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i-manager's Journal on Cloud Computing (JCC)

Current Issue Vol. 10 Issue 2

Most Cited

Volume 3 Issue 2 February - April 2016

Research Paper

Performance Evaluation for Crud Operations in NosQL Databases

Amandeep Kaur* , Kanwalvir Singh Dhindsa**

* PG Scholar, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.

** Professor, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.

Kaur, A., and Dhindsa, K. S. (2016). Performance Evaluation for Crud Operations in NosQL Databases. i-manager’s Journal on Cloud Computing, 3(2), 1-9.

Abstract

With the Web growing rapidly and increase in user-generated content websites such as Facebook and Twitter, there is a need for fast databases that can handle huge amounts of data. For this purpose, new database management systems collectively called NoSQL are being developed. There are many NoSQL database types with different performances, and thus it is important to evaluate performance. To check the performance, three major NoSQL databases called MongoDB, Cassandra, and Couchbase have been considered. For performance analysis, different workloads were designed. The evaluation has been done on the basis of read and update operations. This evaluation enables users to choose the most appropriate NoSQL database according to the particular mechanisms and application needs.

References

[1]. A.B.M. Moniruzzaman and S.A. Hossain, (2013). “NoSQL Database: New Era of Databases for Big data Analytics - Classification, Characteristics and Comparison”. International Journal of Database Theory and Application, Vol. 6, No. 4, pp. 1–14.

[2]. A. Ron, B. Sheba, and A. Shulman-peleg, (2015). “No th SQL, No Injection? Examining NoSQL Security”. 8 International Conference on Databases, IEEE, California, US.

[3]. B. Saraladevi, N. Pazhaniraja, P.V. Paul, M.S.S. Basha, and P. Dhavachelvan, (2015). “Big Data and Hadoop-A n d Study in Security Perspective”. 2 International Symposium on Big Data and Cloud Computing, Vol. 50, pp. 596–601.

[4]. C.-O. Truica, F. Radulescu, A. Boicea, and I. Bucur, (2015). “Performance Evaluation for CRUD Operations in Asynchronously Replicated Document Oriented th Database”. 20 International Conference on Control Systems and Computer Science, IEEE, pp. 191–196.

[5]. G. Aydin, I.R. Hallac, and B. Karakus, (2015). “Architecture and implementation of a scalable sensor data storage and analysis system using cloud computing and big data technologies”. Hindawi Journal of Sensors, Vol. 9, No. 02, pp. 1-11.

[6]. I.A.T. Hashem, I. Yaqoob, N. Badrul Anuar, S. Mokhtar, A. Gani, and S. Ullah Khan, (2014). “The rise of 'Big Data' on cloud computing: Review and open research issues”. Information Systems, Vol. 47, No. 7, pp. 98–115.

[7]. J. Pokorny, (2011). “NoSQL Databases: A step to database scalability in Web environment”. International Conference on WEB Information Systems, Vol. 9, No. 1, pp. 69-82.

[8]. J.R. Lourenço, V. Abramova, M. Vieira, B. Cabral, and J.B. Bernardino, (2015). “NOSQL databases: A software engineering perspective”. Advances in Intelligent Systems and Computing, Springer, Vol. 353, No. 6, pp. 741–750.

[9]. K. Barmpis and D.S. Kolovos, (2014). “Evaluation of Contemporary Graph Databases for Efficient Persistence of Large-Scale Models”. Journal of Object Technology, Vol. 13, No. 3, pp. 1-26.

[10]. K. Chitra and B. Jeevarani, (2013). “Study on Basically Available, Scalable and Eventually Consistent NOSQL Databases”. International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, No. 5, pp. 991–996.

[11]. K. Zvarevashe and T.T. Gotora, (2014). “A Random Walk through the Dark Side of NoSQL Databases in Big Data Analytics”. International Journal of Science and Research, Vol. 3, No. 6, pp. 506-509.

[12]. Manoj V., (2014). “Comparative Study of NoSQL Document, Column Store Databases and Evaluation of Cassandra”. International Journal of Database Management Systems, Vol. 6, No. 4, pp. 11–26.

[13]. P. Soni and N.S. Yadav, (2015). “Quantitative Analysis of Document Stored Databases”. International Journal of Computer Applications, Vol. 118, No. 20, pp. 37–41.

