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In many real world applications, we often face high dimensional data. Developing efficient clustering methods for high dimensional datasets may be a challenging problem because of the curse of dimensionality. Common method to deal with this is to use first dimensionality reduction approach and then cluster the data in the lower dimensions. Even though we can initially reduce the dimensionality by any approach and then use clustering approaches to group high dimensional data, performance can also be improved since these two techniques are conducted in sequence. Naturally, if we consider the requirement of clustering during the process of dimensionality reduction and vice versus then the performance of clustering can be improved. This paper presents a review of different techniques for clustering high dimensional data by joint feature learning and clustering.

Clustering, high dimensional data, feature learning, dimensionality reduction

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Ghatage Trupti B., Patil Deepali E., Takmare Sachin B., Patil Sushama A., "Joint Feature Learning and Clustering Techniques for Clustering High Dimensional Data: A Review," International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.54-58, 2016.

Duplicated web pages in consist of identical structure but regarded as clones regarded as clones different data. The identification of similar and near-duplicate pairs in a large collection is a significant the problem with the twide-spread application. The problem deliberated for diverse data types in diverse settings. The contemporary materialization is efficient of the problem identification of the near duplicate Web pages. This is challenging in the web scale to the voluminous data and the high dimensionalities of documents. This review has a fundamental intention to present an up-to-date review of the existing of literature in duplicate and near duplicate detection of general documents and web documents in web crawling. The classification of the existing literature in duplicate and the near duplicate detection techniques and a detailed description of same are the presented so as to make the review more comprehensible.

Web crawling, web pages, web mining, web content mining, and duplicate document, near duplicate detection

[1] Andrei Z. Broder., "Identifying and Filtering Near-Duplicate Documents", Proceedings of the 11th Annual Symposium on Combinatorial Pattern Matching. UK: Springer-Verlag, pp. 1-10, 2000.
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[3] Bernstein, Y., Shokouhi, M., and Zobel, J., "Compact Features for Detection of Near- Duplicates in Distributed Retrieval", in 'Proceedings of String Processing and Information Retrieval Symposium (to appear)', Glasgow, Schotland, 2006.
[4] Charikar, M.,“Similarity estimation techniques from rounding algorithms”, In Proc. 34th Annual Symposium on Theory of Computing (STOC 2002), pp. 380-388, 2002.
[5] Chowdhury, A., Frieder, O., Grossman, D., and Catherine Mccabe, M., “Collection Statistics for Fast Duplicate Document Detection", In. ACM Transactions on Information Systems (TOIS), Vol. 20, No. 2, 2002.
[6] Deng, F., Rafiei, D., "Approximately detecting duplicates for streaming data using stable bloom filters" ,Proceedings of the 2006 ACM SIGMOD international conference on Management of data, pp. 25-36, 2006.
[7] Deng, F., Rafiei, D., "Estimating the Number of Near Duplicate Document Pairs for Massive Data Sets using Small Space", University of Alberta, Canada, 2007.
[8] Manku, G. S., Jain, A., Sarma, A. D., "Detecting near-duplicates for web crawling", Proceedings of the 16th international conference on World Wide Web, pp: 141 – 150, 2007.
[9] Udi Manber., "Finding Similar Files In A Large File System", Proceedings of the USENIX Winter 1994 Technical Conference on USENIX Winter 1994 Technical Conference, San Francisco, California, pp. 2-2, 1994.
[10] Ye, S., Wen, J., R., and Ma, W.Y., "A systematic study of parameter correlations in large scale duplicate document detection", Text and Document Mining, 10th Pacific-Asia Conference, PAKDD 2006, Singapore, April 9-12, pp. 275-284, 2006.

Patil Deepali E., Ghatage Trupti B., Takmare Sachin B., Patil Sushama A., "A Review on Duplicate and Near Duplicate Documents Detection Technique," International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.59-62, 2016.

