6, pp. 357-361, November-December 2015.
[6] Osheen Sharma and S Dadral, “Light Fidelity-A way of data transmission”, International Journal of Advanced Research in Computer Science, Vol. 9, No.2, pp. 428-430, March-April 2018, DOI: http://dx.doi.org/10.26483/ijarcs.v9i2.5804.
[7] G. Kant , V. Gogate , V. Kotak, “Li-Fi Need of 21st Century”, International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue 2, pp. 49-54, May 2017.
[8] M.A. Hadi, “Wireless Communication tends to Smart Technology Li-Fi and its comparison with Wi-Fi”, American Journal of Engineering Research (AJER), Vol. 5, Issue 5, pp. 40-47, 2016.
[9] Ashish Parnami, Prof. Sanjiv Kumar, “A Review Paper on Light-Fidelity (Li-Fi)”, IJIRST , National Conference on Innovations in Micro-electronics, Signal Processing and Communication Technologies (V-IMPACT-2016) February 2016, ISSN: 2349-6010.
[10] Anurag Sarkar, Prof. Shalabh Agarwal, Dr. Asoke Nath, “Li-Fi Technology: Data Transmission through Visible Light”, International Journal of Advance Research in Computer Science and Management Studies (IJARCSMS), Vol. 3, Issue 6, June 2015, ISSN: 2321-7782.
[11] Niharika .R. Chavhan, Rakshanda .P. Shetey, Prasad .V. Dixit, Deepali Kotambkar, “Exploring Light Fidelity for Wireless Text and Audio Transmission”, International Journal of Computer Science and Engineering (IJCSE),Vol. 6, Issue 3, pp.246-250, March 2018.
[12] Sowdhaya M P, Vikas Krishna, Drashan S, Nikhil A R, “Evolution of Gi-Fi and Li-Fi in wireless network”, International Journal of Computer Science and Engineering (IJCSE), Vol. 4, Issue 3, pp.147-153, Special issue 2016.

Shruti, Osheen Sharma, "Finding an Efficient Network Medium: Wi-Fi or Li-Fi," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.469-472, 2018.

With tremendous growth of cloud computing in IT industries, cloud security has become one of the major issues that garnered noticeable attention of researchers from industries as well as academia. Cloud computing technology is vulnerable to number of security threats and attacks. Security challenges are major barriers in the adaptation of cloud computing model. Security issues are related to virtualization, network and data including eavesdropping, masquerading, privacy, confidentiality, availability of resources, access control, and identity management. In cloud computing, data are stored on a remote server and accessed through public network. Many of the cryptographic based solutions such as encryption/decryption and digital signature for authentication have been developed. In this paper, we have identified and discussed number of security issues such as authentication, access control, data confidentiality, data integrity, identity management, legal and contractual issues, data breaches, data theft, and unavailability. Moreover, we have also discussed some possible solutions to the security issues and their feasibility and security analysis in real time cloud environment.