[14]. R. Aniceto and R. Xavier, (2015). “Evaluating the Cassandra NoSQL Database Approach for Genomic Data Persistency ”. Hindawi Publishing Corporation International Journal of Genomics, Vol. 25, No. 03.

[15]. S. Kaisler, F. Armour, and J. A. Espinosa, (2014). “Introduction to Big Data: Challenges, Opportunities, and th Realities Minitrack”. 47 Hawaii International Conference on System Sciences (HICSS), pp. 728–728.

[16]. S. Madden, (2012). “From Databases to Big Data”. IEEE Computer Society, Vol. 16, No. 3, pp. 4–6.

[17]. S.S. Pore and S.B. Pawar, (2015). “Comparative Study of SQL & NoSQL Databases”. International Journal of Advanced Research in Computer Engineering & Technology, Vol. 4, No. 5, pp. 1747–1753.

[18]. V. Abramova, J. Bernardino, and P. Furtado, (2014). “Which NoSQL Database? A Performance Overview”. Open Journal of Databases, Vol. 1, No. 2, pp. 17–24.

[19]. V. Sharma and M. Dave, (2012). “SQL and NoSQL Databases”. International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 2, No. 8, pp. 20–27.

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Research Paper

Performance Evaluation of Task Scheduling Algorithms for Cloud Computing

Amtoj Kaur* , Kanwalvir Singh Dhindsa**

* PG Scholar, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.

** Professor, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.

Kaur, A., and Dhindsa, K. S., (2016). Performance Evaluation of Task Scheduling Algorithms for Cloud Computing. i-manager’s Journal on Cloud Computing,3(2), 10-16.

Abstract

Cloud Computing deals with the varied virtualization resources. The task scheduling plays a crucial role to enhance the performance of cloud computing. The issue with task scheduling is distribution of tasks within the system in a way that will optimize the performance of the overall system, minimize the makespan, waiting time, maximize throughput, and so on. The paper highlights the comparison between FCFS, Priority based and Round Robin scheduling algorithms. The priority based and round robin scheduling algorithm have showcased better results under certain parameters than the FCFS.

References

[1]. Antony Thomas, Krishnalal G., and Jagathy Raj VP, (2015). “Cried Based Scheduling Algorithm in Cloud Computing Environment”. International Conference on Information and Communication Technologies, Elsevier, Vol. 46, pp-913-920.

[2]. Amin Mehranzadeh and Seyyed Mohsen Hashemi, (2013). “A Novel-Scheduling Algorithm for Cloud Computing based on Fuzzy Logic”. International Journal of Applied Information Systems Foundation of Computer Science FCS, New York, USA, Vol. 5, No. 7, pp. 2249-0868.

[3]. Ali Al-maamari and Fatma A. Omara, (2015). “Task Scheduling Using PSO Algorithm in Cloud Computing Environments”. International Journal of Grid Distribution Computing, Vol. 8, No. 5, pp. 245-256.

[4]. Aditya Marphatia, Aditi Muhnot, Tanveer Sachdeva, Esha Shukla, and Lakshmi Kurup, (2013). “Optimization of FCFS Based Resource Provisioning Algorithm for Cloud Computing”. IOSR Journal of Computer Engineering, Vol. 10, No. 5, pp. 01-05.

[5]. Amit Agarwal, and Saloni Jain, (2014). “Efficient Optimal Algorithm of Task Scheduling in Cloud Computing Environment”. International Journal of Computer Trends and Technology, Vol. 9, No. 7, pp. 344- 349.

[6]. Eakta Kumari and Monika, (2015). “Task Scheduling Algorithms in Cloud Computing: A Review”. International Journal of Science, Environment and Technology, Vol. 4, No. 2, pp.433-439.

[7]. Gaurang Patel, Rutvik Mehta, and Upandra Bhoi, (2015). “Enhanced Load Balanced Min Min Algorithm For Static Meta Task Scheduling in cloud computing”. International Conference on Recent Trends in Computing, Elsevier, Vol. 57, pp.545-553.

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[9]. Kun Li, Gaochao Xu, Guangyu Zhao, Yushuang Dong, and Dan Wang, (2011). “Cloud Task scheduling based on Load Balancing Ant Colony Optimization”. Sixth Annual China Grid Conference, IEEE, Chang Chun, Liaoning, China, pp. 3-9.

