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Cloud services are widely used around the world since the cloud services are playing a key role in many industries such as Supply Chain, Networking, Storages, etc. Different task scheduling algorithms have been used to handle cloud service applications, but none of the algorithms contain all the constraints such as load balancing, makespan time, cost and the time of execution. The scheduling technique considers well when it efficiently performs utilizing resources of the cloud. The heuristic scheduling algorithm provides the optimal solution, thereby increasing the efficiency of the overall system. Heuristic methods such as Genetic Algorithm (GA) are deals with the natural selection of solutions from the all possible solutions. Genetic algorithms schedule the cloud tasks according to the computational power of the system, memory resources and requirements of the tasks. The aim of this survey is to propose a technique to minimize the completion time and cost of tasks and maximize resource utilization using Genetic Algorithm (GA). This work also presents the comparative analysis of different task scheduled applications proposed by the researchers during the last five years.

Cloud Computing, Scheduling, Genetic Algorithm, Optimization, Scheduling Algorithms

[1] Sourabh Budhiraja, Dheerendra Sing, “Task Scheduling using Genetic Algorithm in Cloud Computing Environment: A Review”, International Journal of Info. Tech. and Knowledge Management, Vol.8, No.1, pp.46-49, 2014.
[2] Tarun Goyal and Aakanksha Agrawal, “Host Scheduling Algorithm Using Genetic Algorithm in Cloud Computing Environment”, International Journal of Research in Engineering & Technology, Vol.1, Issue.1, pp.7-12, 2013.
[3] Simply, Jagandeep Sidhu, “Different Scheduling Algorithms in Different Cloud Environment”, International Journal of Advanced Research in Computer and Communication Engineering, Vol.3, Issue.9, pp.8003-8006, 2014.
[4] Hongyan Cui, Xiaofei Liu, Tao Yu, Honggang Zhang, Yajun Fang, and Zhongguo Xia, “Cloud Service Scheduling Algorithm Research and Optimization”, Security and Communication Networks, Hindawi, Vol.2017, Article ID 2503153, pp.1-7, 2017.
[5] Durairaj, M and Kannan, P, “Improvised Genetic Approach for an Effective Resource Allocation in Cloud Infrastructure”, International Journal of Computer Science and Information Technologies, Vol.6, Issue.4, pp.4037-4046, 2015.
[6] R. Durga, Lakshmi, N. Srinivasu " A Review and Analysis of Task Scheduling Algorithms in Different Cloud Computing Environments " International Journal of Computer Science and Mobile Computing, Vol.4, Issue.12, pp.235–241, 2015.
[7] S. Ravichandran, E.R. Naganathan, “Dynamic Scheduling of Data Using Genetic Algorithm in Cloud Computing”, International Journal of Computing Algorithm, Vol.2, Issue.1, pp.127-133, 2013.
[8] M. Padmavathi, Shaik. Mahboob Basha, Srinivas Pothapragada, “A Survey on Scheduling Algorithms in Cloud Computing”, IOSR Journal of Computer Engineering, Vol.16, Issue.4, pp.27-32, 2014.
[9] Safwat A. Hamad, Fatma A. Asmara “Genetic-Based Task Scheduling Algorithm in Cloud Computing Environment " International Journal of Advanced Computer Science and Applications, Vol.7, No.4, pp. 550-556, 2016.
[10] A. Kaleeswaran, V. Ramasamy, P. Vivekanandan, “Dynamic Scheduling of Data using Genetic Algorithm in Cloud Computing”, International Journal of Advances in Engineering & Technology, Vol.5, Issue.2, pp.327-334, 2013.
[11] R. Durga Lakshmi, N. Srinivasu, “A Dynamic Approach to Task Scheduling in Cloud Computing using Genetic Algorithm”, Journal of Theoretical and Applied Information Technology, Vol.85, No.2, pp.124-135, 2016.
[12] M. Durairaj, A. Menaka, “Load Balancing in Cloud Computing”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 5, Issue.8, pp. 862-870, 2015.
[13] Athokpam Bikramjit Singh, Sathyendra Bhat J, Rajesh Raju, Rio D`Souza, “A Comparative 8dy of Various Scheduling Algorithms in Cloud Computing”, American Journal of Intelligent Systems, Vol.7, Issue.3, pp.68-72, 2017.
[14] Pardeep Kumar, Amandeep Verma, “Scheduling Using Improved Genetic Algorithm in Cloud Computing for Independent Tasks”, International Conference on Advances in Computing, Communications, and Informatics, India, pp.137-142, 2012.
[15] Teena Mathew, K. Chandra Sekaran, John Jose, “Study and Analysis of Various Task Scheduling Algorithms in the Cloud Computing Environment”, International Conference on Advances in Computing, Communications, and Informatics, India, pp.658-664, 2014.
[16] Sonali Jain, “Task Scheduling in Cloud Computing using Genetic Algorithm”, International Journal of Computer Science, Engineering, and Information Technology Research, Vol.6, Issue.4, pp. 9-22, 2016.
[17] Pinal Salot, “A Survey of Various Scheduling Algorithm in Cloud Computing Environment”, International Journal of Research in Engineering and Technology, Vol.2, Issue.2, pp. 131-135, 2013.
[18] Jeni Patel, Jignesh Prajapati, “A Survey of Various Scheduling Algorithms and types of Resources Provisioning in Cloud Environment”, International Journal of Engineering and Computer Science, Vol.4 Issue.1, pp.10132-10134, 2015.
[19] Shekhar Singh, Mala Kalra, “Task Scheduling Optimization of Independent Tasks in Cloud Computing using Enhanced Genetic Algorithm”, International Journal of Application or Innovation in Engineering & Management, Vol.3, Issue.7, pp.286-291, 2014.
[20] M. Durairaj, T. Sathyavathi, “Applying Rough Set Theory for Medical Informatics Data Analysis,” International Journal of Scientific Research in Computer Sciences and Engineering, Vol. 1, Issue. 5, pp. 1–8, Oct. 2013.