Cloud, Data, Security, Threats, Attacks, Mitigation

[1]. P. Mell, T. Grance, “NIST Definition of Cloud Computing”, 2011.
[2]. “Top Threats to cloud Computing”, Cloud Security Alliance (CSA), 2010.
[3]. Y. Ghanam, J. Ferreira, F. Maurer, “Emerging issues & challenges in Cloud- A hybrid approach”. Journal of software engineering and applications, vol. 5, no. 11, pp.923-937, 2012.
[4]. McAfee Labs Threats Reports, 2016.
[5]. L. Wei, H. Zhu, Z. Cao, X. Dong, W. Jia, Y. Chen, A.V. Vasilakos, “Security and privacy for storage and computation in cloud computing”, ACM International Journal of Information Science, vol. 258, pp.371–386, 2014.
[6]. S. Sajithabanu, E. G. P. Raj, “Data Storage Security in Cloud”. International Journal of Computer Science and Technology, vol. 2, no. 4, pp.37-44, 2011.
[7]. S. Ruj, A. Nayak, V. Stojmenovic, “DACC: Distributed Access Control in Clouds”. In the proceeding of International Joint Conference of IEEE TrustCom, pp.91-98, 2011.
[8]. C. Gentry, “A Fully Homomorphic Encryption Scheme”, 2009.
[9]. P. Paillier, “Public-key Cryptosystems based on Composite Degree Residuosity Classes”. In the proceeding of International Conference on Theory and Application of Cryptographic Techniques, Heidelberg: Springer-Verlag, pp.223–238, 1999.
[10]. R. Rivest, A. Shamir, L. Adleman, “A Method for Obtaining Digital Signatures and Public-key Cryptosystems”. Communications of the ACM, vol. 2, pp.120–12, 1978.
[11]. S. Halevi and V. Shoup, “Design and Implementation of a Homomorphic - Encryption Library”, Nov, 2012.
[12]. R.D. Dhungana, A. Mohammad, A. Sharma, I. Schoen, “Identity management framework for cloud networking infrastructure”. In the proceeding of IEEE International Conference on Innovations in Information Technology, South Africa, pp.13–17, 2013.
[13]. G. Wang, Q. Liu, J. Wu, “Hierarchical Attribute-Based Encryption for Fine-Grained Access Control in Cloud Storage Services”, In the proceeding of 17thACM conference on Computer and communications Security, USA, pp.735-737, 2010.
[14]. Z. Wan, J. Liu, R.H. Deng, “HASBE: a hierarchical attribute-based solution for flexible and scalable access control in cloud computing”. IEEE Transaction Information Forensics Section, vol. 7, no. 2, pp.743–754, 2012.
[15]. Boneh, Dan, M. Franklin, “Identity-based encryption from the Weil pairing”, SIAM Journal on Computing”, vol. 32, no.3, pp.586-615, 2003.
[16]. Q. Liu, G. Wang, J. Wu, “Time-based proxy re-encryption scheme for secure data sharing in a cloud environment”, ACM International Journal Information Science, vol. 258, pp.355–370, 2014.
[17]. M. Rak, N. Suri, J. Luna, D. Petcu, V. Casola, U. Villano, “Security as a service using an SLA-based approach via SPEC”.In the proceeding of 5th IEEE International Conference on Cloud Computing Technology and Science, UK, pp.1-6, 2013.
[18]. M.L. Hale, R. Gamble, “Secagreement: advancing security risk calculations in cloud services”. In the proceeding of 8th IEEE World Congress on Services, pp.133-140, 2012.
[19]. “Best Practice for Mitigating Risks in Virtual Environments”, Cloud Security Alliance (CSA), April, 2015.
[20]. Z. Tari, “Security and privacy in cloud computing”. IEEE Cloud Computing, vol. 1, no. 1, pp.54–57, 2014.
[21]. A. Singh, K. Chatterjee, “Cloud security issues and challenges: a survey”. Elsevier Journal of Network and Computer Application, vol. 79, no. 1, pp.88-115, 2016.
[22]. K. K. Chauhan, A. Sanger, A. Verma, “Homomorphic Encryption for Data Security in Cloud Computing”, In the proceeding of 14th IEEE International conference on Information Technology, India, pp.206-209, 2015.
[23]. S. Subashini, V. Kavitha, “A Survey on Security issues in Service delivery models of Cloud Computing”, Elsevier Journal of Network and Computer Applications, vol. 34, pp.1-11, 2011.
[24]. N. Jain, P. Sharma, “A Security Key Management Model for Cloud Environment”, International Journal of Scientific Research in Computer Science and Engineering, vol.5, issue.1, pp.45-48, Feb-2017.
[25]. S. Kathuria, “A Survey on Security Provided by Multi-Cloud in Cloud Computing”, International Journal of Scientific Research in Network Security and Communication, vol.6, issue.1, pp.23-27, Feb-2018.
[26]. M.A. Khan, “A Survey of Security issues for Cloud Computing”, Elsevier Journal of Network and Computer Applications, vol. 71, pp. 11-29, 2016.

K. K. Chauhan, A. K. S. Sanger, "Cloud Security: Threats, Attacks and Mitigation," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.473-478, 2018.

Sentiment analysis is important part of text mining. From the last few years social networking sites like Facebook, Twitter, and Amazon generates large amount of data, such vast amount of data contains lots of useful information which need to be analyzed. As we all know social networking sites generate data in huge amount not only in terabyte but in petabyte so processing of such large amount of data is big challenge, sentiment analysis is the technique which help to analyzie such raw amount of data and extract useful information from it. The reason behind using Sentiment analysis is that it analyze such large amount of data and extract useful information from it that it analyze such large amount of data and extract useful inform Sentiment analysis helps business and organization because it’s easy for them to know how people feel about their product or services so that they can make better decision or improve their services. For that purpose we have different sentiment analysis techniques like Naïve bayes, Maximum Entropy, SVM which gives correctness of information or provides us accuracy. For sentiment we use machine learning because it train the computer to recognize the emoticon behind the sentence.

