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Recommender systems plays a significant role, by providing personalized information to users over the internet. With the evolution of the internet, the recommender systems too have evolved from being based on simple demographics, user and item information, into complex hybrid models capable of providing an effective real-time recommendation on a per-user basis. This works provides an overview of traditional recommender system approaches, their taxonomy and discusses the various hybridization techniques used for creating complex models that provide hyper-personalized recommendations. A detailed discussion of the research challenges and how they impact the performance of the various recommender models have been presented as a solution to the existing issues in recommendation systems. Metrics for evaluation and the need for diversity and novelty in recommender systems have also been discussed. Future research directions concerning mobile and IoT based, context-aware recommender systems and the effectiveness of Deep Learning models and how Transfer Learning could address the major drawbacks of recommender systems have also been discussed.

Recommender Systems; Hybrid Filtering; Collaborative Filtering; Content-Based Recommendation; Context-Aware Recommender; Demographic Filtering

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K.Reka, T.N.Ravi, "Hybrid Recommender Systems: Process, Challenges, Approaches and Metrics," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1024-1033, 2018.

Our society has many challenges related to the environment, one of them is air pollution. There are many causes to increase the air pollution percentage in different area some of them are transportation, industrialization and constructions. It creates unhealthy atmosphere. Many people are suffering from many deceases invoked from the pollution. So we planned to design an air pollution monitoring system which indicates the polluted air amount in the environment. It will help to identify the polluted areas.

Air quality, Arduino, IOT and Gas sensors

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Hansa Rajput, Snehlata Barde, "An Idea to design a system to detect Air pollution in different area," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1034-1036, 2018.

With the increasing use of Internet and its services leads to the generation where availability of data has become boundless. The abundant flow of data due to the advent of IoTs is not new and for storing such huge amount of data paved the way for the technology like cloud computing. But with cloud computing still some issues need to be resolved such as high latency, network bandwidth, network congestion, security and others that cannot be compromised in case of real time applications. ‘Fog computing’ introduces a new dimension to the way cloud works as it focuses on the provisioning of resources and services at the edge of the network that means closer to end devices and hence there is less delay in processing client’s request in distributed environment. So in this perspective it is heading the way to cloud computing paradigm. Its evolution is not for replacing cloud computing but to complement in such a manner that its potential can be realized and utilized in an effective manner. This paper highlights the fog computing technology concept and gives an insight details in terms of its characteristics, and the related work done in prospect of challenges.

Fog computing, Cloud computing, Edge computing, IoT, Programming model

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A. Ahuja, "Fog Computing: Overview and Research Challenges," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1039-1044, 2018.

Buying and selling of things are a major part of human’s since early ages , but with the development of the online market the trade got shifted from usual market to online for ease of everyone .Internet (www) has been a resource to get the user’s review about the particular thing he had purchased. There are 2.4 billion active online users, who write and read online and use internet around us [1]. It will also help the companies to know what the problem the customers are facing in their use of the product. This will help the company to make better product and will surely help the customer to buy a product will large positive value [2]. With the help of the given system we classify the reviews. The paper will try to compare the various technique used to find out the opinion of the users .The proposed System will use the general algorithms of AI to find out the answer to this problem which are described in details in this paper.

Sentiment Analysis, Naïve Bayes, Random Forest

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[7] Opinion Mining and Sentiment Analysis Bo Pang and Lillian Lee Yahoo! Research, 701 First Avenue, Sunnyvale, CA 94089, USA, Computer Science Department, Cornell University, Ithaca, NY 14853, USA, llee@cs.cornell.edu
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Ishan Arora, Gagandeep Singh, Lokesh Kumar, "Online Product Review analysis for Sentiments," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1045-1048, 2018.

Cryptography is the best piece of the establishment of correspondence security and PC security. Regardless, there are a couple of torpid defects in different built up cryptography advances generally cryptography, for instance, RSA and DES computations—which are broken by some attack programs. DNA cryptography and learning science was considered a while later examination inside the field of DNA preparing field by Adleman. It has transformed into the forefront of all inclusive research on cryptography. Cryptography relies upon natural issues. In this theory, a DNA structure not simply has predictable enrolling power as a contemporary framework, in any case, it has productivity and capacity customary PCs can`t coordinate. Utilizing DNA in connection with cryptography is another and energizing investigation bearing. Shockingly, it needs a great deal of assets, it has cutting edge research facility necessities and a few computational constraints. Along these lines, the productive utilization of DNA cryptography is as yet troublesome from a functional perspective. This paper talks about DNA cryptosystem ideas in view of the work of art and present day stance and overviews DNA cryptosystem connected to picture Cryptography field.