M. Durairaj, C. Dhanavel, "A Survey on Cloud Service Scheduling Using Genetic Algorithm," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1201-1207, 2018.

Biometric is physical or behavioral characteristics that can be used for human Unique Identification. Biometric verification has become common and refers to an automatic verification of a person predicated on some concrete biometric features derived from his/her physiological and/or behavioral characteristics and is more reliable than the traditional username and password system Applications for biometric ranges from ATM, computers, security installations, mobile phones, credit cards, health and gregarious accommodations. In this paper, we contribute to these surveys by discussing recent ear recognition techniques proposed until the first quarter of 2018 and the applications developed for the same. We pay special attention to the recently developed acoustic and smartphone-based ear recognition techniques.

Ear, biometric, ear-acoustics

[1] Ali Fahmi P.N. and Elyor Kodirov and Deok-Jai Choi and Guee-Sang Lee and Mohd Fikri Azli A and Shohel Sayeed, “Implicit Authentication based on Ear Shape Biometrics using Smartphone Camera during A Call,” IEEE International Conference on Systems, Man, and Cybernetics, pp. 2272-2276, 2012.
[2] B Kocaman, M Kirci, EO Gunes, Y Cakir, O Ozbudak, “On ear biometrics”, EUROCON 2009, EUROCON`09. IEEE, 327-332.
[3] Michal Choras, “Image Feature Extraction Methods for Ear Biometrics--A Survey”, published in 6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM`07).
[4] Khamiss Masaoud and S. Algabary and Khairuddin Omar and Md. Jan Nordin and Siti Norul Huda Sheikh Abdullah, “A Review Paper on Ear Recognition Techniques: Models, Algorithms and Methods,” Australian Journal of Basic and Applied Sciences, vol. 7, no.1, pp. 411-421, 2013.
[5] Khamiss Masaoud S. Algabary and Khairuddin Omar and Md Jan Nordin, “3-DIMENSIONAL EAR RECOGNITION BASED ITERATIVE CLOSEST POINT WITH STOCHASTIC CLUSTERINGMATCHING,” Journal of Computer Science, vol.10, no. 3, pp. 477-483, 2014.
[6] FURUTANI Satoshi and KOSHINAKA Takafumi and OOSUGI Kouji, “Human-Oriented IoT Solutions Using Hearable Technology from NEC,” NEC Technical Journal,Vol.12, No.1, pp.50-54, 2017.
[7] Article on, “NEC Announces Earbud-based Biometric Authentication Technology” dated May 23, 2017.
[8] Dayanand B.Gore and Seema S. Kawthekar and Vipin Y. Borole, “ Ear Recognition Techniques for Biometrics Using Digital Image Processing: A Review,” IOSR Journal of Computer Engineering (IOSR-JCE), PP 22-26.
[9] Žiga Emerši ˇc and Vitomir Štruc and Peter Peer, “ Ear recognition: More than a survey ,” Elsevier B.V., pp. 1-14, 2017.
[10] David J. Hurley and Mark S. Nixon* and John N. Carter, “Force field feature extraction for ear biometrics,” Computer Vision and Image Understanding 98 Elsevier, pp. 491-512, 2005.
[11] Ni Kadek Ayu Wirdiani and Ni Nyoman Triana Anggra and A. A. K. Oka Sudana, “Application of Android-based Ear Biometrics Identification,” International Journal of Computer Applications (0975 – 8887), vol. 172 ,No.10, pp. 11-17, 2017.
[12] Mohd Shafry Mohd Rahim and Amjad Rehman and Fajri Kurniawan and Tanzila Saba,” Ear biometrics for human classification based on region features mining,” Biomedical Research, vol.28, no.10, pp. 4660-4664, 2017.
[13] Neha Kuduk and Akshada Hinge and Kirti Kshirsagar, “BIOMETRIC EAR RECOGNITION SYSTEM,” International Research Journal of Engineering and Technology (IRJET), Vol. 04, no. 1, pp.1002-1006, 2017.
[14] Inas Al-Taie and Nassr Azeez and Arwa Basbrain and Adrian Clark, “ The Effect of Distance Similarity Measures on the Performance of Face, Ear and Palm Biometric Systems,” IEEE, 2017.
[15] Himanshu Srivastava, “ A Comparison Based Study on Biometrics for Human Recognition,” IOSR Journal of Computer Engineering (IOSR-JCE), Vol. 15,no. 1,pp. 22-29 ,2013.
[16] Gursimarpreet Kaur and Dr.Chander Kant Verma, “ Comparative Analysis of Biometric Modalities,” International Journal of Advanced Research in Computer Science and Software Engineering vol.4, no.4, pp. 603-613, 2014.
[17] Srividya R and Ramesh B, “Impregnable Biometric - A Survey,” International Journal of Scientific and Research Publications, Vol. 8, no 2, pp. 26-30, 2018.