Sentiment analysis, Machine Learning. Sentiment Technique

[1]. Kolkur, S., Dantal, G., & Mahe, R. (2015). Study of different levels for sentiment analysis. International Journal of Current Engineering and Technology, 5(2), 768Ű770.
[2]. Wankhede, R., & Thakare, A. N. (2017, April). Design approach for accuracy in movies reviews using sentiment analysis. In Electronics, Communication and Aerospace Technology (ICECA), 2017 International conference of (Vol. 1, pp. 6-11). IEEE.
[3]. .Bhavitha, B. K., Rodrigues, A. P., & Chiplunkar, N. N. (2017, March). Comparative study of machine learning techniques in sentimental analysis. In Inventive Communication and Computational Technologies (ICICCT), 2017 International Conference on (pp. 216-221). IEEE.
[4]. Kumar, K. S., Desai, J., & Majumdar, J. (2016, December). Opinion mining and sentiment analysis on online customer review. In Computational Intelligence and Computing Research (ICCIC), 2016 IEEE International Conference on (pp. 1-4). IEEE.
[5]. Parveen, H., & Pandey, S. (2016, July). Sentiment analysis on Twitter Data-set using Naive Bayes algorithm. In Applied and Theoretical Computing and Communication Technology (iCATccT), 2016 2nd International Conference on (pp. 416-419). IEEE.
[6]. Rana, S., & Singh, A. (2016, October). Comparative analysis of sentiment orientation using SVM and Naive Bayes techniques. In Next Generation Computing Technologies (NGCT), 2016 2nd International Conference on (pp. 106-111). IEEE.
[7]. Prabhat, A., & Khullar, V. Sentiment classification on Big Data using Naïve Bayes and Logistic Regression
[8]. Tripathi, A., & Trivedi, S. K. (2016, October). Sentiment analysis of Indian movie review with various feature selection techniques. In Advances in Computer Applications (ICACA), IEEE International Conference on (pp. 181-185). IEEE.
[9]. Shivaprasad, T. K., & Shetty, J. (2017, March). Sentiment analysis of product reviews: A review. In Inventive Communication and Computational Technologies (ICICCT), 2017 International Conference on (pp. 298-301). IEEE.
[10]. Chachra, A., Mehndiratta, P., & Gupta, M. (2017, August). Sentiment analysis of text using deep convolution neural networks. In Contemporary Computing (IC3), 2017 Tenth International Conference on (pp. 1-6). IEEE.
[11]. Chen, X., Wang, Y., & Liu, Q. (2017). Visual and Textual Sentiment Analysis Using Deep Fusion Convolutional Neural Networks. arXiv preprint arXiv: 1711.07798.
[12]. Alam, M. H., Rahoman, M. M., & Azad, M. A. K. (2017, December). Sentiment analysis for Bangla sentences using convolutional neural network. In Computer and Information Technology (ICCIT), 2017 20th International Conference of (pp. 1-6). IEEE.
[13]. Bhoir, P., & Kolte, S. (2015, December). Sentiment analysis of movie reviews using lexicon approach. In Computational Intelligence and Computing Research (ICCIC), 2015 IEEE International Conference on (pp. 1-6). IEEE.
[14]. Vaitheeswaran, G., & Arockiam, L. (2017). Lexicon Based Approach to Enhance the Accuracy of Sentiment Analysis on Tweets. International Journal Of Computer Science And Information Technology & Security (IJCSITS), 6(3), 33-38.
[15]. Sonawane, S. L., & Kulkarni, P. V. (2017, October). Extracting sentiments from reviews: A lexicon-based approach. In Intelligent Systems and Information Management (ICISIM), 2017 1st International Conference on (pp. 38-43). IEEE
[16]. Zhang, Q., Liu, C., Zhong, S., & Lei, K. (2017, July). Spam comments detection with self-extensible dictionary and text-based features. In Computers and Communications (ISCC), 2017 IEEE Symposium on (pp. 1225-1230). IEEE.
[17]. Manohar, M. Y., & Kulkarni, P. (2017, June). Improvement sarcasm analysis using NLP and corpus based approach. In Intelligent Computing and Control Systems (ICICCS), 2017 International Conference on (pp. 618-622). IEEE.

S. Sharma, D. Singh, "Study of Sentiment Classification Techniques," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.479-783, 2018.

