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In this paper we presents a comprehensive literature survey of cognitive radio technology, focusing on its application to dynamic resource allocation, based on priority scheduling approach. Dynamic spectrum access provides resource sharing between primary users called licensed users (PUs) and Secondary Users called unlicensed users (SUs). An essential examination test is that in what capacity ought to be apportioned or relegated accessible unused range to unlicensed clients. The fitting bit of unmoving repeat range existing together learned radios while enhancing hard and fast transmission limit usage furthermore minimizing impedance is required for the profitable extent use in CRN. The system for settled extent segment came to fruition to less range utilization over the entire reach. In this paper we presented the different approaches used for dynamic resource allocation and scheduling in heterogeneous Cognitive radio networks.

Cognitive Radio; Energy; OFDM; Resource Allocation; Spectrum sensing; Heterogenitive services

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S. Tamilarasan and P. Kumar, "Dynamic Resource Allocation in Cognitive Radio Networks – Priority Scheduling approach: Literature Survey," International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.1-11, 2016.

Virtualization plays a main role in the cloud computing technology, usually in the cloud computing, users share the data there in the clouds like application etc., but with virtualization users shares the communications. A general technique to enhance the energy proficiency of a datacentre is VM placement by coordinating the quantity of dynamic servers to the present needs of the VMs and setting the remaining servers in low-control standby modes using SLA violations .In cloud computing environments, cloud service users consume cloud resources as a service and pay for service use. Before a cloud provider provisions a service to a consumer, the cloud provider and consumer (or broker) need to establish a service level agreement. So this work explored the utilization of VM migration with GA algorithm in MATLAB environment. We found the performance parameters like Number of VMs, Response time, Throughput and Execution Time.

Virtual Machine Security, Genetic Algorithm, Deployment Models, Service Level Agreement

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Anu Thind, Mandeep Devgan, "Improvement of SLA Parameters in Virtual Machine Migration by using Genetic Algorithm," International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.12-22, 2016.

There are lots of applications where only periodic monitoring (sweep coverage) is sufficient instead of continuous monitoring. The main goal of sweep coverage problem is to minimize the number of mobile sensor nodes moving with uniform velocity required to guarantee coverage as per given sweep time. Sweep coverage problems are broadly categorized in three types depending on applications viz point sweep coverage, area sweep coverage and boundary sweep coverage. In this paper we have solved the problem of point sweep coverage, where a set of densely spaced points in the given region are periodically monitored using convex hull algorithm.

Sweep coverage problem; Area sweep coverage; Point sweep coverage; convex hull algorithm; Tessellation

[1] Gurbax Kaur, Ritesh Sharma, “A Review on Sweep Coverage in Wireless Sensor Networks”, International Journal of Computer Sciences and Engineering, Volume-4, Issue-6, Page No (113-117), June 2016, E-ISSN:2347-2693.
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Gurbax Kaur, Ritesh Sharma, "Point Sweep Coverage in Wireless Sensor Networks Using Convex Hull Algorithm," International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.23-27, 2016.

A sensor network consist of low battery power, low cost, limited storage, tiny sensing devices. The one of the significant challenge in wireless sensor network is how well the network is monitored while maximizing network’s lifetime. Since sensing and transmitting data consume sensors’ energy, so to preserve energy an optimal sensor node scheduling scheme is required where only an optimal number of sensors are activate and other node are eligible to shut down to save their energy which can be used to prolong lifetime of sensor network. In this paper we introduced a node scheduling scheme which is based on optimal Coverage Preserving Scheme (OCoPS) that first check the redundant sensor and then decide to turn itself off. Further, in wireless sensor network there may exist some regions where sensors are not able to sense data or communicate which are called hole regions. Since hole region may jeopardize sensing, communicating or connectivity of sensor network, therefore identification of hole regions is also prime concern. In this paper, we first detect the hole regions in sensor network and then deploying sensors at appropriate location for covering that region. Our hole detection approach is based on Boundary Critical Points. The simulation results demonstrate that the proposed algorithm can lead to a high coverage ratio while keeping long network’s life.

