Examining Cloud Computation Technologies

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Cloud computing involves a lot of concepts and technologies. Companies and corporations such as Amazon, Google and Microsoft are providing services following the logic of computational infrastructure cloud computing, with Amazon the pioneer in providing and marketing infrastructure of this kind.

The academic community has also shown interest in cloud computing, and some work has been directed to improvements in aspects of performance, security, usability, implementation and reliability of the system as a whole (Armbrust et al. 2009). Other work has developed new techniques to make adequate infrastructure to each context of cloud computing environments, among which we highlight the project Eucalyptus (Liu et al. 2007), developed by the University of California. The following are some technology, such a model of programming, infrastructure and platforms for cloud computing.


The MapReduce (Dean and Ghemawat 2004) is a model of programming aimed at processing large volumes of data, where the user specifies your application through the sequence of MapReduce operations. The tasks of parallelism, fault tolerance, data distribution and load balancing are left to the MapReduce system, simplifying the development process. From the standpoint of distributed systems, MapReduce offers the transparency of replication, distribution and synchronization.

Each operation of the MapReduce model consists of two functions. The first call mapping function receives a portion of the input file and according to the specification of the user issues a set of intermediate key-value pairs. The second function, called reduction, given a set of values associated with each key, called block. The processing defined by the user and perform...

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- Ciurana E. (2009). Developing with Google App Engine. Apress, Berkely, CA, USA.

- Dean, J. and Ghemawat, S. (2004). MapReduce: Simplified Data Processing on Large Clusters


- Liu S., Liang Y., and Brooks M. (2007). Eucalyptus: a web service-enabled infrastructure. In CASCON ’07: Proceedings of the 2007 conference of the center for advanced studies on Collaborative research, pages 1–11, New York, NY, USA. ACM. http://portal.acm.org/citation.cfm?id=1321213&dl=GUIDE&coll=GUIDE&CFID=97803065&CFTOKEN=12833606

- Hadoop 2010. Apache Hadoop. http://hadoop.apache.org/mapreduce/

- Vecchiola C., Chu X., and Buyya R. (2009). Aneka: A Software Platform for.NET-based Cloud Computing. http://www.cloudbus.org/reports/AnekaCloudPlatform2009.pdf

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