Remote sensor systems (WSNs) incorporate independent hubs which may be equipped with sensors to screen the physical or ecological circumstances. The objective of a WSN is to feel the environment and to convey the amassed records to the base station. Since quality is the bottleneck property of the WSNs, bringing down excess quality admission is a decent estimated examine issue. Rather than rest booking, accessible if the need arises for or occasion initiated task of the group will upgrade the execution and the lifetime. This approach is conceivable with the wake-up recipient age. The present wake-up beneficiary equipment items in the commercial center in conjunction with its continuous equipment thinks about enable us to evaluate the wake-up collector technique as a competitor work for various WSN bundles. In this paper, we investigate the wake-up collector time exceptionally well with its past, blessing and future. Subsequent to offering the country of the specialty of the wake-up innovation, we dissect the focal points and difficulties and call attention to their utility districts in the wi-fi sensor arranges In this paper, we address the favors and the requesting circumstances of utilizing the rest wakeup recipients inside the WSN bundles.

wireless sensor networks, heterogeneous network Clustering Sleep-awake, Wake-up receiver

[1] Guy, Chris. "Wireless sensor networks." Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence. Vol. 6357. International Society for Optics and Photonics, 2006.
[2] Lewis, Franck L. "Wireless sensor networks." Smart environments: technologies, protocols, and applications 11 (2004): 46.
[3] Van Dam, Tijs, and Koen Langendoen. "An adaptive energy-efficient MAC protocol for wireless sensor networks." Proceedings of the 1st international conference on Embedded networked sensor systems. ACM, 2003.
[4] Mainwaring, Alan, et al. "Wireless sensor networks for habitat monitoring." Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications. Acm, 2002.
[5] Chintalapudi, K., Fu, T., Paek, J., Kothari, N., Rangwala, S., Caffrey, J., ... & Masri, S. (2006). Monitoring civil structures with a wireless sensor network. IEEE Internet Computing, 10(2), 26-34, 2006.
[6] Ye, Wei, John Heidemann, and Deborah Estrin. "An energy-efficient MAC protocol for wireless sensor networks." INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE. Vol. 3. IEEE, 2002.
[7] Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. In INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE (Vol. 3, pp. 1567-1576). IEEE.
[8] Tan, Hwee-Pink, et al. "Impact of power control in wireless sensor networks powered by ambient energy harvesting (WSN-HEAP) for railroad health monitoring." Advanced Information Networking and Applications Workshops, 2009. WAINA`09. International Conference on. IEEE, 2009.
[9] C. Zhu, Y. Chen, L. Wang, L. Shu, and Y. Zhang, Smac-based proportionalfairness backo scheme in wireless sensor networks," in The International WirelessCommunications and Mobile Computing Conference, pp. 138{142, 2010.
[10] R. C. Carrano, D. Passos, L. C. Magalhaes, and C. V. Albuquerque, Survey and taxonomy of duty cycling mechanisms in wireless sensor networks," IEEE Communications Surveys & Tutorials, vol. 16, no. 1, pp. 181{194, 2014.
[11] Z.-Y. Xu, S.-G. Zhao, and Z.-J. Jing, A clustering sleep scheduling mechanismbased on sentinel nodes monitor for wsn," International Journal of Smart Home,vol. 9, no. 1, pp. 23{32, 2015.
[12] H. Chen, X. Li, and F. Zhao, A reinforcement learning-based sleep schedulingalgorithm for desired area coverage in solar-powered wireless sensor networks,"IEEE Sensors Journal, vol. 16, no. 8, pp. 2763{2774, 2016.
[13] H. P. Gupta, S. V. Rao, and T. Venkatesh, Sleep scheduling protocol for k-coverage of three-dimensional heterogeneous wsns," IEEE Transactions on Ve-hicular Technology, vol. 65, no. 10, pp. 8423{8431, 2016.