WirelessSensor, Scheduling Sensor, Hole Detection, Wireless Network

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Somil Tyagi and Jaspreet Kaur, "A Literature Review in Wireless Sensor Hole Detection Along with Node Scheduling Algorithm," International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.28-32, 2016.

Detection of indoor static objects by visually impaired without help of third person is a crucial task. The indoor object detection enables a visually impaired to settle on suitable and convenient choices of route to follow in an indoor area. Literature presents that methods such as Electronic Travel Aids (ETA), Augmented Reality (AR) and Navigation Assistance for Visually Impaired (NAVI) are used to assist visually impaired. These methods are expensive and involves overhead for every decision. This paper presents an algorithmic based model which uses machine learning technique. In the proposed methodology firstly, the database is prepared which consist of various images of objects to train the system. During the use, the image which is captured by the visually impaired is compared with entries of the database to detect the object. The experiments were conducted using MATLAB for image recognition and analysis.

Image processing; Machine learning; Indoor object detection; Visually Impaired; Blind people; Navigation; Object recognition applications; MATLAB

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Pritam Shaha, Niranjan Kshatriya and Rahul Borse, "Static Indoor Object Detection Using MATLAB For Visually Impaired," International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.33-37, 2016.

Now a day, large amounts of heterogeneous digital data is available this big data need to be carefully examined for analysis point of view. Big data is nothing but a large volume of heterogeneous and distributed data collection. In real world big data applications has contain huge amount of continuously grow able data but it is very costly to clean up, extract , manage and process data using present software tools. Fast and accurate retrieval of the relevant information from dataset has always been a significant issue. Prominent and accurate data clustering is a main task of exploratory data analysis and data mining applications. Clustering process is one of the data mining techniques for dividing informative dataset into group and it is a kind of unsupervised data mining technique.

Big data, Clustering, Data Mining

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[4] Chen, H., Chaing, R.H.L. and Storey, V.C. (2012) Business Intelligence and Analytics: From Big Data to Big Impact, MIS Quarterly, 36, 4, pp. 1165-1188.
[5] Neelamadhab Padhy, Dr. Pragnyaban Mishra and Rasmita Panigrahi, “The Survey of Data Mining Applications And Feature Scope”, International Journal of Computer Science and Informatio Processing(CSIP).
[6] Wu Yuntian, Shaanxi University of Science and Technology, “Based on Machine Learning of Data Mining to Further Explore”, 2012 International Conference on Machine Learning Banff, Canada.
[7] Guo, G, Neagu, D. (2005) Similarity-based Classifier Combination for Decision Making . Proc. Of IEEE International Conference on Systems, Man and Cybernetics, pp. 176-181
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[9] Wu, X., Zhu, X., Wu, G., Ding, W. (2014) Data Mining with Big Data, Knowledge and Data Enginnering , IEEE Transactions.
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Vishal Kumar Gujare, Pravin Malviya, "A Novel Algorithm for Big Data Clustering," International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.38-40, 2016.

Data mining is the process of extract unseen and hidden information from a large amount of data. It is a powerful technology that helps researchers to find the meaningful information by providing different tools and technologies. In this paper we focused on different tools, technologies and application area of data mining. Also discussed the weka tool,how we build data set for weka and how this data set is loaded on weka.