Cryptography, DNA, DNA Sequence, Encryption, Security

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[15] Kane, Amadou Moctar. "How DNA Cryptography can help whistleblowers and refugees." arXiv preprint arXiv:1606.06644 (2016).
[16] Hossain, Emtious Md Sazzad, Kazi Md Rokibul Alam, Md Rafiul Biswas, and Yasuhiko Morimoto. "A DNA cryptographic technique based on dynamic DNA sequence table." In Computer and Information Technology (ICCIT), 2016 19th International Conference on, pp. 270-275. IEEE, 2016.
[17] Kaur, Sarbjeet, and Sheenam Malhotra. "A Review on Image Encryption Using DNA Based Cryptography Techniques." International Journal 4, no. 3 (2016).
[18] Norouzi, Benyamin, and Sattar Mirzakuchaki. "Breaking a novel image encryption scheme based on an improper fractional order chaotic system." Multimedia Tools and Applications 76, no. 2 (2017): 1817-1826.
[19] Krishnamoorthy, Kuppusamy, and Mahalakshmi Jeyabalu. "A New Image Encryption Method Based on Improved Cipher Block Chaining with Optimization Technique." In Advanced Image Processing Techniques and Applications, pp. 133-149. IGI Global, 2017.
[20] Niu, Ying, Xuncai Zhang, and Feng Han. "Image Encryption Algorithm Based on Hyperchaotic Maps and Nucleotide Sequences Database." Computational Intelligence and Neuroscience 2017 (2017).

S. Verma, S. Indora, "DNA Sequencing Based Image Encryption Methods: A Survey," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1049-1054, 2018.

Software Testing is an essential and important phase of SDLC. The quality and acceptance of any software highly depends on the success of software testing phase. The successful completion of testing phase also ensures that the produced software is of good quality. In order to achieve high quality product lots of Process Maturity Models have been developed and CMMI is one of the most popular among them. The organizations at the initial level of CMMI (also non-CMMI compliance organizations) neither implement any of the standard processes for software product development nor they use any software testing strategies, hence, the quality of the product produced by them is always susceptible and imposes a great risk over its acceptance as well as on their survival. The main driving force behind this paper is to study the implications of software testing processes (partially or at introductory level) over the quality of software produced by the organizations at initial level.

Software Testing Strategies, CMMI, Maturity Levels, Capability Levels, Process Areas