[18] Kalyani Mali and Samayita Bhattacharya, “ Comparative Study of Different Biometric Features,” International Journal of Advanced Research in Computer and Communication Engineering,Vol. 2, no.7, pp.2776-2780, 2013.
[19] AYMAN ABAZA and ARUN ROSS and CHRISTINA HEBERT and MARY ANN F. HARRISON and MARK S. NIXON, “A Survey on Ear Biometrics,” ACM Computing Surveys, Vol. 45, No. 2, pp. 22:1 – 22:35, 2013.
[20] Ajit D. Dinkar and Shruti S. Sambyal, “ Person identification in Ethnic Indian Goans using ear biometrics and neural networks,” Forensic Science International 223, pp.373.e1- 373.e13, 2012.
[21] Israa M. Alsaadi, “Physiological Biometric Authentication Systems, Advantages, Disadvantages And Future Development: A Review,” INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH, vol. 4, no. 12, pp. 285-289, 2015.
[22] Sukhdeep Singh and Dr. Sunil Kumar Singla, “ A Review on Biometrics and Ear Recognition Techniques,” International Journal of Advanced Research in Computer Science and Software Engineering, vol.3, no.6, pp. 1624-1630, 2013.
[23] Bahattin Kocaman and Mürvet K_rc_ and Ece Olcay Güne_ and Yüksel Çak_r and Özlem Özbudak, “ON EAR BIOMETRICS”, IEEE, pp. 327-332, 2009.
[24] S. Gangaram and S. Viriri, “Human Identification based on Ear Recognition,” Recent Advances in Electrical Engineering and Educational Technologies, pp.230-234.
[25] Santosh H.Suryawanshi, “THE EAR AS A BIOMETRIC,” International Journal of Computer Science and Mobile Computing, vol.4, no.2, pp. 61-65, 2015.
[26] SWATI NEWALE and PROF.A.M.RAWATE and PROF. PRAVEEN KAMBLE, “Overview of image based ear biometric with Smartphone app,” International Research Journal of Engineering and Technology (IRJET), Vol. 04, no. 07, pp.1265-1268, 2017.
[27] Pedro LuisGaldámez and WilliamRaveane and AngélicaGonzález Arrieta, “ A brief review of the ear recognition process using deep neural networks,” Journal of Applied Logic, pp 1-9,2016.
[28] Shradha Tiwari and Prof. J.N. Chourasia and Dr. Vijay S.Chourasia, “A Review of Advancements in Biometric Systems,” International Journal of Innovative Research in Advanced Engineering (IJIRAE), Vol.2, no.1, pp. 187-204, 2015.
[29] Sasan Karamizadeh and Shahidan M. Abdullah and Azizah A. Manaf and Mazdak Zamani1 and Alireza Hooman, “An Overview of Principal Component Analysis,” Journal of Signal and Information Processing, vol 4, 173-175, 2013.
[30] Ping Yan, “Ear Biometrics in Human Identification,” Graduate Program in Department of Computer Science and Engineering, pp. 1-152, 2006.
[31] K.H. Pun and Y.S. Moon, “Recent Advances in Ear Biometrics,” IEEE International Conference on Automatic Face and Gesture Recognition, 2004.
[32] Barnabas Victor and Kevin Bowyer and Sudeep Sarkar, “AN EVALUATION OF FACE AND EAR BIOMETRICS,” IEEE, pp. 429-432, 2002.
[33] Mauro Conti and Irina Zachia-Zlatea and Bruno Crispo, “Mind How You Answer Me!(Transparently Authenticating the User of a Smartphone when Answering or Placing a Call),” ACM, pp.249-260, 2011.
[34] Takayuki Arakawa and Takafumi Koshinaka and Shohei Yano and Hideki Irisawa and Ryoji Miyahara and Hitoshi Imaoka, “Fast and Accurate Personal Authentication Using Ear Acoustics,” NEC, 2017.
[35] Hui Chen and Bir Bhanu, “Human Ear Recognition in 3D,” IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 29, no. 4, pp. 718-737, 2007.
[36] Andrea F. Abate and Michele Nappi and Stefano Ricciardi, “Smartphone Enabled Person Authentication Based on Ear Biometrics and Arm Gesture,” IEEE International Conference on Systems, Man, and Cybernetics, pp. 003719 - 003724, 2016.
[37] Shubham Mohurle and Seema Khutwad and Pratiksha Kunjir and Anjali Bhosle, “ Review Paper on Ear Biometric Authentication,” International Journal of Engineering Science and Computing, vol. 6, no. 10, pp. 2875-2880, 2016.
[38] Amandeep Kaur Bhatia and Harjinder Kaur, “Security and Privacy in Biometrics: A Review”, International Journal of Scientific Research in Computer Science and Engineering, vol. 1, no. 2, pp. 33-35, 2013.
[39] V.K. Jain and N. Tripathi, “Speech Features Analysis and Biometric Person Identification in Multilingual Environment”, Int. J. Sci. Res. in Network Security and Communication,Vol.6, no. 1, pp. 7-11, 2018.