A vital challenge in the design of Wireless Sensor Network is to improve the network lifetime. Wireless Sensor nodes convey limited essential power source. In single static sink node based wireless sensor network, a sensor node spends the most of its energy for relaying data packets particularly which are situated in the surrounding area of the sink node. They distribute their energy so fast because of numerous to one traffic pattern and finally they die. This uneven depletion phenomenon is known as hot spot issue which gets to be more genuine as the number of sensor nodes increase. Replacing these energy sources in the field is normally not feasible. So if the distance between a sensor node and sink node is reduced which leads to decrease in energy utilization. This paper provides asurvey on various methods which are developed to increase the lifetime of a network. The sensor nodes close to the sink will generally consume more battery power than others; thus, these nodes will rapidly drain out their battery energy and shorten the network lifetime of the WSN. Sink relocation is an effective network lifetime augmentation technique, which avoids consuming an excess of battery energy for a particular gathering of sensor nodes. In this paper, propose a moving methodology called energy-aware sink relocation (EASR) for mobile sinks in WSNs. The proposed system utilizes data identified with the residual battery energy of sensor nodes to adaptively conform the transmission range of sensor nodes and the relocating scheme for the sink.

Energy consumption, energy efficient routing, network lifetime, Wireless sensor network, mobile sink, sink relocation

[1] G. S. Sara and D. Sridharan, “Routingin mobile wireless sensor network: A survey,” Telecommun. Syst., Aug. 2013.
[2] A.A. Somasundara, A. Kansal, D. D. Jea, D. Estrin, and M. B. Srivastavam, “Controllably mobile infrastructure for low energy embedded networks,” IEEE Trans. Mobile Comput., vol. 5, no. 8, pp. 958–973, Aug. 2006.
[3] H. Mousavi, A. Nayyeri, N. Yazani, and C. Lucas, “Energy conserving movement-assisted deployment of ad hoc sensor networks,” IEEE Commun. Lett., vol. 10, no. 4, pp. 269–271, Apr. 2006.
[4] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayiric, “Wireless sensor networks: A survey,” Comput. Netw., vol. 38, no. 4, pp. 393–422, Mar. 2002.
[5] N. Jain and D. P. Agrawal, “Current trends in wireless sensor network design,” Int. J. Distrib. Sensor Netw., vol. 1, no. 1, pp. 101–122, 2005.
[6] D. Tian and N. D. Georganas, “A node scheduling scheme for energy conservation in large wireless sensor networks,” Wireless Commun. Mobile Comput., vol. 3, no. 2, pp. 271–290, Mar. 2003.
[7] X. Hong, M. Gerla, W. Hanbiao, and L. Clare, “Load balanced, energyaware communications for Mars sensor networks,” in Proc. IEEE Aerosp. Conf., vol. 3. May 2002, pp. 1109–1115.
[8] S. C. Huang and R. H. Jan, “Energy-aware, load balanced routing schemes for sensor networks,” in Proc. 10th Int. Conf. Parallel Distrib. Syst., Jul. 2004, pp. 419–425.
[9] R. C. Shah and J. Rabaey, “Energy aware routing for low energy ad hoc sensor networks,” in Proc. IEEE Wireless Commun. Netw. Conf., vol. 1. Mar. 2002, pp. 350–355.
[10] G. L. Wang, G. H. Cao, and T. L. Porta, “Movement-assisted sensor deployment,” in Proc. IEEE Inf. Commun. Conf., Aug. 2004, pp. 2469–2479.
[11] Chu-Fu Wang, Jau-Der Shih, Bo-Han Pan, and Tin-Yu Wu, “A Network Lifetime Enhancement Method for Sink Relocation and Its Analysis in Wireless Sensor Networks”, ieee sensorsjournal, vol. 14, no. 6, june 2014.

Abdul Jawad1 and P. B. Mali, "Survey on Network Lifetime Enhancement Method," International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.63-66, 2016.

Every educational organization from medium size to large size hosts Local Area Network (LAN) equipped with machines of different brands with disparate softwares installed on each of them and connected to different hardware devices. It becomes extremely challenging for the lab technician to keep track of hardware and software configuration details of LAN and their working condition. On many occasions the softwares which are rarely used are installed only on few machines of LAN. Thus, for an end user it becomes difficult to search softwares by virtually attending every machine connected to LAN. In the current paper, the authors have designed and developed a model for obtaining information of all computers connected to a workgroup or a domain controller. The hardware and software information on each machine is queried and stored in a centralized relational database management system. The stored information can be queried using Hardware Query Language (HQL) and Software Query Language (SOQL) designed by the authors. Further, to render the queries more user friendly and close to human language fuzzy text parser is designed and implemented which takes care of synonyms and superfluous words with implied meaning into account. The parse tree is developed and parser is tested for few HQL statements.

