The week's pick
Random Articles
Reseach Article
To Analyze Power Consumption and Quality of Service using Map Reduce on Hadoop: A Survey
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 182 - Number 25 |
| Year of Publication: 2018 |
| Authors: Sandeep Rai, Aishwarya Namdev |
10.5120/ijca2018918059
|
Sandeep Rai, Aishwarya Namdev . To Analyze Power Consumption and Quality of Service using Map Reduce on Hadoop: A Survey. International Journal of Computer Applications. 182, 25 ( Nov 2018), 8-11. DOI=10.5120/ijca2018918059
Abstract
Data is growing at a rate which cannot be handled by the traditional methods of computing. To store and process such data new data analysis and storage techniques have emerged over the last few years. Hadoop is one such parallel processing open source framework which provides distributed storage and processing of Big data. Big Data analytics has emerged as an attractive domain of research these days. For handling big data cloud computing has been used and back end of thetechnology is cluster of resources. Cluster of resources can be formed using a framework like Apache Hadoop. In this paper a survey is performed on big data analysis using Apache Hadoop and other utility tools. For better performance of cloud Quality of service and power consumption should be optimal. So in this survey is discuss resolves around Quality of Service and energy consumption.
References
- D. P. Acharjya, Kauser Ahmed P, Survey on Big Data Analytics: Challenges, Open Research Issues and Tools, School of Computing Science and Engineering, IT University Vellore, India, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 7, No. 2, 2016
- J.Dean, S.Ghemawat,“MapReduce: simplified data processing on large clusters,” Communications of the ACM, 51(1):107–113, January 2008.
- NIST Definition of Cloud Computing V15, csrc.nist.gov/groups/SNS/cloudcomputing/ cloud-def-V15.doc
- Annual energy review 2008. Energy Information Administration, U.S. Department of Energy, June 2011.
- “Green Grid data center efficiency metrics: PUE and DCIE,” White Paper, The Green Grid, December 2012.
- SPECpower ssj2008. Standard Performance Evaluation Corporation, http://www.spec.org/power ssj2008/, April 2013.
- Google, “ Data center efficiency measurements,” The Google Blog, 2014. C. Belady, “In the data center, power and cooling costs more than the IT equipment it supports,” Electronics Cooling Magazine, 13(1):24–27, February 2015.
- J. Koomey, “Worldwide electricity used in data centers,” Environmental Research Letters, 3(3), September 2015.
- “International energy annual 2006,” Energy Information Administration, U.S. Department of Energy, June 2016.
- A. Desai, Nagegowda K S, “Advanced Control Distributed Processing Architecture (ACDPA) using SDN and Hadoop for identifying the flow characteristics and setting the quality of service(QoS) in the network,”2016 IEEE International Advance Computing Conference (IACC), Bangalore, 2015, pp. 784-788.
- A. Desai, Nagegowda K S, Ninikrishna T, “Secure and QoS aware architecture for cloud using software defined networks and Hadoop,” 2017 International Conference on Computing and Network Communications (CoCoNet), Trivandrum, 2015, pp. 369-373.
- R. Osman, J. F. Pérez, G. Casale, “Quantifying the Impact of Replication on the Quality-of-Service in Cloud Databases,” 2016 IEEE International Conference on Software Quality, Reliability and Security (QRS), Vienna, 2017, pp. 286-297.
- Z. Zhao, M. Peng, Z. Ding, W. Wang, H. V. Poor, “Cluster Content Caching: An Energy-Efficient Approach to Improve Quality of Service in Cloud Radio Access Networks,” in IEEE Journal on Selected Areas in Communications, vol. 34, no. 5, pp. 1207-1221, May 2017.
- S. Ghemawat, H. Gobioff, S.-T. Leung, “The Google file system,” SIGOPS Oper. Syst. Rev., 37(5):29–43, 2003.
- J. Ammer, J. Rabacy, “The energy-per-useful-bit metric for evaluating and optimizing sensor network physical layers,” In Sensor and Ad Hoc communications and Networks, 2006.
- SECON ’06. 2006 3rd Annual IEEE Communications Society on, vol. 2, pages 695–700, Sept. 2017. Energy star enterprise server specification, United States April 2017.
- L. A. Barroso, U. H¨olzle, “The case for energy-proportional computing,” Computer, 40(12):33–37, 2017.
- K. Lim, P. Ranganathan, J. Chang, C. Patel, T. Mudge, S. Reinhardt, “Understanding anddesigning new server architectures for emergingwarehouse-computing environments,” In ISC A ’08:Proceedings of the 35th International Sym posium on Computer Architecture, pages 315– 326, W ashington, DC, USA, 2008. IEEE Computer Society.
- Gridmix. HADOOP-HOME/src/benchmarks/gridmix in all recent Hadoop distributions.
- Javier Conejero, Omer Rana, Peter Burnap, Jeffrey Morgan, Blanca Caminero, Carmen Carrion, “Analyzing Hadoop power consumption and impact on application QoS,” Elsevier, pg. no. 213-223, March 2017
Index Terms
Keywords