Uttara Athawale, Manoj Gupta, "Survey on Recent Ear Biometric Recognition Techniques," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1208-1211, 2018.

Scheduling techniques play a prominent role in parallel computing environment to reduce the waiting time of users. Parallel computing provides an incredible amount of resources for user’s on-demand. Therefore, it has become more challenging to schedule the resources in an efficient manner. It has been observed that scheduling is NP-Hard in nature so in order to solve this, meta-heuristic techniques are used for optimal solution. This paper has exhibited a comprehensive review on different scheduling algorithms in the perspective of scheduling metrics such as Execution cost, response time, Makespan, Energy Consumption, Resource utilization are presented. Additionally, classification of meta-heuristic techniques such as GA, PSO, ACO, DA etc. and various constraints designed for parallel computing environment have also been discussed.

ParallelComputing,Scheduling,Meta-heuristics,Deadline,ReliabilityConstraint

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[3] D. Agarwal, S. Jain, et al., “Efficient optimal algorithm of task scheduling in cloud computing environment," arXiv preprint arXiv:1404.2076, 2014.
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[9] R.Abbas ,Haidri, C.P.katti, P.C Saxena, “Cost Effective Deadline Aware Scheduling Strategy for Workflow Applications on Virtual Machines in Cloud Computing”, Journal of King Saud University – Computer and Information Sciences 2017.
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[12] E. Hyytiä, R. Righter, O. Bilenne, and W. Xiaohu. "Dispatching fixed-sized jobs with multiple deadlines to parallel heterogeneous servers." Performance Evaluation (2017)
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[14] Haque, Mohammad, H. Aydin, and D. Zhu. "On Reliability Management of Energy-Aware Real-Time Systems Through Task Replication." IEEE Transactions on Parallel and Distributed Systems 28, no. 3: 813-825,2017.
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[19] Wang, Shuli, L .Kenli, M. Jing, X. Guoqing and L .Keqin. "A Reliability-aware Task Scheduling Algorithm Based on Replication on Heterogeneous Computing Systems." Journal of Grid Computing 15, no. 1: 23-39.2017.
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[24] G Kaur, and M Kalra. "Deadline constrained scheduling of scientific workflows on cloud using hybrid genetic algorithm." In Cloud Computing, Data Science & Engineering-Confluence, 2017 7th International Conference on, pp. 276-280. IEEE, 2017.
[25] Xie, Guoqi, Y Chen, X. Xiao, C Xu, Li Renfa , and Li Keqin . "Energy-efficient Fault-tolerant Scheduling of Reliable Parallel Applications on Heterogeneous Distributed Embedded Systems." IEEE Transactions on Sustainable Computing (2017).
[26] P Kaur, and S.Mehta. "Resource provisioning and work flow scheduling in clouds using augmented Shuffled Frog Leaping Algorithm." Journal of Parallel and Distributed Computing 101: 41-50,2017.
[27] Gedik, Ridvan, C. Rainwater, H. Nachtmann, and Ed A. Pohl. "Analysis of a parallel machine scheduling problem with sequence dependent setup times and job availability intervals." European Journal of Operational Research 251, no. 2: 640-6.50,2016.
[28] Hao, Yongsheng, LWang, and M Zheng. "An adaptive algorithm for scheduling parallel jobs in meteorological Cloud." Knowledge-Based Systems 98: 226-240,2016.
[29] N Kaur, and S Singh. "A Budget-constrained Time and Reliability Optimization BAT Algorithm for Scheduling Workflow Applications in Clouds." Procedia Computer Science 98: 199-204,2016.
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[31] T.Kaur, and I Chana. "Energy aware scheduling of deadline constrained tasks in cloud computing." Cluster Computing 19, no.2 : 679-698,2016.
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[34] A. Verma and S. Kaushal, “Cost Minimized PSO based Workflow Scheduling Plan for Cloud Computing”, I.J. Information Technology and Computer Science, vol.08, 37-43, 2015 Published Online July 2015 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijitcs.2015.08.06.
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[36] Liu, Guoquan, Y. Zeng, Dong Li, and Y. Chen. "Schedule length and reliability-oriented multi-objective scheduling for distributed computing." Soft Computing 19, no. 6 (2015): 1727-1737.
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D. Nanda, "A Comprehensive Study of Various Metaheuristic Based Parallel Job Scheduling Techniques With Different Constraints.," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1212-1218, 2018.

Education is the process teaching, acquire skills, imparting and enhancing knowledge from various sources. Through education, students can learn how to become a good citizen. In present day education system, the variety of courses offered for prospective graduates by the institution is augmenting consistently. The growth of higher education in India especially private and government mode have given an opportunity for prospective graduates to undertake the preferred course but at the same time the gap exists on selection of course and intention behind to chosen. This article speaks about the options available for higher secondary students and on what reasons he/she selects a particular course and pursues it. This paper gives importance for a survey on how earlier researchers have travelled in this area. This survey proves effective for upcoming researcher to orient their research.