DataMining,MachineLearning,Clustering,Classification, WekaTool

[1] Jiawei Han, Micheline Kamber “ Data Mining: Concepts and Techniques”, Morgan Kaufmann Publishers, Second Edtion- 2006, ISBN: ISBN: 978-1-5090-0669-4
[2] Ravneet Jyot Singh, Williamjeet Singh "Data Mining in Healthcare for Daibetes Mellitus", International Journal of Science and Research, Volume-03, Issue-07, Page No (1993-1998), July 2014.
[3] Mansi Gera, Shivani Goel “Data Mining – Techniques , Methods and Algorithms: A Review on Tools and their Validity”, International Journal of Computer Applications, Volume-113, Issue-19,Page No (22-29),March2015.
[4] A. Michael, “IBM developerWorks : IBMs resource for developers and IT,” 27 April 2010. [Online]. Available: http://www.ibm.com/developerworks/library/ba-data-mining-techniques/.
[5] Beant Kaur, Williamjeet Singh “Review on heart disease prediction using data mining techniques,” International Journal on recent and innovation trends in computer and communication , Volume- 2, Issue-10,Page No( 3003-3008), October2014.
[6] Vikas Chaurasia, Saurabh Pal “Data Mining Approach to Detect Heart Dieses,” International Jouranal of Advanced Computer Science and Information Technology,Volume-02, Issue-04, Page No (56-66), 2013.
[7] Mohd Fauzi bin Othman, Thomas Moh Shan Yau “Comparision of different classificaton techniques using WEKA for Breast Cancer,” Springer, Volume-15, Issue-04, Page No (520-523), 2007.

Kulwinder Kaur, Shivani Dhiman, "Review of Data Mining with Weka Tool," International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.41-44, 2016.

In order to diagnose any disease, the expert system developed by human may be a cheering way out to diminish cost, time, human efforts and medical error. This paper focuses on today’s most severe heart related diseases. It also discusses different expert systems that are presently used in the field of medical sciences. Further, noteworthy contribution is also cited. Additionally, it reveals the well-known database used for heart disease diagnosis i.e. UCI repository.

Diagnosis, Expert System, FIS, Fuzzy, Heart Attack

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[4] Heon Gyu Lee, Ki Yong Noh and Keun Ho Ryu, “Mining Bio-signal Data: Coronary Artery Disease Diagnosis using Linear and Nonlinear Features of HRV,” LNAI 4819: Emerging Technologies in Knowledge Discovery and Data Mining, pp. 56-66, May 2007.
[5] Cristianini, N. and Shawe-Taylor, J. “An introduction to Support Vector Machines”, Cambridge University Press, Cambridge, 2000.
[6] Li, W., Han, J. and Pei, J., “CMAR: Accurate and Efficient Classification Based on Multiple Association Rules”, In: Proc. of 2001 International Conference on Data Mining. 2001.
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[9] Sellappan Palaniappan, Rafiah Awang, "Intelligent Heart Disease Prediction System Using Data Mining Techniques", IJCSNS International Journal of Computer Science and Network Security, Vol.8 No.8, August 2008.
[10] Niti Guru, Anil Dahiya, Navin Rajpal, "Decision Support System for Heart Disease Diagnosis Using Neural Network", Delhi Business Review, Vol. 8, No. 1, 2007.
[11] Carlos Ordonez, "Improving Heart Disease Prediction Using Constrained Association Rules," Seminar Presentation at University of Tokyo, 2004.
[12] Franck Le Duff, Cristian Munteanb, Marc Cuggiaa, Philippe Mabob, "Predicting Survival Causes After Out of Hospital Cardiac Arrest using Data Mining Method", Studies in health technology and informatics, Vol. 107, No. 2, pp. 1256-9, 2004.
[13] Boleslaw Szymanski, Long Han, Mark Embrechts, Alexander Ross, Karsten Sternickel, Lijuan Zhu, "Using Efficient Supanova Kernel For Heart Disease Diagnosis", proc. ANNIE 06, intelligent engineering systems through artificial neural networks, vol. 16, pp:305-310, 2006.
[14] Kiyong Noh, Heon Gyu Lee, Ho-Sun Shon, Bum Ju Lee, and Keun Ho Ryu, "Associative Classification Approach for Diagnosing Cardiovascular Disease", Springer,Vol:345, pp. 721- 727, 2006.
[15] Tanmay Kasbe, Ravi Singh Pippal, “Dengue Fever: State-of-the-Art Symptoms and Diagnosis,” International Journal of Computer Sciences and Engineering, vol. 04, no. 06, 2016, pp. 26-30.
[16] Manish B. Giri, Ravi Singh Pippal, “Agricultural Environmental Sensing Application Using Wireless Sensor Network for Automated Drip Irrigation,” International Journal of Computer Sciences and Engineering, vol. 04, no. 07, 2016, pp. 133-137.
[17] Md Jahid Akhtar, Rakesh Kumar Sanodiya, Ravi Singh Pippal, “Fuzzy Logic Controlled Resource Allocation for Efficient Load Balancing in Cloud Computing Environment,” International Journal of Engineering Sciences and Research Technology, vol. 5, no. 1, 2016, pp. 135-140.
[18] M. V. Jagannatha Reddy and B. Kavitha, “Expert System to Predict the Type of Fever Using Data Mining Techniques on Medical Databases,” International Journal of Computer Sciences and Engineering, vol. 03, no. 09, 2016, pp. 165-171.
[19] Pima Indians Diabetes Data Set, [Online], Available: http://archive.ics.uci.edu/ml/datasets/Pima+Indians+Diabetes