[14] J. Oller, I. Demirkol, J. Casademont, J. Paradells, G. U. Gamm, and L. Reindl,Has time come to switch from duty-cycled mac protocols to wake-up radio forwireless sensor networks?," IEEE/ACM Transactions on Networking, vol. 24, no. 2,pp. 674{687, 2016.
[15] R. Xie, A. Liu, and J. Gao, A residual energy aware schedule scheme for wsns em-ploying adjustable awake/sleep duty cycle," Wireless Personal Communications,vol. 90, no. 4, pp. 1859{1887, 2016.
[16] S. B. Baba and K. M. Rao, Improving the network life time of a wireless sensornetwork using the integration of progressive sleep scheduling algorithm with op-portunistic routing protocol," Indian Journal of Science and Technology, vol. 9,no. 17, 2016.
[17] Y.Wang, H. Chen, X.Wu, and L. Shu, An energy-efficient sdn based sleep schedul-ing algorithm for wsns," Journal of Network and Computer Applications, vol. 59,pp. 39{45, 2016.
[18] D. Wang, M. Mukherjee, L. Shu, Y. Chen, and G. Hancke, Sleep scheduling forcritical nodes in group-based industrial wireless sensor networks," in Communi-cations Workshops (ICC Workshops), 2017 IEEE International Conference on,pp. 694{698, IEEE, 2017.
[19] D. Ye and M. Zhang, A self-adaptive sleep/wake-up scheduling approach for wire-less sensor networks," IEEE Transactions on Cybernetics, 2017.
[20] H. Mostafaei, A. Montieri, V. Persico, and A. Pescape, A sleep scheduling ap-proach based on learning automata for wsn partial coverage," Journal of Networkand Computer Applications, vol. 80, pp. 67{78, 2017.
[21] M. I. Khalil, M. A. Hossain, R. Mamtaz, I. Ahmed, and M. Akter, Time efficient receiver oriented sleep scheduling for underwater sensor network," in Imaging,Vision & Pattern Recognition (icIVPR), 2017 IEEE International Conference on,pp. 1{6, IEEE, 2017.
[22] M. Kordafshari, A. Movaghar, and M. Meybodi, A joint duty cycle schedulingand energy aware routing approach based on evolutionary game for wireless sensornetworks," Iranian Journal of Fuzzy Systems, vol. 14, no. 2, pp. 23{44, 2017.
[23] S. Kumar and H. Kim, Low energy scheduling of minimal active time slotsfor multi-channel multi-hop convergence wireless sensor networks," in Comput-ing, Networking and Communications (ICNC), 2017 International Conference on,pp. 1051{1057, IEEE, 2017.
[24] W. Fang, M. Mukherjee, L. Shu, Z. Zhou, and G. P. Hancke, Energy utilization concerned sleep scheduling in wireless powered communication networks," in Com-munications Workshops (ICC Workshops), 2017 IEEE International Conferenceon, pp. 558{563, IEEE, 2017. A Short Review on Sleep Scheduling Mechanism in Wireless Sensor Networks
[25] Z. Chen, A. Liu, Z. Li, Y.-j. Choi, and J. Li, Distributed duty cycle controlfor delay improvement in wireless sensor networks," Peer-to-Peer Networking andApplications, vol. 10, no. 3, pp. 559{578, 2017.
[26] Nazir, Babar, and Halabi Hasbullah. "Dynamic sleep scheduling for minimizing delay in wireless sensor network." Electronics, Communications and Photonics Conference (SIECPC), 2011 Saudi International. IEEE, 2011.
[27] Nan, G., Shi, G., Mao, Z., & Li, M. (2012). CDSWS: coverage-guaranteed distributed sleep/wake scheduling for wireless sensor networks. EURASIP Journal on Wireless Communications and Networking, 2012(1), 44.
[28] Naveen, K. P., & Kumar, A. (2013). Relay selection for geographical forwarding in sleep-wake cycling wireless sensor networks. IEEE Transactions on Mobile Computing, 12(3), 475-488.
[29] Hsu, C. C., Kuo, M. S., Wang, S. C., & Chou, C. F. (2014). Joint design of asynchronous sleep-wake scheduling and opportunistic routing in wireless sensor networks. IEEE Transactions on Computers, 63(7), 1840-1846.
[30] Hammoudeh, M., & Newman, R. (2015). Adaptive routing in wireless sensor networks: QoS optimisation for enhanced application performance. Information Fusion, 22, 3-15.

Deepika Tyagi, Sanjeev Indora, "Survey of Sleep Awake Mechanism in Wireless Sensor Networks," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.484-491, 2018.