Education system, Courses, Opportunity, Intentions

[1]. Mrs. Neelam Verma and Manju Kumar, “Educational / Training / Job opportunities After 10th & 12th”, pp.1-114.
[2]. Dr.R.Saravanan, What next after +2, pp.1-91.
[3]. Shivam Panchal, “A Complete Guide to all the Career Options and Courses After 10+2”, 1-18
[4]. Josephine Nyamwange, “Influence of Student’s Interest on Career Choice among First Year University Students in Public and Private Universities in Kisii County, Kenya”, Journal of Education and Practice, ISSN 2222-288X, Vol.7, No.4, pp.96-102, 2016.
[5]. Chinchu C, “Vocational Preferences and Career Awareness Among Psychology Students in Kerala”, Global Journal for Research Analysis, ISSN NO.2277-8160, Vol.4, No.5, pp.71-73, 2015.
[6]. Prof. Ritesh Patel & Prof. Mitesh Patel, A Study on Perception and Attitude of Students Regarding Factors which they Consider while Making Selection of Institute in MBA Programme in Gujarat State, Journal of Arts, Science & Commerce, E-ISSN 2229-4686, Vol.3, No.1, pp.115-121, 2012.
[7]. Jeofrey Mtemeri & Regis Chireshe, Factors Influencing the Choice of Career Pathways among High School Students in Midlands Province, Zimbabwe, Ph.D thesis, University of South Afria,, pp.1-189, 2017.
[8]. Kazi Afaq Ahmed, Nimra Sharif and Nawaz Ahmad, Factors Influencing Students’ Career Choices: Empirical Evidence from Business Students, Journal of Southeast Asian Research, 2017, pp.1-15
[9]. Sella Kumar, “Career Choice And College Students: Parental Influence on Career Choice Traditionalism among College Students in Selected Cities in Ethiopia”, International Journal of Psychology and Educational Studies, Vol.3, No.3, pp.23-30, 2016.
[10]. Kamol Kitsawad, “An Investigation of Factors Affecting High School Student’s Choice of University in Thailand”, Ph.D thesis, University of Wollongong, pp.1-282, 2013.
[11]. Karunya Ravi and Pradeep Kumar, “Career Aspiration and Perspective Among Students Pursuing Master Course In A Private Dental College, Chennai”, IOSR Journal of Dental and Medical Sciences, e-ISSN: 2279-0853, p-ISSN: 2279-0861. Vol. 13, No.1,pp.56-58, 2014.
[12]. Azubuike Adams and Azubuike Amarachi Salome, “Factors Affecting the Choice of Science Subjects among Female Students in Jigawa Metropolis, Nigeria”, Creative Education, 5, pp.1296-1304, 2014.
[13]. Vijay Paul Reddy, “The Influence of Social Media on International Students’ Choice of University and Course”, Master of Information Technology (Research), Queensland University of Technology, pp.1-205, 2014.
[14]. Nuthanap.G., “Gender Analysis of Academic Achievement among High School Students”, Master of Home Science, University of Agricultural Sciences, Dharwad, pp.1-95, 2007.
[15]. Ilhaam Ashraf, Wendy W T Chan, Ramakrishna Prasad, Mohan Kubendra, Hemavathy D, Shailendra Prasad, “Family medicine: Perception and attitudes among Indian medical students”, Journal of Family Medicine and Primary Care , Published by Wolters Kluwer – Medknow,Vol.7, No.1, pp.205-209, 2018.
[16]. OECD, “Equity and Quality in Education: Supporting Disadvantaged Students and Schools”, OECD Publishing, pp.1-170, 2012.
[17]. Indian Institute of Education, “A Study of unemployment among female graduates in Pune city”, Sponsored by Planning Commission, Government of India, pp.1-130, 2002.
[18]. Madhuri Dubey, http://www.nationalskillsnetwork.in/aicte-skill-development, 2017.
[19]. Vaibhav Jain, “Evaluating and Summarizing Student’s Feedback Using Opinion Mining”, International Journal of Scientific Research in Computer Science and Engineering, E-ISSN: 2320-7639, Vol.1, Issue 1, 2013, pp.43-46
[20]. K. Parimala , G. Rajkumar , A. Ruba and S. Vijayalakshmi, “Challenges and Opportunities with Big Data”, International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue 5, pp.16-20, 2017.

M. Kannan, "Studying Options and Attitude of Students in Selecting Course – A Bibliography Survey," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1219-1222, 2018.

“Internet-of-Things” - a keyword which covers numerous aspects related to the advancements of the Internet into physical reality. The two trending technologies for the IoT are, RFID and wireless sensor networks (WSNs). But since, IoT requires the features of both the technologies, a need for a new communication technology arises. Currently, Nanotechnology is providing the engineering community with a new set of tools to control matter at an atomic and molecular level. Nanotechnology integrates Nano-components and creates a basic functional unit called Nano-machine which performs vital tasks like sensing and actuating. The integration of Nano scale devices and communication networks with High Speed Internet has developed a new technology - “Internet of Nano-Things (IoNT)”. Further, ubiquitously arrayed multimedia Nano-devices, communication networks and Internet are being blended which has developed another communication system which is called as Internet of Multimedia Nano-Things (IoMNT).

Nanotechnology, IoT, IoNT, IoMNT

[1] The Internet of Things: an Overview, Internet society, October 2015.
[2] Akyildiz,I.F., & Jornet, J. M. “The internet of Nano-things. IEEE Wireless Communications”, 17(6), 58-63., 2010
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Santosh S. Kulkarni, Sanjeev G. Kulkarni, Vani P. Datar, "Current Trends in Internet of Things: A Survey," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1223-1226, 2018.

The Internet of Things (IoT) brings together a multitude of technologies, with a vision of creating an interconnected world. This will benefit both corporations as well as the end users. However, a plethora of security and privacy challenges need to be addressed for the IoT to be fully realized. In this paper, we identify and discuss the properties that constitute the uniqueness of the IoT in terms of the upcoming security and privacy challenges. Furthermore, we construct requirements induced by the aforementioned properties. We survey the four most dominant IoT architectures and analyse their security and privacy components with respect to the requirements. Our analysis shows a mediocre coverage of security and privacy requirements. Finally, through our survey, we identify a number of research gaps that constitute the steps ahead for future research.

Internet of Things, IoT Architecture, IoT Applications, Security, Privacy, Future Trends

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[15] R. V. Dharmadhikari 1,S. S. Turambekar,S. C. Dolli,P K Akulwar "Cloud Computing: Data Storage Protocols and Security Techniques", International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.2, pp.113-118, April (2018).
[16] Oluigbo Ikenna V, Nwokonkwo Obi C., Ezeh Gloria N., Ndukwe Ngoziobasi G. "Revolutionizing the Healthcare Industry in Nigeria: The Role of Internet of Things and Big Data Analytics", International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.6, pp.1-12, December (2017)

A.A. Kulkarni, P.K. Mishra, B.K. Tripathy, Manoranjan Panda, "A Security Survey on Internet of Things," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1227-1233, 2018.

Cloud computing is one of the evergreen area where the resources such as data storage, infrastructure, and applications services are provided to the users over the network on demand. Cloud service providers charge users depending upon the space or service provided. So it is not always feasible to hire cloud services every time. Alternate to this, various cloud Infrastructure as a Service frameworks and simulation tools exist in recent years. It is difficult for end-users, developers and researchers to figure out which features and performance of each framework will match their problem statement. This paper analyses some of the most popular open source cloud computing software tools such as Eucalyptus, OpenStack, OpenNebula and CloudStack and also presented its feature comparison which facilitate the researchers and developers in selecting from the different open source cloud platforms.