Domain Controller, Human Computer Interface, MySQL, Parse Tree, Synonyms, Workgroup.

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Poornima G. Naik and Kavita S.Oza , "Design and Development of Fuzzy Text Parser for Querying Hardware and Software Information in a Local Area Network," International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.67-76, 2016.

Wireless Sensor Networks (WSNs) consist of large number of tiny, battery powered sensor nodes with sensing, computation, and wireless communications technologies. These Nodes sense and send their reports towards a centralized node which is called ―sink or base station. This transmission and reception process consumes lots of energy as compared to data processing, all sensor nodes are processed by limited capacity battery resources which are difficult to replace or recharge due to the unsuitable nature of located nodes. Therefore, to increase the life time of the nodes in WSN, the designing of energy aware routing protocol is vital role in WSN to increase the life time of the sensor nodes. An Energy Efficient Routing is a significant issue in the designing of Wireless Sensor Network (WSN) protocols. This paper presents the list of various type of energy efficient routing protocols have been studied having classified them into proper categories.

WSN; EER; LEACH; PEGASIS and DREAM

[1] Akyildiz LF, Su W, Sankarasubramaniam Y, Cayirci E. ―A survey on sensor networks. IEEE Communications Magazine, 40(8): 102~114.Vol.25, No.4, 2002, 114-124.
[2] S.Ranjitha and D. Prabakar and S. Karthik, "A Study on Security issues in Wireless Sensor Networks", International Journal of Computer Sciences and Engineering, Volume-03, Issue-09, Page No (50-53), Sep -2015,
[3] W. R. Heinzelman, A .Chandrakasan, and H. Balakrishnan., Energy-Efficient Communication Protocol for Wireless Microsensor Networks. IEEE. Published in the Proceedings of the Hawaii International Conference on System Sciences, January 4-7
[4] L. T. Nguyen, X. Defago, R. Beuran, Y. Shinoda., An Energy Efficient Routing Scheme for Mobile Wireless Sensor Networks IEEE ISWCS 2008
[5] H. Abusaimeh, S-H Yang., Dynamic Cluster Head for Lifetime Efficiency in WSN International Journal of Automation and Computing 06(1), February 2009, 48-54, 2009 SPRINGER.
[6] S. Lindsey, C. Raghavendra,"PEGASIS: Power-Efficient Gathering in Sensor Information Systems," IEEE Aerospace Conference Proceedings, 2002, Vol.3. No. 9-16, pp. 1125 1130.
[7] Neha Gupta and Balraj S. Sidhu, "Cost Based Energy Efficient Routing Algorithm for Wireless Body Area Networks", International Journal of Computer Sciences and Engineering, Volume-03, Issue-08, Page No (1-5), Aug -2015.
[8] J. Kulik, W. R. Heinzelman, and H. Balakrishnan, "Negotiation-based protocols for disseminating information in wireless sensor networks," Wireless Networks, Volume: 8, pp. 169-185, 2002.
[9] S. Basagni and et. al. A Distance Routing Effect Algorithm for Mobility (DREAM). In ACM/IEEE Int. Conf. on Mobile Computing and Networking ( MobiCom'98), October 1998.
[10] W. Heinzelman, A. Chandrakasan and H. Balakrishnan “Energyefficient communication protocol for wireless microsensor networks”, in Proceedings of the 33rd Hawaii International Conference on System Sciences , Vol. 2, 2000.
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[12] M. Younis, M. Youssef and K. Arisha, “Energy-Aware Routing in Cluster-Based SensorNetworks”, in the Proceedings of the 10th IEEE/ACM International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS2002), Fort Worth, TX, October 2002.
[13] Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan. “Energy-Efficient Communication Protocol for Wireless Micro sensor Networks”, 33rd Hawaii International Conference on System Sciences, 2000.
[14] Niharika Singh Matharu and Avtar Singh Buttar, "An Efficient Approach for Localization using Trilateration Algorithm based on Received Signal Strength in Wireless Sensor Network", International Journal of Computer Sciences and Engineering, Volume-03, Issue-08, Page No (11-16), Aug -2015

A. Hemalatha and D. Sasirekha, "A Survey on Energy Efficient Routing Protocols in WSN," International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.77-81, 2016.