In WSNs, congestion seems to be an unpredictable stage caused by the packets collision and the overloaded network. The main reason of overloading is the neighboring nodes. In large networks, mainly neighbor nodes behave smartly to grasp the large amount of bandwidth in advance for packet transmission. The affect of low bandwidth causes the problem of packet delay and dropping rate. Both network and transport layer share the responsibility to control the congestion. To achieve these objectives, Flexible congestion control scheme (FCCFA) is proposed. FCCFA uses the closed loop congestion control technique to control the traffic rate accordingly by using three parameters. The Type-2 Fuzzy Logic System is used to estimates the adjustment rate to handle the uncertainty of data. Implicit notification system is used to notify the immediate nodes without wasting any energy. The simulated results give the proof of our promises and improvements.

Congestion Control Technique, Delay Ratio, Dropping Rate , Flexible, Fuzzy Logic System, Neighbors, Type-2 Fuzzy logic.

[1] Yeduri Sreenivasa Reddy, K. K. Pattanaik, “A Reply Cache Mechanism to Reduce Query Latency of WSNs in IoT Sensory Enviornment” 2016 IEEE International Symposium on Nanoelectronic and Information System, pp 19-21, Dec 2016, Gwalior , India.
[2] Sonmez et al: “Fuzzy Based Congestion Control for Wireless Multimedia Sensor Network” , EURASIP journal on Wireless Communications and Networking , 2014:63 , Istanbul ,Turkey.
[3] Ghaffari A. “Congestion Control Mechanisms in Wireless Sensor Networks: A Survey”, Journal of Network and Computer Applications 2015, Tabriz , Iran.
[4] Dharmendera Singh , Neeraj Singh kushwaha , Sachin Kumar, “ Fast AIMD: A Fairness Based Congestion Control Approach for TCP Networks”, International Conference on Computing Communication and Automation 2015.
[5] Hrvoja Kozacinski, Peter Knezevid, “An Approach using Simulation Techniques to Estimate Quality of Service Parameter in Communication Networks”, MIPRO Opatiya, Croatic, 26-30, May 2014.
[6] K M Archana Patel , Richa Martolia, “Congestion Control Techniquesin Networking”, International Conference on Communication and Signal Processing 2016, India.
[7] Majid Hatamian, Hamid Barati , “Priority based Congestion Control Mechnism for Wireless Sensor Networks using Fuzzy Logic”, IEEE Journal on ICCCNT 2015, July , 13-15, 2015, Denton , U.S.A.
[8] Sara Ghanavati, Jemal Abawajy and Davood Izadi, “A Congestion Control Scheme Based on Fuzzy Logic in Wireless Body Area Networks”, IEEE- International Symposium on Network Computing and Applications 2015.
[9] O. B. Akan, I.F. Akyidiz, “ESRT: Event to Sink Reliable Transport in Wireless Sensor Networks” , IEEE Transactions on Networking 2005.
[10] Saad A. Munir, Yu Wen Bin, Ren Biao, Ma Jian, “Fuzzy Logic Based Congestion Estimation for QoS” , Wireless Communications and Networking conference 2007, Kowloon, China.
[11] Saurabh Jaiswal, Anamika Yadav, “Fuzzy Based Adaptive Congestion Control in Wireless Sensor Networks”, IEEE 2013, Raipur , India.
[12] Arpita Chakroborty, Srinjoy Ganguly, Mrinal Kanti Naskar, Anupam Karmakar, “A Trust Based Fuzzy Algorithm for Congestion Control in Wireless Multimedia Sensor Networks”, Journal of IEEE 2013, Kolkata, India.
[13] Rakha Chakravarthi, C Gomathy, “IFCCDC: A Fuzzy control based Congestion Detection and Control in Wireless Sensor Networks”, International Journal of Computer Applications, 12-17, June 2012.
[14] Roxanne Hawi, George Okayo, Michael kimwale, “ Smart Traffic Light Control using Fuzzy Logic and Wireless Sensor Networks”, IEEE 2017, 18-20 , July , London, UK.
[15] C. Chrysostomou , K. Tatas and A.R. Runcan, “A Dynamic Fuzzy logic based Routing Scheme for Bufferless NoCs”, IEEE 2012, Nicosia , Cyprus.
[16] Rekha Chakravarthi, “A Fuzzy Approach to Detect and Control Congestion in Wireless Sensor Networks”, IJCSE, Chennai, India.
[17] Hemba S, Islam N, “Fuzzy Logic: A Review”, IJCSE, Guwahati, India.

M. Arora, S. Upadhyaya, N. Kashyap, "Flexible congestion control using fuzzy logic for Wireless Sensor Networks," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.492-499, 2018.