Iaas, Eucalyptus, OpenStack, OpenNebula, CloudStack, Open source

[1] Paramjot Singh, Vishal Pratap Singh, Gaurav Pachauri, “Critical Analysis of Cloud Computing Using OpenStack” IJCSMC, Vol. 3, Issue. 3, pp. 121-127, 2014.
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[4] Amita and Rajendra Nath, “A comparative study of Open Source IaaS Cloud computing” , International journal of Advanced Research in Computer Science and Software Engineering, pp. 288-293, 2015.
[5] Theo Lynn, Graham Hunt, David Corcoran, John Morrison and Philip Healy, “A Comparative study of current Open-source Infrastructure as a Service frameworks”, International Conference on Cloud Computing and Services Science, 2015.
[6] Jisha S. Manjaly and Jisha S., “A Comparative study on Open Source Cloud Computing Frameworks”, International Journal of Engineering and Computer Science, pp. 2026-2029, 2013.
[7] Rizwana Shaikh and M. Sasi Kumar, “Cloud Simulation Tools: A Comparative Analysis”, International Journal of Computer Applications, pp. 11-14, 2013.
[8] Siddharth Jain, Rakesh Kumar, Anamika and Sunil Kumar Jangir, “A Comparative study for Cloud Computing Platform on Open Source Software”, ABHIYANTRIKI: An International Journal of Engineering and Technology”, pp. 28-35, 2014.
[9] Sonia Shahzadi, Muddesar Iqbal, Zia Ul Qayyum and Tasos Dagiuklas, “Infrastructure as a Service (IaaS): A Comparative performance Analysis of Open-Source Cloud Platforms”, International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, 2017.
[10] Mikyung Kang, Dong-In Kang, John Paul Walters, and Stephen P. Crago, “A Comparison of System Performance on a Private OpenStack Cloud and Amazon EC2”, IEEE 10th International Conference on Cloud Computing, 2017.
[11] Ravi Verma, Ojas Rahate, Ashish Gouda, Nirav Racherla, Prof. Khandu Khot, “Monitoring and Alerting of An OpenStack Cloud", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 2, pp. 941-944, 2017.
[12] K. Phaneendra, Dr. M. Babu Reddy, "Prototype Survey of Different Resource Provisioning Procedures in Cloud Computing", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 1, Issue 1, pp. 108-115, 2016.

V. Suganya, M. Kannan, "A Comparative Analysis on Open Source Infrastructure as a Service Cloud Framework," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1234-1237, 2018.

Data is the new science and it powers everything that we do. Big Data is a phrase that describes the huge collection of structured, unstructured and semi-structured data. It is a mixture of new hardware and algorithms that allow us to ascertain new sequence of structure in large volume of data sets. These structures can used to make effective predictions and, eventually, better resolutions which bring huge benefits to the business organization. Today, organizations are bringing Big Data in such assorted fields, like healthcare, smart cities, education, IOT, banking, marketing, finance and etc. Big data analytics is crucial to work and grow Internet of Things. Big data is combined with IOT for making real-time decisions, such as predicting the behaviour of a gene, suspicious activities of banking transactions, controlling the traffic signals and so on. Big Data has the tremendous power to progress lives with enhanced services and goods, but obstacles remain between Big Data`s commitment and realism. This paper presents an overview of big data and its significance, applications, Technical elements, issues and challenges and review on it.

Bigdata, Architecture,Characteristics,Tools, Issues, Challenges, Applications

[1] Abdul Raheem Syed Willium, “The Future Revolution on Big Data”, IJARCCE Vol. 2, Issue 6, June 2013.
[2] Thi Mai Le and Shu-Yi Liaw “Effects of Pros and Cons of Applying Big Data Analytics to Consumers’ Responses in an E-Commerce Context”, MDPI May 2017.
[3] Bharati. P., Chaudhury. A, “ An empirical investigation of decision-making satisfaction in web-based decision support systems” Decis. Support Syst. 2004, 37, 187–197.
[4] Resnick, P.; Varian, “H.R. Recommender systems” Commun. ACM 1997, 40, 56–58.
[5] Zaharaddeen Karami Lawal, “A review: Issues and Challenges in Big Data from Analytic and Storage perspectives”, International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume – 5 Issue -03 March, 2016 Page No. 15947-15961.
[6] Yuri Demchenko, Canh Ngo, Peter membray “Architecture framework and components for the big data ecosystem”, Techreport,2013.
[7] Krishna Kumar and Akhilesh Dwivedi,” Big Data Issues and Challenges in 21st Century”, International Journal on Emerging Technologies (Special Issue NCETST-2017) 8(1): 72-77(2017)
[8] Stephen Kaisler, “Big data issues and challenges moving forward”,2013 46th Hawaii international conference on system sciences.
[9] Kuchipudi Sravanthi et al, “Applications of bigdata in various fields”, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 6 (5) , 2015, 4629-4632.
[10] Magesh G and P Swarnalatha, “Big data and its applications: A, 2017 survey”,RJPBCS,Pg.No:2346
[11] Shikha Anirban, “Big data analytics in education sector: needs, opportunities and challenges”, International journal of research in computer and communication Technology, Vol 3, Issue 11, November - 2014
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[15] Suraiya Jabin “Big data issues and challenges in business intelligence”,Research gate.
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[17] Abdullah Gani, Aisha Siddiqa, Shahaboddin Shamshirband, Fariza Hanum, “A survey on Indexing Techniques for Big Data Taxonomy and Performance Evaluation”, Knowledge and Information Systems - Issue 2/2016.
[18] Lenka venkata satyanarayan, “Survey on challenges and advantages in big data” , ICJCT volume 6, Issue 2.
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Gaurav Jain , Kunal Gupta , Arpit Kushwah , Abhishek Agrawal, “ A Survey on various Big Data Issues on Cloud Computing”, IJCSE, Volume-5 , Issue-9 , Page no. 131-134, Sep-2017.