[10]. Liyun Zuo, Lei Shu Shoubin Dong, Chunsheng Zhu, and Takahiro Hara, (2015). “A Multi-Objective Optimization Scheduling Method Based on the Ant Colony Algorithm in Cloud Computing”. Special Section on Big Data Services and Computational Intelligence for Industrial Systems, IEEE, Vol. 3, pp. 2687-2699.

[11]. Pandaba Pradhan, Prafulla Ku. Behera, and BNB Ray, (2016). “Modified Round Robin Algorithm for Resource Allocation in Cloud Computing”. International Conference on Computational Modeling and Security, Elsevier, Vol. 85, pp. 878-890.

[12]. Sonia Sindhu, (2015). “Task Scheduling in Cloud Computing”. International Journal of Advanced Research in Computer Engineering & Technology, Vol. 4, No. 6, pp. 3019-3023.

[13]. R K Jena, (2015). “Multi objective Task Scheduling in Cloud Environment Using Nested PSO Framework”. Procedia Computer Science, Elsevier, Vol. 57, pp. 1219- 1227.

[14]. S. Sindhu and Saswati Mukherjee, (2011). “Efficient Task Scheduling Algorithms for Cloud Computing Environment”. Department of Information Science and Technology Springer.

[15]. Tripti Mandal and Sriyankar Acharyya, (2015). “Optimal Task Scheduling in Cloud Computing Environment: Meta Heuristic Approaches”. International Conference on Electrical Information and Communication Technology, IEEE, pp. 25-28.

[16]. Vijindra, and Sudhir Shenai, (2012). “Survey on Scheduling Issues in Cloud Computing”. International Conference on Modeling Optimization and Computing, Vol. 38. pp. 2881-2888.

[17]. Weifeng Sun, Yudan Zhu, Zhiyuan Su, Dong Jiao, and Mingchu Li, (2010). “A Priority-based Task Scheduling Algorithm in Grid”. Third International Symposium on Parallel Architectures, Algorithms and Programming, IEEE, Dalian, China, pp. 311-315.

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Research Paper

Providing Security to The User Data in Cloud

Nagaraja J* , M. Purushotham**

* PG Scholar, Department of Computer Science and Engineering, Siddhartha Educational Academy Group of Institutions, Tirupathi, AP, India.

** Assistant Professor, Department of Computer Science and Engineering, Siddhartha Educational Academy Group of Institutions, Tirupathi, AP, India.

Nagaraja, j., and Purushotham, M. (2016). Providing Security to The User Data in Cloud. i-manager’s Journal on Cloud Computing,3(2), 17-24.

Abstract

References

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Abstract

Cloud computing infrastructure is widely used for deploying client's data in sharing environment. Clients can store and retrieve their data, whenever client needs to access his data, cloud provides the required data efficiently. However, some of the important data might be easily damaged, where the data holder can't store in the cloud unless and until the data privacy and confidentiality is guaranteed. It is nice to provide confidentially during the query processing time and retrieval time. To provide confidentially and efficiency for the query processing, The authors use RC4 algorithm which provides security to users data. The RC4 algorithm produces a pseudo-random key stream that issued to generate the cipher text (by XORing it with the plaintext). With this stream cipher, it can be used for encryption by combining it with the plaintext using bit-wise exclusive-or; translate is performed in the same way.

References

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Research Paper

Improving the Proof of Retrievability in Cloud Computing

ALI AHAMMED DARUBHAIGARI*

PG Scholar, Department of Computer Science and Engineering, JNTUACEA, Andhra Pradesh, India.

Ahammed, D. A. (2016). Improving the Proof of Retrievability in Cloud Computing. i-manager’s Journal on Cloud Computing,3(2), 25-31.

Abstract

References

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Abstract

Cloud computing provides resource sharing and handling of applications on internet without having local or personal devices. The data integrity is one of the major challenges in cloud computing. The Outsourced Proof of Retrievability (OPoR) system focuses on Cloud Storage Server (CSS) for prevention of routing attacks and malicious operations of servers. In Public verifiability, the security monitoring is taken by Cloud Audit Server (CAS) for reducing overhead on clients. Hence there is a chance that CAS can take miscellaneous operations, so it is needed to strengthen the secure process of both CSS and CAS. This paper strengthens the Proof of Retrievability model (PoR) process and its dynamic data integrity verification on distrusted and outsourced storages on cloud computing. It strengthens the CAS and CSS operations by using third party entities, which generates unique temporary key for each update or modification of the file from user. Generally, this type of OTP key is generated by the server side, hence it is generated by third party Key-Generator entity. The reset attacks of CAS and cloud storage server is secured by a unique temporary key and deleting the local host replica after verifying the uploaded file proof tags, which was send by CAS and CSS, and the cost of memory and process time is reduced using Elliptic curve cryptography. Thus the proposed system, Improving the Proof of Retrievability (IPoR) model will toughen the resistant of retrievability on upload and update of file operations on cloud computing.