[1] “Capability Maturity Model® Integration (CMMI®) Overview”, Carnegie Mellon University/ Software Engineering Institute, pp: 393-411, 2005.
[2] “CMMI® for Development, Version 1.3”, Technical Report, CMMI Product Team, Carnegie Mellon University/ Software Engineering Institute, Nov-2010.
[3] R. S. Pressman, “Software Engineering: A Practitioner`s Approach”, Fourth Edition, McGraw-Hill Publications, pp: 448-512, 1997.
[4] A. Luqman, “Implementation And Analysis of CMMI`s Configuration Management Process Area; Applicable to "Defined" Level – 3”, International Conference of Information and Communication Technology, Karachi, Pakistan, IEEE Conference Publications, pp: 296-301, 27-28 Aug’2005.
[5] P. Monteiro; R. J. Machado, R. Kazman, “Inception of Software Validation and Verification Practices within CMMI Level 2”, ICSEA `09. Fourth International Conference on Software Engineering Advances, Porto, Portugal, IEEE Conference Publications, pp: 536-541, Conference of Proceedings published by IEEE Computer Society, 20-25 Sep’2009.
[6] R. Dadhich, U. Chauhan, “Integrating CMMI Maturity Level-3 in Traditional Software Development Process”, International Journal of Software Engineering & Applications (IJSEA), Vol.3, No.1, pp: 17-26, January 2012.
[7] S. H. Trivedi, “Software Testing Techniques”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 10, pp: 433-439, October 2012.
[8] R. K. Chauhan, I. Singh, “Latest Research and Development on Software Testing Techniques and Tools”, INPRESSCO, International Journal of Current Engineering and Technology, Vol.4, No.4, pp: 2386-2372, Aug 2014.
[9] M. Staples, M. Niazi, R. Jeffery, A. Abrahams, P. Byatt, R. Murphy, “An exploratory study of why organizations do not adopt CMMI”, Journal of Systems and Software, Vol. 80, No.6, pp: 883-895, June’2007.
[10] S. R. Durugkar, V. Surwase, “Software Validation and Verification Practices in CMMI levels”, BIOINFO Soft Computing, Vol. 1, Issue 1, pp: 01-04, 2011.
[11] D. Singh, “Software Testing using CMMI Level 5”, International Journal of Computer Science Trends and Technology, pp: 233-242, Mar-Apr 2016.
[12] N. Chauhan, “Software Testing: Principles and Practices”, Second Edition, Oxford University Press, India, Dec’2016, ISBN-13: 978-0198061847.
[13] R. Chopra, “Software Testing (A Practical Approach)”, Third Edition, S.K. Kataria & Sons, India, 2010, ISBN: 9788189757908, 8189757903.
[14] S. Jat, P. Sharma, “Analysis of Different Software Testing Techniques”, International Journal of Scientific Research in Computer Science and Engineering (IJSRCSE), Vol.5, Issue.2, pp.77-80, April ‘2017.

R. Sharma, R. Dadhich, "Implications of Software Testing Strategies at Initial Level of CMMI: An Analysis," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1055-1061, 2018.

Achieving better phases of security in transferring an image over LAN or internet and performance of enigma is depends on its efficiency based on time taken and the way it generates different graphs from a pixel. The most widely used algorithms are RSA, public key algorithm and other such algorithms does not provide full security to the cipher text, RSA is not going to assure the enigma while transforming the images. A better approach is to use Apex magic total Labeling (AMTL) of complete graph. It increases the efficiency by adding more extra security to the enigma systems. This method provides more security due to its difficulty in encryption in AMTL formation that cannot be easily found. This proposed research work provides an additional level of security to public key algorithms such as RSA, DH algorithm, etc. this approach is experimented in simulated systems like MATLAB.

RSA,bipartitegraph,Apexmagicsquare,Enigma,SAMTL

[1] Krishnappa H.K., Kishore Kottapalli, V.Ch. Venkaiah, “On Apex Magic Total Labeling of Complete graphs”, AKCE Journal of Graphs and Combin, 6, No.1(2009)pp.143-154.
[2] J.A. MacDougall, M.Miller, K.A.Sugeng, “Super Magic Total Labelings of graphs”, Proceeding of the Fifteenth Australian workshop on Combinatorial Algorithms 2004, Balina, NSW, (2004), 222-229.
[3] K.A.Sugeng, M.Miller, M.Baca and Slamin, “Super Edge Anti Magic Total Labeling of Catterpillars”, Lecture note in Computer Science (IJCGGT-2003), Vol.3330, (2005)
[4] K.A.Sugeng and W.Xie, “Construction of Super edge magic total graphs”, Proceedings of 16th Australian Workshop on Combinatorial Algorithms 2005, Ballarat, Australia, (2005), 303-310.
[5] Y. H. Yu, C. C. Chang and Y. C. Hu, ―Hiding Secret Data in Images via Predictive Coding,‖ Pattern Recognition, vol. 38, pp. 691-705, 2005.
[6] Nameer N. EL-Emam, ―”Hiding a Large Amount of Data with High Security Using Enigma Algorithm”, Journal of Computer Science, vol. 3 (4), pp. 223-232, 2007.
[7] S.G.K.D.N. Samaratunge, ―”New Enigma Technique for Palette Based Images”,In Second International Conference on Industrial and Information Systems, pp. 335-340, Aug. 8 – 11, 2007.
[8] J. He, S. Tang and T. Wu, ―”An Adaptive Image Enigma Based on Depth-Varying Embedding”, In Congress on Image and Signal Processing, vol. 5, pp. 660-663, 27-30 May 2008.
[9] Krishnappa.H.K., N.K.Srinath and P.Ramakanth Kumar, “Vertex Magic Total Labeling of Complete graphs”, IJCMSA., Vol 4, No 1-2 (2010), 157-169.
[10] S Roy and D.G. Akka, “On complementary edge magic of certain graphs”, American Journal of Mathematics and Statistics 2012,2(3):22-26.
[11] R.Rajeshwari, R.Parameswari,”Total Magic Cordial Labeling of Star related grapgh”, 2017 international conference on intelligent computing and control (I2C2).
[12] Hao Lu; Mahantesh Halappanavar; Daniel Chavarria-Miranda; Assefaw H,” Algorithms for Balanced Graph Colorings with Application in Parallel Computing”.2017 IEEE Transaction on Parallel and Distributed System (volume:28).
[13] A Gupta, E Sharma, N Sachan, N Tiwari, “ Door Lock System Through Face recognition using MATLAB”, International Journal of Scientific Research in Computer Science and Engineering-2014.
[14] M Bandyopadhya, S Chattopadhaya, A Das, “ Emphasis on Genetic Algorithm over Different PLD Tuning Methods using MATAB”, International Journal of Scientific Research in Computer Science and Engineering-2013.