— Natural Language Processing (NLP) is a branch of artificial intelligence which deals with the analysis and synthesis of natural languages in the form of text and speech. NLP requires stemming algorithms to remove derivational and inflectional affixes without performing morphological analysis of the inputs. These algorithms are essential to extract root or stem words. The goal of stemming is to reduce word forms/grammatical forms to their root forms. To accomplish, specific knowledge of language is required. In NLP, the stemmer can be used to improve the efficiency of text summarization, text mining, information retrieval and sentiment analysis. In this paper, we proposed a rule based stemming approach for Marathi language using Marathi corpus, stopword list and suffix stripping rules.

natural language processing, stemming, corpus, marathi, suffix stripping and stopwords

[1]Ciravegna F, Harabagiu S, “Recent Advances in Natural Language Processing”.IEEE,2013.
[2] Garje, G. V., & Kharate, G. K. “Survey of machine translation systems in India.” International Journal on Natural Language Computing (IJNLC) Vol, 2, 47-67, 2013.
[3] Hovy, E., & Lin,C.Y., “Automated text summarization and the SUMMARIST system”. In Proceedings of a workshop on held at Baltimore, Maryland: October 13-15, 1998. Association for Computational Linguistics, (1998, October).
[4] Lin, C. Y. Rouge: A package for automatic evaluation of summaries. In Text summarization branches out: Proceedings of the ACL-04 workshop (Vol. 8), (2004, July).
[5] M. Kasthuri and S. B. R. Kumar “A Comprehensive Analyze Of Stemming Algorithms For Indian And Non-Indian Languages” International Journal of Computer Engineering and Applications, Volume VII, Issue III, September 14.
[6] M.Thangarasu., R.Manavalan, “A Literature Review: Stemming Algorithms for Indian Languages”, International Journal of Computer Trends and Technology (IJCTT), volume 4 Issue 8, August 2013.
[7] Mihalcea, R., & Tarau, P.,“TextRank: Bringing order into texts. Association for Computational Linguistics”, (2004, July).
[8] Ms. Anjali Ganesh Jivani, “A Comparative Study of Stemming Algorithms”, International Journal of Computer Technology and Applications, Vol.2 (6), PP 1930-1938, NOV-DEC 2011.
[9] Mudassar, Tanveer J Siddiqui, “Discovering suffixes: A Case Study for Marathi Language”, (IJCSE) International Journal on Computer Science and Engineering, 2010.
[10]Rohit Kansal Vishal Goyal G. S. Lehal, “Rule Based Urdu Stemmer”. Proceedings of COLING 2012: Demonstration Papers, pages 267–276, COLING 2012, Mumbai, December 2012.
[11] Sajjad Ahmad Khan1, Waqas Anwar1, Usama Ijaz Bajwa1, Xuan Wang2, “A Light Weight Stemmer for Urdu Language: A Scarce Resourced Language”, Proceedings of the 3rd Workshop on South and Southeast Asian Natural Language Processing (SANLP),, COLING 2012, Mumbai, December 2012.
[12]Snigdha Paul, Mini Tandon, Nisheeth Joshi and Iti Mathur, “Design of a rule based Hindi Lemmatizer”, pp. 67–74, 2013.
[13]Upendra Mishra, Chandra Prakash, “MAULIK: An Effective Stemmer for Hindi Language”, International Journal on Computer Science and Engineering (IJCSE) Vol. 4 No. 5, PP.711-717, May 2012.
[14]V.Gupta,N.Joshi,I.Mathur,”Design & Development of Rule Based Infectional and Derivational Urdu Stemmer ‘Úsal’” ,INBUSH-ERA-2015,7-12,2015.
[15] V.Gupta,N.Joshi,I.Mathur, “Design & Development of Rule Based Urdu Lemmatizer”,IEEE,2015.
[16]V.Gupta,N.Joshi,I.Mathur, “Rule based stemmer in Urdu”,Computer and Communication Technology(ICCCT) 2013 4th International,2013.
[17]Virat V. Giri, Dr.M.M. Math & Dr.U.P. Kulkarni, “A Survey of Automatic Text Summarization System for Different Regional Language in India”, In Bonfring International Journal of Software Engineering and Soft Computing, Vol. 6, Special Issue, October 2016

N. Pise, V. Gupta, "Rule based Stemmer for Marathi Language," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.500-505, 2018.