Today in the age of computers and internet, identity theft, data theft, privacy and confidentiality infringement are some of the major issues faced by organizations as well as individuals. Network and System Security can be provided with the help of firewalls and Intrusion Detection Systems. An Intrusion Detection System (IDS) investigates all incoming and outgoing network traffic to identify malicious behavior that may pose a threat to the confidentiality, integrity or availability of a network or a system. IDS can be signature-detection (misuse) based or anomaly detection based. Misuse detection technique can be used to detect only known attacks whereas anomaly detection can be used to detect novel attacks (Unknown Attacks).This paper focuses on Hybrid Intrusion Detection System which combines both Misuse and Anomaly Detection modules. Various data mining techniques have been developed and implemented to be used with Intrusion Detection Systems. We use K-Means Clustering Algorithm to cluster and classify the incoming data into normal and anomalous connections. Clustering is an unsupervised learning technique for finding patterns in collection of unsupervised data. Prototype testing shows that K-Means algorithm can be successfully used to detect unknown attacks in real live data.

K-Means, Intrusion Detection system, Data Mining, Clustering

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https://web.cs.dal.ca/~zincir/bildiri/pst05-gnm.pdf

Darshan K. Dagly, Rohan V. Gori, Rohan R. Kamath and Deepak H. Sharma, "Hybrid Intrusion Detection System Using K-Means Algorithm," International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.82-85, 2016.

MANET is infrastructure less, decentralized multi hope network where the nodes are randomly to move in any direction, there each node works as a router and host to send packet to each other, there is no any requirement of fixed infrastructure. There are many security threats in MANET. Various types of attacks can be easily triggered in the network. So MANET has a security issue. In this paper we have discussed about Jamming attack in AODV protocol. Due to this attack network performances degrade. Therefore a novel technique has been proposed to detect and isolate jamming attack in the network using monitoring nodes.

MANET, Attacks, Grayhole, Throughput, ZRP, internal attacks

[1] Ali Hamieh, Jalel Ben-Othman, “Detection of Jamming Attacks in Wireless Ad Hoc Networks using Error Distribution”, IEEE, 2009
[2] Ashish K. Maurya, D. S. (Nov,2013). "Simulation based Performance Comparison of AODV, FSR and ZRP Routing Protocolin Manet". IJCA , 23-28.
[3] Awadesh Kumar, P. S. (July,2013). ''Performance Anaysis Of AODV ,CBRP,DSDV and DSR MANET Routing Protocols using NS2 sIMULATION''. I.J Computer Network and Information Security , 45-50.
[4] Meenakshi Jamgade and Vimal Shukla , "Comparative on AODV and DSR under Black Hole Attacks Detection Scheme Using Secure RSA Algorithms in MANET", International Journal of Computer Sciences and Engineering, Volume-04, Issue-02, Page No (145-150), Feb -2016.
[5] Divangna Gupta, R. K. (aug,2014). Simulationof Different Routing Protocols in MANET Using NS2. International journal of Scientific and Research Publication , 1-5.
[6] Bing Wu, Jianmin Chen, Jie Wu, Mihaela Cardei, “A Survey on Attacks and Countermeasures in Mobile Ad Hoc Networks” ,Springer ,2006
[7] Smita Das, "Routing table of DSDV in Mobile Ad-hoc Networking", International Journal of Computer Sciences and Engineering, Volume-03, Issue-10, Page No (48-51), Oct -2015, E-ISSN: 2347-2693.
[8] M Ravi Kumar, D. G. (2013). ''Performance Evaluation of AODV and FSR Routing Protocol in MANET. GJCST , 1-7.
[9] Onkar V.Chandure, A. P. (NOV,2012). Simlation of secure AODVin Gray-hole Attack for Mobile ad-hoc Network. IJAET , 67-75.
[10] Onkar V.Chandure, P. (2011). ''A Mechanism for Recognition & Eradication of Gray Hole Attack using AODV Routing protocol in MANET''. IJCSIT , 2607-2611.
[11] Preeti Gharwar, M. S. (April,2013). "Performance Comparison Of Routing Protocols''. IJARCCE , 1920-1924.
[12] Rutvij H. Jhaveri, D. C. (2012). ''A Novel Gray Hole and Black Hole Attacks in Mobile Ad-Hoc Networks''. International Conference on Advanced Computing& Communicaion Technologies'' , 556-560.
[13] Virali Girdhar and Gaurav Banga, "A Comparative Analysis of Different Movement Models in MANET", International Journal of Computer Sciences and Engineering, Volume-03, Issue-06, Page No (9-13), Jun -2015
[14] S onam Gupta and Rekha Sharma,” A QoS Based Simulation Approach of Zone Routing Protocol in Wireless Ad-hoc Networks ”, International Journal of Computer Sciences and Engineering, Volume 2, issue 7, P.No 24-30, 2014

Harkiranpreet Kaur and Rasneet Kaur, "A Novel Technique to Isolate and Detect Jamming Attack in MANET," International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.86-90, 2016.