C.S. Madhu, H.K. Krishnappa, K.H. Sandeep, S. Dinesh, "Apex Magic Square Labeling for Complete Bipartite Graph and their application using Enigma," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1062-1066, 2018.

String matching algorithms are widely used in computer science fields for information retrieval, intrusion detection, music retrieval, database queries, language syntax checker, bioinformatics, DNA sequence matching and etc. The most common and well-known use of string matching algorithms is for bioinformatics. In bioinformatics the DNA sequences of the normal human being and matched with the DNA sequence of a person having viruses or any kind disease. The pattern of any disease or virus is matched with the normal DNA genome sequence. If the pattern is found in the sequence which is in the form of string it is considered that the human being or patient is having the tested disease. Thus the pattern is matched with the large amount of DNA sequence which is sometimes very complex and not easy to retrieve. Thus to get the result or matched pattern in the less time with more accuracy the algorithms such as Knuth-Morris-Pratt(KMP), Boyer-Moore, Brute Force, Rabin-Karp and other algorithms are used. This paper presents five string matching algorithms from which four are exact matching algorithms and one is approximate string matching algorithm (Edit Distance). The above listed algorithms complexity will be compared using the DNA dataset to find the appropriate algorithm with high quality time and accuracy.

String Matching Algorithm, DNA sequence

[1] NYO ME TUN, THIN MYA MYA SWE, “Comparison of Three Pattern Matching Algorithms using DNA Sequences”, IJSETR, Vol.3, Issue.35, pp.6916-6920, 2014.
[2] https://en.wikipedia.org/wiki/DNA
[3] Robert Sedgewick, Kevin Wayne, “Algorithms”, Fourth Edition, Addison-Wesley,Pearson Edition, India, pp. 760-776, 2011.
[4] Thomas Cormen,Charles E. Leiserson,Ronald L. Rivest,Clifford Stein, “Introduction to Algorithms”, McGraw-Hill Publication, India, pp.909-926, 2001.
[5] Raju Bhukya, DVLN Somayajulu, “Exact Multiple Pattern Matching Algorithm using DNA Sequence and Pattern Pair”, International Journal of Computer Applications, Number 8,Article 6, pp.32-38, 2011.
[6] Petteri Jokinen, Jorma Tarhio and Esko Ukkonen, “A Comparison of Approximate String Matching Algorithms”, Software-Practice and Experience, Vol.1(1), pp.1-4, 1988.
[7] http://ccg.vitalit.ch/cgibin/htpselex/show?htpselex&tf=NF1_1&clone
[8] https://archive.ics.uci.edu/ml/machine-learning-databases/molecular-biology/promoter-gene-sequences/promoters.data

Pooja Manisha Rahate, M. B. Chandak, "Comparative Study of String Matching Algorithms for DNA dataset," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1067-1074, 2018.