P. Muthulakshmi, S. Udhayapriya, "A SURVEY ON BIG DATA ISSUES AND CHALLENGES," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1238-1244, 2018.

As the use of internet grows rapidly, there are some of the securities problems arise. Electronic security mechanisms are already followed on Internet even than these problems are increased day by day. This paper discusses the current research trend to solve the issues of digital image authentication and integrity. Different systems suggested by researchers to solve the above mentioned issues are studied and are classified as Fragile watermarking system as well as Semi-fragile watermarking system. Some of the researchers also apply the combination of fragile as well as semi-fragile watermarking system. Individually different systems are analyzed where some systems solve the authentication issue, some systems work with tamper localization where as other systems are there which has capability to get back the original image from the tampered image. Review findings are discussed based on the existing systems discussed by other researchers. Some of the challenges come up based on these reviews and are also discussed here.

Digital Watermarking, Image Authentication, Tamper detection, Tamper localization, Self Recovery

[1]. Vaishnavi D., and T. S. Subashini. "Image Tamper Detection based on Edge Image and Chaotic Arnold Map." Indian Journal of Science and Technology vol. 8, No. 6: pp. 548-555, 2015.
[2]. Pongsomboon, Paween, Toshiaki Kondo, and Yoshiyuki Kamakura. "An image tamper detection and recovery method using multiple watermarks." Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 13th International Conference on. IEEE, 2016.
[3]. Dadkhah, Sajjad, et al. "An effective SVD-based image tampering detection and self-recovery using active watermarking." Signal Processing: Image Communication Vol. 29, No.10 : pp. 1197-1210, 2014.
[4]. Haghighi, Behrouz Bolourian, Amir Hossein Taherinia, and Ahad Harati. "TRLH: Fragile and blind dual watermarking for image tamper detection and self-recovery based on lifting wavelet transform and halftoning technique." Journal of Visual Communication and Image Representation, 2017.
[5]. Kim, Cheonshik, Dongkyoo Shin, and Ching-Nung Yang. "Self-embedding fragile watermarking scheme to restoration of a tampered image using AMBTC." Personal and Ubiquitous Computing Vol. 22 No. 1: pp.11-22, 2018.
[6]. Kiatpapan, Sawiya, and Toshiaki Kondo. "An image tamper detection and recovery method based on self-embedding dual watermarking." Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2015 12th International Conference on. IEEE, 2015.
[7]. Vaishnavi, D., and T. S. Subashini. "Fragile watermarking scheme based on wavelet edge features." Journal of Electrical Engineering & Technology Vol. 10 No.5 : pp. 2149-2154, 2015.
[8]. Rawat, Sanjay, and Balasubramanian Raman. "A chaotic system based fragile watermarking scheme for image tamper detection." AEU-International Journal of Electronics and Communications Vol. 65 No.10 : pp. 840-847, 2011.
[9]. Botta, Marco, Davide Cavagnino, and Victor Pomponiu. "A successful attack and revision of a chaotic system based fragile watermarking scheme for image tamper detection." AEU-International Journal of Electronics and Communications Vol. 69 No. 1 : pp. 242-245, 2015.
[10]. Bravo-Solorio, Sergio, et al. "Fast fragile watermark embedding and iterative mechanism with high self-restoration performance." Digital Signal Processing Vol. 73 : pp. 83-92, 2018.
[11]. Sathik M. M., and S. S. Sujatha. "Authentication of digital images by using a semi-fragile watermarking technique." International Journal of Advanced Research in Computer Science and Software Engineering Vol. 2 No. 11 : pp. 39-44, 2012.
[12]. Madduma Buddhika, and Sheela Ramanna. "Content-based image authentication framework with semi-fragile hybrid watermark scheme." Man-Machine Interactions 2. Springer Berlin Heidelberg, pp. 239-247, 2011.
[13]. Arathi Chitla. "A semi fragile image watermarking technique using block based SVD." International Journal of Computer Science and Information Technologies Vol. 3 No. 2 : pp. 3644-3647, 2012.
[14]. Kommini Chaitanya, Kamalesh Ellanti, and E. Harshavardhan Chowdary. "Semi-Fragile Watermarking Scheme based on Feature in DWT Domain."International Journal of Computer Applications Vol. 28 No. 3 : pp. 42-46, 2011.
[15]. LV LINTAO, et al. "A semi-fragile watermarking scheme for image tamper localization and recovery." Journal of Theoretical and Applied Information Technology Vol. 42 No. 2 : pp. 287-291, 2012.
[16]. Gokhale U. M., and Y. V. Joshi. "A semi fragile watermarking algorithm based on SVD-IWT for image authentication." International Journal of Advanced Research in Computer and Communication Engineering Vol. 1 No. 4, 2012.
[17]. Li Chunlei, et al. "Semi-fragile self-recoverable watermarking scheme for face image protection." Computers & Electrical Engineering on Elsevier ,2016.
[18]. Molina-García, Javier, et al. "Watermarking algorithm for authentication and self-recovery of tampered images using DWT." Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves (MSMW), 2016 9th International Kharkiv Symposium on. IEEE, 2016.
[19]. Gadhiya, Tushar D., et al. "Use of discrete wavelet transform method for detection and localization of tampering in a digital medical image." IEEE Region 10 Symposium (TENSYMP), 2017. IEEE, 2017.
[20]. Ramos, Clara Cruz, et al. "Watermarking-Based Image Authentication System in the Discrete Wavelet Transform Domain." Discrete Wavelet Transforms-Algorithms and Applications. InTech, 2011.
[21]. Tiwari, Archana, and Manisha Sharma. "An Efficient Vector Quantization Based Watermarking Method for Image Integrity Authentication." Progress in Intelligent Computing Techniques: Theory, Practice, and Applications. Springer, Singapore, pp. 215-225, 2018.
[22]. Chetan, K. R., and S. Nirmala. "Intelligent Multiple Watermarking Schemes for the Authentication and Tamper Recovery of Information in Document Image." Advanced Computing and Communication Technologies. Springer, Singapore, pp. 183-193, 2018.
[23]. Kavitha V., and Subhashree M. "Detection and tampering of Tampered Images." International Conference on Current Research in Engineering Science and Technology (ICCREST): pp. 57-61, 2016.
[24]. Lyu, Wan-Li, Chin-Chen Chang, and Feng Wang. "Color PNG Image Authentication Scheme Based on Rehashing and Secret Sharing Method." Journal of Information Hiding and Multimedia Signal Processing Vol. 6 No. 3 : pp. 523-533, 2015.
[25]. Mishra Mitali, and Flt Adhikary. "Digital image tamper detection techniques-a comprehensive study." International Journal of Computer Science & Business Informatics Vol. 2 No. 1: pp. 1-12, 2013