Content based image retrieval is a important research area in the field of image processing used for searching and retrieving images from large database. It uses virtual content of images comprises of low level feature extraction such as color, texture, shape & spatial locations to represent images in the database. The system retrieves similar images images when an example image or sketch is presented as input to the system. This paper provides review of the approaches used for extracting low level features, various distance measures for retrieval, various datasets used in CBIR & performance measures. Creation of a content-based image retrieval system implies solving a number of difficult problems, including analysis of low-level image features and construction of feature vectors, multidimensional indexing, design of user interface, and data visualization. Quality of a retrieval system depends, first of all, on the feature vectors used, which describe image content. The paper presents a survey of common feature extraction and representation techniques and metrics of the corresponding feature spaces. Color, texture, and shape features are considered.

Content based image retrieval (CBIR), Image retrieval, and feature extraction

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Shraddha S.Katariya and Ulhas B.Shinde, "Review of Content Based Image Retrieval Using Low Level Features," International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.91-97, 2016.

Language is the prime means of communication used by the individuals. It is the tool everyone uses to express the greater part of ideas and emotions. The usually poor quality of grammar leaves a bad impression on the reader. Therefore, there is a need for grammar checkers. We propose a grammar checking system by means of �Syntax Analysis�. Syntax refers to the arrangement of words in a sentence and their relation with each other. The objective of syntactic analysis is to find syntactic structure of a grammar of a natural language. Natural language processing is an area of computer science and linguistics, concerned with the dealings amongst computers and human languages. It processes the data through lexical analysis, Syntax analysis and Semantic analysis. This paper gives various parsing methods. The algorithm specified in the paper splits the English sentences into parts using POS tagger and then parses these sentences using grammar rules of Natural language.

Natural Language Processing, Context-Free-Grammar, CYK Algorithm, Part-of-Speech Tagging, Syntax Parsing

[1] Earley Parser, https://en.wikipedia.org/wiki/Earley_parser, 27/11/2015
[2] The Earley Parsing Algorithm, http://demo.clab.cs.cmu.edu/fa2014-11711/images/a/a6/Earley-Parsing.pdf , 27/11/2015
[3] Kinoshita, J.; Salvador, L.N.; Menezes, C.E.D.; Silva, W.D.C., "CoGrOO - An OpenOffice Grammar Checker," in Intelligent Systems Design and Applications, 2007. ISDA 2007. Seventh International Conference on , vol., no., pp.525-530, 20-24Oct.2007 doi: 10.1109/ISDA.2007.145
[4] Jaiswal, U.C.; Kumar, R.; Chandra, S., "A Structure Based Computer Grammar to Understand Compound-Complex, Multiple-Compound and Multiple-Complex English Sentences," in Advances in Computing, Control, & Telecommunication Technologies, 2009. ACT `09. International Conference on , vol., no., pp.746-751, 28-29Dec.2009 doi:10.1109/ACT.2009.189
[5] Lee, J.; Seneff, S., "An analysis of grammatical errors in non-native speech in English," in Spoken Language Technology Workshop, 2008. SLT 2008. IEEE , vol.,no.,pp.89-92,15-19Dec.2008 doi:10.1109/SLT.2008.4777847
[6] Brian Roark (Oregon Health & Science University), Kristy Hollingshead (University of Maryland), Nathan Bodenstab (Oregon Health & Science University), �Finite-State Chart Constraints for Reduced Complexity Context-Free Parsing Pipelines�, in Journal: Computational Linguistics, Volume 38 Issue 4, December 2012, Pages 719-753 , doi:10.1162/COLI_a_00109
[7] The CYK Algorithm, https://www.cs.wmich.edu/~elise/courses/cs6800/CYK-Algorithm.ppt, 16/11/2015
[8] Earley parser.pdf - Computer Science and Engineering, www.cse.unt.edu/~tarau/teaching/NLP/Earley%20parser.pdf, 16/12/2015
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(ICESC), 2014 International Conference on, Nagpur, 2014, pp. 376-381. doi: 10.1109/ICESC.2014.71

Pratik Ghosalkar, Sarvesh Malagi, Vatsal Nagda, Yash Mehta, Pallavi Kulkarni, "English Grammar Checker," International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.98-100, 2016.