Suresh Nagar, Arvind Kumar Jain, "Expert System for Diagnosis of Heart Disease: A Review," International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.45-47, 2016.

Orthogonal frequency division multiplexing(OFDM) is the case of multicarrier transmission in which a single data stream is transmitted over a number of subcarriers of lower rate. OFDM is a modulation format that is being used in latest wireless and telecommunications standards. OFDM has been adopted in the Wi-Fi arena where the standard like 802.11a, 802.11n, 802.11ac. It has been chosen for the cellular telecommunication standard 4G LTE. OFDM has been adopted for a number of broadcast standards from DAB digital radio to the digital video broadcast standards, DVB. OFDM effectively reduce the inter-symbol interference(ISI) caused by the delay spread of wireless channels. OFDM has been used in both wired and wireless communication medium. One of the major drawback of OFDM is its peak to average power ratio(PAPR). In this paper we are going to discuss basics of OFDM techniques, scopes, losses and its application.

Orthogonal Frequency Division Multiplexing (OFDM), Bit Error Rate(BER), Intersymbol Interference(ISI), Peak To Average Power Ratio(PAPR).

[1] Ahmed, Bannour, and Mohammad Abdul Matin. “Coding for MIMO-OFDM in Future Wireless Systems.” Springer International Publishing, 2015.
[2] Sukhpalsingh, Harmanjotsingh.“ Review paper on OFDM-concepts and applications.” 2015 international journal of engineering development and research |volume 3,issue 3| ISSN: 2321-9939.
[3] Han, SeungHee, and Jae Hong Lee. "An overview of peak-to-average power ratio reduction techniques for multicarrier transmission." Wireless Communications, IEEE 12.2 (2005): 56-65.
[4] Karimi, Bashir Reza, MojtabaBeheshti, and Mohammad JavadOmidi. "PAPR Reduction in MIMO-OFDM Systems: Spatial and Temporal Processing." Wireless Personal Communications 79.3 (2014): 1925-1940.
[5] Vishal Pasi, PrateekNigham andDr. VijayshriChaurasia. “Review on OFDM a brief survey.” International journal of scientifics and research publications, volume 3, issue 11,November 2013.
[6] Shi, Zhenguo, et al. "Improved spectrum sensing for OFDM cognitive radio in the presence of timing offset." EURASIP Journal on Wireless Communications and Networking 2014.1 (2014): 1-9.
[7] Mishra, Amit, Rajiv Saxena, and Manish Patidar. "OFDM link with a better performance using artificial neural network." Wireless personal communications 77.2 (2014): 1477-1487.
[8] Kamruzzaman, M. M. "Performance of turbo coded wireless link for SISO-OFDM, SIMO-OFDM, MISO-OFDM and MIMO-OFDM system." Computer and Information Technology (ICCIT), 2011 14th International Conference on. IEEE, 2011.
[9] ManushreeBhardwaj, ArunGangwar and DevendraSoni. “ Areview on OFDM: Concept, Scope and its applications.”IOSR journal of mechanical and civil Engineering, Volume 1, issue 1(may-june 2012).
[10] Da Costa Pinto, Fabio, et al. "A low cost OFDM based modulation schemes for data communication in the passband frequency." Power Line Communications and Its Applications (ISPLC), 2011 IEEE International Symposium on. IEEE, 2011.
[11] Nuwanpriya, Asanka, et al. "Position modulating OFDM for optical wireless communications." Globecom Workshops (GC Wkshps), 2012 IEEE. IEEE, 2012.
[12] Sumathi, K., and M. L. Valarmathi. "Resource allocation in multiuser OFDM systems—A survey." Computing Communication & Networking Technologies (ICCCNT), 2012 Third International Conference on. IEEE, 2012.
[13] Dissanayake, SarangiDevasmitha, and Jean Armstrong. "Comparison of ACO-OFDM, DCO-OFDM and ADO-OFDM in IM/DD Systems." Journal of lightwave technology 31.7 (2013):1063-1072.
[14] B. Benarji , Prof G. SasibhusanaRao and S.PallamSetty “BER Performance of OFDM System with various OFDM frames in AWGN, Rayleigh and Rician Fading Channel. “International Journal of Computer Sciences and Engineering” Volume 3, issue 4 (2015).
[15] AnuragPandey and Sandeep Sharma, “BERperformance of OFDM System in AWGN andRayleigh Fading Channel” International Journal of Engineering Trends and Technology, ISSN: 2231-5381, Volume 13, Number 3, July 2014, pp. 126-128.