Cloud computing provides on demand accessibility of resources with transparency.The cloud composed of serveral datacenters and customers may acess the computational resources over a network provisioned by cloud service provider. The challenge in cloud environment is to meeting customers demand succesfully by allocating of computational resources.Scheduling is an important criteria that effects performance of systems.Round robin is a preemptive scheduling policy that effects the performance of systems as it provides fairness in scheduling tasks in cloud environment.The current work is based on the time varying time quatum strategy that deals with maximum cpu utilization and minimizes the waiting time,Tunraronud time,Average turn around time ,context switching and provides better performance.

Round robin,scheduling,time quantum,cloud computing

[1] Ahmed Alsheikhyl, Reda Ammar1, Raafat Elfouly , “An Improved Dynamic Round Robin Scheduling Algorithm Based on a Variant Quantum Time” , IEEE 2015.
[2] Jayanti Khatri, “An Improved Dynamic Round Robin CPU Scheduling Algorithm Based on Variant Time Quantum” ,IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 18, Issue 6, Ver. IV (Nov.-Dec. 2016), PP 35-40.
[3] Mohd Abdul Ahad , “ Modifying Round Robin Algorithm for Process Scheduling using Dynamic Quantum Precision “ ,Special Issue of International Journal of Computer Applications (0975 – 8887) on Issues and Challenges in Networking, Intelligence and Computing Technologies – ICNICT 2012, November 2012.
[4] Raman , Dr.Pardeep Kumar Mittal, “An Efficient Dynamic Round Robin CPU Scheduling Algorithm” , International Journal of Advanced Research in Computer Science and Software Engineering , Volume 4, Issue 5, May 2014 .
[5] Muhammad Umar Farooq, Aamna Shakoor, Abu Bakar Siddique , “An Efficient Dynamic Round Robin Algorithm for CPU scheduling”, International Conference on Communication, Computing and Digital System ,2017
[6] Prof. Dipali V. Patel , “A Best Possible Time Quantum for Advanced Round Robin With Shortest Job First Scheduling Algorithm”, IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 03, 2015
[7] P.Surendra Varma , “A Finest Time quantum for improving shortest remaining burst round robin (srbrr) algorithm” , Journal of Global Research in Computer Science, Volume 4, No. 3, March 2013.
[8] Priyanka Sangwan, Manmohan Sharma, Anil Kumar, “Improved Round Robin Scheduling in Cloud Computing” , Advances in Computational Sciences and Technology ISSN 0973-6107 Volume 10, Number 4 (2017) pp. 639-644 © Research India Publications http://www.ripublication.com .
[9] Manish kumar Mishra, “Improved Round Robin CPU Scheduling Algorithm”, Journal of Global Research in computer science, ISSN - 2229-371X, vol. 3,No. 6, June 2012.
[10] Rami J Matarneh, “Self- Adjustment Time Quantum in Round Robin Algorithms Depending on Burst Time of the Now Running Processes”, American Journal of Applied Sciences, ISSN 1546-92396, (10):1831-1837, 2009 .
[11] Saroj Hiranwal, “ Adaptive Round Robin Scheduling using shortest Burst Approach Based on smart time slice ”, International Journal of Data Engineering(IJDE), volume2, Issue 3,2 011 .
[12] H.S. Behera, “Weighted Mean Priority Based scheduling for Interactive systems”, Journal of global Research in computer science, ISSN-2229-371X, volume 2, No.5, May 2011 .
[13] Lalit Kishor & Dinesh Goyal, “Time Quantum Based Improved Scheduling Algorithms”, International Journal of Advanced Research in Computer science and Software Engineering, ISSN: 2277-128X, Volume 3, Issue 4, April 2013 .
[14] H.S.Behera, “ Enhancing the CPU performance using a modified mean-deviation round robin scheduling algorithm for real time systems”, Journal of global Research in computer science, ISSN-2229-371X, volume 3,No. 3, March 2012,
[15] Aashna Bisht, “ Enhanced Round Robin Algorithm for process scheduling using varying quantum precision”, IRAJ International Conference-proceedings of ICRIEST- AICEEMCS,29 th Dec 2013,pune India. ISBN: 978- 93-82702-50-4
[16] Rakash Mohanty & Manas Das, “ Design and performance Evaluation of A new proposed fittest Job First Dynamic Round Robin Scheduling Algorithms”, International journal of computer information systems, ISSN: 2229-5208, vol. 2, No. 2, Feb 2011. [