Cloud Computing has evolved as an effective solution for client and business application advancement. It deals with large number of different types of resources. So in order to deliver these cloud facilities and services effectively, testing of the cloud based services turns out to be an essential step before its usage by the clients. For testing cloud applications there are various tools and methods. In this paper we analyze the use of various performance testing tools used in cloud environment and the correlation of the same for testing of cloud applications. Also we had gathered the expert reviews about the tools with the assistance of a review on survey monkey website over a time of one week. A sum of 20 working professionals had demonstrated enthusiasm for our overview that incorporates cloud professionals working in different Information Technology sector. The outcomes depict the tools which are most widely used by the cloud professionals.

Cloud Computing; Cloud Testing; Software Testing; Performance Testing; Cloud Application; Benchmarks

[1] Nachiyappan, S., & Justus, S., "Cloud Testing Tools and its Challenges: A Comparative Study", Procedia Computer Science, 50, 2015, 482-489.
[2] Reshma D. Abhang and B. B. Gite,"Testing Methods and Tools in a Cloud Computing Environment", International Journal of Engineering Research & Technology, Volume-03, Issue-11 November 2014.
[3] Kiran prajapati, Jaytrilok choudhary, "A Survey on Cloud Computing with different Encryption Techniques to Secure Cloud Data", International Journal of Computer Sciences and Engineering, Volume-03, Issue-05, Page No (1-6), May -2015
[4] Ali Mohsenzadeh, "Cloud Computing Testing Evaluation", International Journal of Computational Engineering & Management, Volume-16, Issue-06, November 2013.
[5] Bai, X., Li, M., Chen, B., Tsai, W., & Gao, J., "Cloud testing tools", Proceedings of 2011 IEEE 6th International Symposium on Service Oriented System (SOSE).
[6] Brataas, G., Stav, E., Lehrig, S., Becker, S., Kopčak, G., & Huljenic, D., "CloudScale", Proceedings of the ACM/SPEC International Conference on International Conference on Performance Engineering - ICPE 2013.
[7] T. Kavitha and P. Nageswara Rao , "Loss Less and Privacy Preserved Data Retrieval in Cloud Environment Using TRSE", International Journal of Computer Sciences and Engineering, Volume-03, Issue-07, Page No (81-84), Jul -2015
[8] Chen, X., & Knottenbelt, W., "A Performance Tree-based Monitoring Platform for Clouds", Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering - ICPE 2015.
[9] Franceschelli, D., Ardagna, D., Ciavotta, M., & Nitto, E. D., "Space4Cloud", Proceedings of the 2013 International Workshop on Multi-cloud Applications and Federated Clouds - MultiCloud 2013.
[10] Gao, J., Bai, X., Tsai, W. T., & Uehara, T., "SaaS Testing on Clouds - Issues, Challenges and Needs", IEEE Seventh International Symposium on Service-Oriented System Engineering, 2013.
[11] Lynch, M., Cerqueus, T., & Thorpe, C.,"Testing a cloud application: IBM SmartCloud inotes: Methodologies and tools", Proceedings of the 2013 International Workshop on Testing the Cloud - TTC 2013.
[12] Mao, B., Jiang, H., Wu, S., & Tian, L., "Leveraging data deduplication to improve the performance of primary storage systems in the cloud", Proceedings of the 4th Annual Symposium on Cloud Computing - SOCC 2013.
[13] Moyo, T., & Bhogal, J. (2014), "Investigating Security Issues in Cloud Computing", Eighth International Conference on Complex, Intelligent and Software Intensive Systems, 2014.
[14] P., Chana, I., & Rana, A.,"Empirical evaluation of cloud-based testing techniques", SIGSOFT Softw. Eng. Notes ACM SIGSOFT

Anuj Pandit, Pritam Shaha, Sanket Bhambure, and Prof. Manjula R, "A Study Analysis And Survey of Different Performance Testing Tools Used For Cloud Applications," International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.101-105, 2016.