Rizwan Ahmed malik, Shahid Shabir, Ruchi Singla, "Review on OFDM: Concept, scope and its application," International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.48-50, 2016.

Transmission lines consume a considerable amount of power. The necessity of power and its dependency has grown exponentially over the years. The void between limited production and tremendous demand has increased the focus on minimizing power losses. For a modern power system, high speed fault clearance is very critical and to achieve this objective various techniques have been developed. This paper presents survey of various techniques used for classification of transmission line faults.

Transmission Lines, Faults, Classification Techniques, Electric Power System, Fault Detection

[1] Anamika Yadav, Aleena Swetapadma, “A novel transmission line relaying scheme for fault detection and classification using wavelet transform and linear discriminant analysis”, Elsevier, Page No (199-209), 2015.
[2] B. Jagan Mohan,N. Ramesh Babu, “Fault classification in power system using EMD and SVM”, Elsevier, Page No (1-9), August 2015.
[3] M. Sanaye-Pasand, H. Khorashadi-Zadeh,” Transmission Line Fault Detection & Phase Selection using ANN”, International Conference on Power Systems Transients – IPST, Page No (1-6), 2003 .
[4] Zhi-kun Hu, Wei-hua Gui, Chun-hua Yang, Peng-cheng Deng, and Steven X. Ding, “Fault Classification Method for Inverter Based on Hybrid Support Vector Machines and Wavelet Analysis”, Springer (2011),pp. 1-8.
[5] Anamika Yadav, A.S. Thoke, “Transmission line fault distance and direction estimation using artificial neural network”, International Journal of Engineering, Science and Technology, Vol. 3, No. 8, Page No (110-121), 2011.
[6] Ch. Durga Prasada, N. Srinivasua, “Fault Detection in Transmission Lines using Instantaneous Power with ED based Fault Index”, Elsevier, Page No (132-138), August 2015.
[7] Kola Venkataramana Babu, Manoj Tripathy and Asheesh K Singh, “Recent techniques used in transmission line protection: a review”, International Journal of Engineering, Science and Technology, Vol. 3, No. 3, Page No (1-8), 2011.
[8] P. Chiradeja and A. Ngaopitakkul, Member, IAENG, “Identification of Fault Types for Single Circuit Transmission Line using Discrete Wavelet transform and Artificial Neural Networks”, Proceedings of the International Multi Conference of Engineers and Computer Scientists , IMECS vol. 2, Page No (1-6), March 2009.

Trisha Chaudhary and Nitima Malsa, "A Survey: Fault Classification Techniques," International Journal of Computer Sciences and Engineering, Vol.4, Issue.8, pp.51-53, 2016.