References

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Review Paper

Security Threats to Cloud and Corresponding Solutions

D. Raghavaraju*

*Assistant Professor, Department of Computer Science and Engineering, SVIT, Anantapur, India.

Raghavaraju, D. (2016). Security Threats to Cloud and Corresponding Solutions. i-manager’s Journal on Cloud Computing,3(2), 32-36.

Abstract

References

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Abstract

Distributed computing frameworks speak to a standout amongst the most complex processing frameworks as of now in presence. Current uses of Cloud include broad utilization of disseminated frameworks with shifting level of network and use. With a late concentrate on huge scale expansion of Cloud processing, personality administration in Cloud based frameworks is a basic issue for the maintainability of any Cloud-based administration. This zone has additionally gotten extensive consideration from the exploration group and also the IT business. Diverse calculations and methodology are utilized by the specialists. Still distributed computing security is in its center stage. A few IT organizations are concentrating on cloud security and cloud information security. This paper gives a thought regarding security dangers and arrangements.

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i-manager's Journal on Cloud Computing (JCC)

Current Issue Vol. 10 Issue 2

Most Read

Most Cited

Volume 3 Issue 2 February - April 2016

Performance Evaluation for Crud Operations in NosQL Databases

Amandeep Kaur* , Kanwalvir Singh Dhindsa**

* PG Scholar, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India. ** Professor, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.

Kaur, A., and Dhindsa, K. S. (2016). Performance Evaluation for Crud Operations in NosQL Databases. i-manager’s Journal on Cloud Computing, 3(2), 1-9.

Abstract

References

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Performance Evaluation of Task Scheduling Algorithms for Cloud Computing

Amtoj Kaur* , Kanwalvir Singh Dhindsa**

* PG Scholar, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India. ** Professor, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.

Kaur, A., and Dhindsa, K. S., (2016). Performance Evaluation of Task Scheduling Algorithms for Cloud Computing. i-manager’s Journal on Cloud Computing,3(2), 10-16.

Abstract

References

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Providing Security to The User Data in Cloud

Nagaraja J* , M. Purushotham**

* PG Scholar, Department of Computer Science and Engineering, Siddhartha Educational Academy Group of Institutions, Tirupathi, AP, India. ** Assistant Professor, Department of Computer Science and Engineering, Siddhartha Educational Academy Group of Institutions, Tirupathi, AP, India.

Nagaraja, j., and Purushotham, M. (2016). Providing Security to The User Data in Cloud. i-manager’s Journal on Cloud Computing,3(2), 17-24.

Abstract

References

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Improving the Proof of Retrievability in Cloud Computing

ALI AHAMMED DARUBHAIGARI*

PG Scholar, Department of Computer Science and Engineering, JNTUACEA, Andhra Pradesh, India.

Ahammed, D. A. (2016). Improving the Proof of Retrievability in Cloud Computing. i-manager’s Journal on Cloud Computing,3(2), 25-31.

Abstract

References

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Security Threats to Cloud and Corresponding Solutions

D. Raghavaraju*

*Assistant Professor, Department of Computer Science and Engineering, SVIT, Anantapur, India.

Raghavaraju, D. (2016). Security Threats to Cloud and Corresponding Solutions. i-manager’s Journal on Cloud Computing,3(2), 32-36.

Abstract

References

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* PG Scholar, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.

** Professor, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.

* PG Scholar, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.

** Professor, Department of Computer Science and Engineering, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.

* PG Scholar, Department of Computer Science and Engineering, Siddhartha Educational Academy Group of Institutions, Tirupathi, AP, India.

** Assistant Professor, Department of Computer Science and Engineering, Siddhartha Educational Academy Group of Institutions, Tirupathi, AP, India.