Hiral A. Patel, Dipti B. Shah, "Review on Watermarking Scheme for Digital Image Authentication, Tampering and Self Recovery.," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1245-1250, 2018.

Accident examination assumes an imperative part in transportation framework. Examination of mishap is critical on the grounds that it can uncover the connection between the distinctive kinds of ascribes that adds to a accident. Qualities that influence the accident can be characteristic, condition properties, movement traits and so on. Breaking down accident can give the data about the commitment of these characteristics which can be used to defeat the accident rate. These days, Data mining is a famous system for inspecting the railway accident dataset. This paper presents various research work done in past in the field of rail accident analysis using data mining as a review and also discussed about the cause of accidents and role of data mining in the analysis of accidents.

Accident, Analysis, Data Mining, Rail Accident, Traffic Management

[1] Sridhar.T, “Safety Alert Signalling Measure In Train Transportation System And Its Automated Behaviours Using Gps”, IEEE, International Conference On Information,Communication & Embedded Systems, 2017.
[2] Xiang Liu, M. Rapik Saat, Christopher P. L. Barkan, “Analysis of Causes of Major Train Derailment and Their Effect on Accident Rates”, Journal of the Transportation Research Board, 2012, pp. 154–163.
[3] E. Davey, “ Rail Traffic Management System ( Tms)”, 2012,
Pp. 126-137
[4] Donald E. Brown, “Text Mining the Contributors to Rail Accidents”, IEEE, Transactions on Intelligent Transportation Systems, Vol.17,No.2,2016,pp. 346 – 355.
[5] Ramesh NanajiWasnik, “Analysis of Railway Fatalities in Central India”, pp. 311-314.
[6] CH. Nireesha, N. Vijay Kumar, V. Babu, “Analysing the Train Accident Injuries using Mining Techniques”, International Journal for Research in Applied Science & Engineering Technology, Vol. 5, Iss. 4, 2017, pp. 1159-1162.
[7] T. S. Letia, A. Astilean, R. Miron, M.M. Santa, “Train Traffic Control Based on Distributed Resource Allocation”, Symposium on Telematics Applications, 2010, pp. 1-6
[8] Haniyeh Ghomi, Morteza Bagheri, “Identifying vehicle driver injury severity factors at highway-railway grade
crossings using data mining algorithms”, IEEE, International Conference on Transportation Information and Safety, 2017, pp. 1054-1059.
[9] Ahmad Mirabadi, Shabnam Sharifian, “Application of association rules in Iranian Railways (RAI) accident data analysis”, 2010, pp. 1427–1435.
[10] Lei Wang, Yuntao Chen, Huaiyuan Zhai, Shouxin Song, “Based on Large Passenger Flow Research on Safety Operation of Urban Rail Transit”, IEEE, 2017.
[11] Francesco Corman, Lingyun Meng, “A Review of Online Dynamic Models and Algorithms for Railway Traffic Management”, IEEE, Transactions on Intelligent Transportation Systems, Vol. 16, No. 3, 2015, pp. 1274-1284.
[12] Pavle Kecman, Rob M.P. Goverde, “An online railway traffic prediction model”, (2013) pp. 1-19.
[13] S. Arivazhagan, R. Newlin Shebiah, J. Salome Magdalene, G. Sushmitha, “Railway Track Derailment Inspection System Using Segmentation Based Fractal Texture Analysis”, ICTACT Journal on Image and Video Processing, Vol. 6, Iss. 1, August 2015, pp. 1060-1065.
[14] Luca Oneto, Emanuele Fumeo, Giorgio Clerico, Renzo Canepa, Federico Papa, Carlo Dambra, Nadia Mazzino, and Davide Anguita, “Advanced Analytics for Train Delay Prediction Systems by Including Exogenous Weather Data”, IEEE, International Conference on Data Science and Advanced Analytics, 2016, pp. 459-467.
[15] Simon Tschirner, Bengt Sandblad, Arne W. Andersson, “Solutions to the problem of inconsistent plans in railway traffic Operation”, Journal of Rail Transport Planning & Management, 2014.

Manju Bala, Anshu Bhasin, "A Review on Analysis of Railway Traffic Accident with Data Mining Techniques," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1251-1256, 2018.