Cloud computing is a set of different types of hardware and software activities that work collectively to deliver many aspects of computing to the end user as an online services. It provides on demand scalable and cost effective services for storing documents. However with all of these features it enters with number of challenges associated in utilizing the cloud securely. Achieving unbreakable document or outsourced data security is an important issue to consider. For this purpose encryption has been suggested, with the popularity of using cryptography to store data in the cloud Attribute Based Encryption receives widespread attention of the researchers. Also to provide security to the outsourced documents, Attribute based encryption is an excellent solution. On the other side of cloud environment, to increase productivity of the cloud, collaboration with more users is important. But the encryption limits the admission of newly authorized user to acquire the data because, when the ciphertext is need to be share with others legally there will be necessity of extending an original access policy specified in ABE. In this process, at the time of extending policy, data uploader had to download ciphertext, modify the access policy as per current requirement and then reupload the data with modified access permissions. This significantly increases the processing time to extend access policy and consumes server space unnecessarily. To address above problem we have introduce modified attribute based encryption with time varying encryption scheme for document encryption which is based on the research of Time Varying Camellia Encryption Algorithm for the cloud storage environment and a novel solution for access permission management in which we will use metadata file to store access permission. Finally we discuss the evaluation result made in between existing work and proposed system.

Time varying encryption, Extended Access Control, Collaboration in cloud, Attribute Based Encryption

[1] Hamlen, K., Kantarcioglu, M., Khan, L., Thuraisingham, B.,”Security issues for cloud computing”, International Journal of Information Security and Privacy, 2010
[2] Chen, Y., Paxson, V., Katz, R. ,”What’s new about cloud computing security”, Tech. Rep. UCB/EECS-2010-5, Electrical Engineering and Computer Sciences, University of California at Berkeley 2010.
[3] Kandukuri, B., Paturi V, R., Rakshit, ,”A.: Cloud security issues”, In: Proceedings of the IEEE International Conference on Services Computing, SCC’09, pp. 517–520. IEEE Computer Society, Washington, DC, USA DOI 10.1109/SCC.2009.84,2009.
[4] Willy Susilo, Peng Jiang, Fuchun Guo, Guomin Yang, , Yong Yu and Yi Mu, Extendable Access Control System with IntegrityProtection,IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY DOI 10.1109/TIFS.2017.2737960.
[5] Amit Sahai and Brent Waters, “Fuzzy identity-based encryption,” in EUROCRYPT 2005, ser. LNCS, vol. 3494, 2005, pp. 457–473.
[6] Saravana Kumar, Rajya Lakshmi, Balamurugun. Enhanced Attribute Based Encryption For Cloud Computing , International Conference on Information and Communacation Technologies (ICICT 2014)
[7] V. Goyal, O. Pandey, A. Sahai, and B. Waters, “Attribute-based encryption for fine- grained access control of encrypted data,” in Proceedings of the 13th ACM Conference on Computer and Communications Security, CCS 2006, 2006, pp. 89–98.
[8] M. Li, S. Yu, Y. Zheng, K. Ren, and W. Lou, “Scalable and secure sharing of personal health records in cloud computing using attribute based encryption,” IEEE Trans. Parallel Distrib. Syst., vol. 24, no. 1,pp. 131–143, 2013.
[9] Issa M. Khalil, Abdallah Khreishah and Muhammad Azeem “Cloud Computing Security: A Survey”, Computers, 2014
[10] P. Shanmuga Priya and R. Sugumar, “MultiKeyword Searching echniques over Encrypted Cloud Data”, IJSR,2014.
[11] Cong Wang, Ning Cao, Kui Ren and Wenjing Lou “Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data”, IEEE Transactions on Parallel and Distributed Systems, 2012.jk
[12] Preethi.D, Priya.J and shanthini.B, “Retrieval of Encrypted Data Using Multi Keyword Top –K Algorithm”, International Journal of Scientific and Research Publications, 2014.
[13] Yan Wang and Nihong Wang , “Research on Time-Varying Camellia Encryption Algorithm”, https://link.springer.com/chapter/10.1007/978-3-642-29455-6_110.
[14] Kapil Dev Raghuwanshi, Prof. Sitendra Tamrakar, An effective Access from Cloud Data using AttributeBased Encryption,2015 1st International conference on futuristic trend in computational analysis and knowledge management (ABLAZE 2015).

Salim Y. Amdani., Sohel A. Bhura, Akshada D. Yevatkar, "Implementation of TVES for Enhancing Performance of Attribute Based Encryption and Collaboration in the Cloud Storage," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.506-512, 2018.