[17] Debashree Nayak& Sanjeev Kumar Malla, “ Improved Round Robin Scheduling using Dynamic time quantum”, International Journal of computer Applications, volume 38, No. 5, January 2012 Shyam et al., International Journal of Advanced Research in Computer Science and Software Engineering 4(7), July – 2014.
[18] Ishwari Singh Rajput,Deepa Gupta, “A Priority based round robin CPU Scheduling Algorithms for real time systems”, International journal of Innovations in Engineering and Technology, ISSN:2319-1058, Vol. 1 ISSUE 3 ,Oct 2012.
[19] H.S. Behera & Brajendra Kumar Swain, “ A New proposed precedence based Round Robin with dynamic time quantum Scheduling algorithm for soft real time systems”, International Journal of advanced Research in computer science and software Engineering, ISSN:2277- 128X, Vol. 2, ISSUE 6, June 2012.
[20] Brajendra Kumar Swain,H.S Behera and Anmol Kumar Parida, “A new proposed round robin with highest response ratio next scheduling algorithm for soft real time system”, International Journal of Engineering and Advanced Technology, ISSN: 2249-8958, Vol. - 1,ISSUE-3, Feb 2012 .
[21] Taskeen Zaidi, and Rampratap, “Modeling for Fault Tolerance in Cloud Computing Environment.”
Journal of Computer Sciences and Applications, vol. 4, no. 1 (2016): 9-13. doi: 10.12691/jcsa-4-1-2
[22] Abbas Noon, Ali Kalakech and Seifedine Kadry, “ A new Round Robin based scheduling algorithm for operating system: Dynamic quantum using the mean average”, International Journal of computer science, ISSN: 1694-0814, Vol. 8,ISSUE 3, No. 1, May 2011
[23] Rakesh kumar Yadav, Abhishck K Mishra ,Navin Prakash and Himanshu Sharma, “ An Improved round robin scheduling algorithm for CPU scheduling”, International Journal of computer science and Engineering, ISSN: 0975-3397, Vol. 02, No. 04, 2010 , 1064-1066
[24] Ali Jbaeer Dawood, “Improved Efficiency of Round Robin Scheduling Using Ascending Quantum and Minumium-Maxumum Burst Time”, Journal of university of anbar for pure science, ISSN: 1991-8941, Vol. 6, No. 2, 2012.
[25] “A.S. Tanenbaum, 2008” Modern Operating Systems, Third Edition, Printice Hall ,ISBN : 13:9780136006633,PP: 1104,
[26] Silberschatz, A., P.B. Galyin and G.Gange, 2004,“ Operating System Concepts”. 7th Edn, John Wiley and Sons, USA, ISBN: 13:978-0471694663, PP: 944.
[27] William Stalling, 2006, “Operating system”, 5th Edition Person Education , ISBN :81311703045,
[28] Dhamdhere ,Systems Programming and Operating Systems SECOND EDITOR.
[29] R. Buyya, C. S. Yeo, and S. Venugopal. Market- oriented cloud computing: Vision, hype, and reality for delivering IT services as computing utilities. In Proceedings of the 10th IEEE International Conference on High Performance Computing and Communications, 2008.
[30] Saurabh Kumar Garg and Rajkumar Buyya, NetworkCloudSim: Modelling Parallel Applications in Cloud Simulations, Proceedings of the 4th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2011, IEEE CS Press, USA), Melbourne, Australia, December 5-7, 2011.
[31] Rodrigo N. Calheiros, Rajiv Ranjan, Anton Beloglazov, Cesar A. F. De Rose, and Rajkumar Buyya, CloudSim: A Toolkit for Modeling and Simulation of Cloud Computing Environments and Evaluation of Resource Provisioning Algorithms, Software: Practice and Experience (SPE), Volume 41, Number 1, Pages: 23-50, ISSN: 0038-0644, Wiley Press, New York, USA, January, 2011. (Preferred reference for CloudSim)
[32] Bhathiya Wickremasinghe, Rodrigo N. Calheiros, Rajkumar Buyya, CloudAnalyst: A CloudSim-based Visual Modeller for Analysing Cloud Computing Environments and Applications, Proceedings of the 24th International Conference on Advanced Information Networking and Applications (AINA 2010), Perth, Australia, April 20-23, 2010.
[33] Rajkumar Buyya, Rajiv Ranjan and Rodrigo N. Calheiros, Modeling and Simulation of Scalable Cloud Computing Environments and the CloudSim Toolkit: Challenges and Opportunities, Proceedings of the 7th High Performance Computing and Simulation Conference (HPCS 2009, ISBN: 978-1-4244-4907-1, IEEE Press, New York, USA), Leipzig, Germany, June 21-24, 2009.

T. Zaidi, S. Shukla, "Variable time Quantum Based Round Robin Policy for Cloud Computing Environment," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1075-1081, 2018.

There is a growing trend of applications that should handle big data. However, analyzing big data is a very challenging problem today. For such applications, the MapReduce framework has recently attracted a lot of attention. Google`s MapReduce or its open-source equivalent Hadoop is a powerful tool for building such applications. In this paper, we will discuss the MapReduce framework based on Hadoop, and how to design efficient MapReduce algorithms and present the state-of-the-art in MapReduce algorithms for data mining, machine learning, query processing, data analysis and similarity joins. The intended audience of this tutorial is professionals who plan to design and develop MapReduce algorithms and researchers who aware of the state-of-the-art in MapReduce algorithms available today for big data analysis.

Map Reduce Framework, Hadoop, Data Mining, Query Processing, Data Analysis

[1]. Ghazal, T. Rabl, M. Hu, F. Raab, M. Poess, A. Crolotte, H. A. Jacobsen, 2013 "BigBench: Towards an industry standard benchmark for big data analytics", Proc. ACM SIGCOMM USA, pp. 1197-1208.
[2]. D. Sun, G. Zhang, S. Yang, W. Zheng, S. U. Khan, K. Li, 2015 "Re-Stream: Real-time and energy-efficient resource scheduling in big data stream computing environments", Information Sciences., vol. 319, pp. 92-112.
[3]. Hideya Nakanishi; Masaki Ohsuna; Mamoru Kojima; Setsuo Imazu; Miki, 2016, “Real-Time Data Streaming and Storing Structure for the LHD’s Fusion Plasma Experiments”, ISSN: 1558-1578, Volume: 63, Issue: 1, pp: 222 – 227.
[4]. Jeongkyu Hong ; Soontae Kim, 2017, “Smart ECC Allocation Cache Utilizing Cache Data Space” ISSN: 0018-9340, Volume 66, Issue 2, pp: 368 – 374.
[5]. Miao Wang ; Guiling Wang ; Yujun Zhang ; Zhongcheng Li, 2016, “A High-reliability Multi-faceted Reputation Evaluation Mechanism for Online Services”, ISSN: 1939-1374, Volume PP, Issue: 99, pp 1-1.
[6]. Neha Bharill ; Aruna Tiwari ; Aayushi Malviya, 2016, “Fuzzy Based Scalable Clustering Algorithms for Handling Big Data Using Apache Spark”, ISSN: 2332-7790, Volume: 2, Issue 4, pp: 339-352.
[7]. Neng Zhang ; Jian Wang ; Yutao Ma, 2017, 7. “Mining Domain Knowledge on Service Goals From Textual Service Descriptions”, ISSN: 1939-1374, Volume PP Issue 99, pp:1-1.
[8]. Yuji Ishizuka; Wuhui Chen; Incheon Paik, 2016, “Workflow Transformation for Real-Time Big Data Processing”, ISSN: 978-1-5090-2622-7, Big Data (BigData Congress), 2016 IEEE International Congress on Wuhui Chen; Incheon Paik; Zhenni Li, 2017,
[9]. “Cost-Aware Streaming Workflow Allocation on Geo-Distributed Data Centers” ISSN: 0018-9340, Volume 66, Issue: 2, pp: 256-271.

Bhavani Buthukuri, M E Purushoththaman, "A Novel Location Awareing Mapreducing Techniques Using Big Data Applications," International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.1082-1091, 2018.