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Cloud Computing Cloud computing means storing and accessing data and programs over
Cloud Computing Cloud computing means storing and accessing data and programs over
Cloud computing
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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.
MapReduce/Hadoop
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
http://static.googleusercontent.com/external_content/untrusted_dlcp/labs.google.com/en//papers/mapreduce-osdi04.pdf
- 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
Cloud is the result of a decade research in the field of distributing computing , utility computing, virtualization , grid computing and more recently software, network services and web technology which is changeable evolution on demanding technology and services also as looking to the rapid growth of cloud computing which have changed the global computing infrastructure as well as the concept of computing resources toward cloud infrastructure. The important and interest of cloud computing increasing day by day and this technology receives more and more attention in the world (Jain, 2014) the mostly widely used definition of cloud computing is introduced by NIST “as a model for enabling a convenient on demand network access
Cloud computing is defined by experts as a type of computing that relies on sharing computing resources rather than having local servers or personal devices to handle applications. The meaning behind the word cloud is that it is a metaphor for the entire online web and its data as well. A cloud service differs from traditional hosting in three different ways. These three differences are that cloud computing is elastic, it is sold on demand, and the service is managed by the provider of the cloud. The easiest way to explain what cloud computing does is that it stores and gives access to different data and programs over the internet rather than just your computer’s hard drive. For it to be actually considered cloud computing it must include data or programs over the internet. Cloud computing can be done anytime, anywhere with an online connection.
In a larger cluster,an extra NameNode called secondary NameNode is configured to avoid single point of failure .HDFS is managed with dedicated NameNode to host the file system index, and secondary NameNode can generate snapshots of namenode's memory structures.In this way ,it preventing file-system errors or corruption and reducing data loss. Similarly, job scheduling can manage through a standalone JobTracker server. In clusters,the Hadoop MapReduce engine deployed against an alternate file system, the NameNode, DataNode,secondary NameNode.
Iansiti, M., & Herman, K. (2011). CA Technologies: Bringing the Cloud to Earth. Case Study, 24.
Google File System (GFS) was developed at Google to meet the high data processing needs. Hadoop’s Distributed File System (HDFS) was originally developed by Yahoo.Inc but it is maintained as an open source by Apache Software Foundation. HDFS was built based on Google’s GFS and Map Reduce. As the internet data was rapidly increasing there was a need to store the large data coming so Google developed a distributed file system called GFS and HDFS was developed to meet the different client needs. These are built on commodity hardware so the systems often fail. To make the systems reliable the data is replicated among multiple nodes. By default minimum number of replicas is 3. Millions of files and large files are common with these types of file systems. Data is more often read than writing. Large streaming needs and small random needs are supported.
Cloud computing is the transfer of computing data or information into Internet. Cloud computing services allows individuals and businesses to
We face the new paradigm of “cloud” computing, in which anything that can be done in
There is a lot of buzz about “the Cloud” and what it can and cannot do for IT departments. A wide range of products and services are lumped into the phrase “Cloud computing.” While the strict definition of a cloud speaks mainly to a collection of easily deployed virtual servers, it also encompasses vendors of outsourced exchange servers, preconfigured CRM applications, web-enabled word processing applications, and online backup services (Gohring, 2013).
The cloud computing is the practice that enables access to the shared pool of configurable computing resources which can be dynamically provisioned. It refers to both the applications delivered as service as well as hardware and system software in the data centres that provide those services. The attractive features of cloud computing such as on-demand access, high scalability, reliability, cost savings, low maintenance and energy efficiency bring benefits to both cloud service consumers and providers.
Big Data is a term used to refer to extremely large and complex data sets that have grown beyond the ability to manage and analyse them with traditional data processing tools. However, Big Data contains a lot of valuable information which if extracted successfully, it will help a lot for business, scientific research, to predict the upcoming epidemic and even determining traffic conditions in real time. Therefore, these data must be collected, organized, storage, search, sharing in a different way than usual. In this article, invite you and learn about Big Data, methods people use to exploit it and how it helps our life.
The fourth characteristic of cloud computing is broad network access. The applications that are available through cloud services are accessible through a variety of devices and locations, allowing users to access applications through various types of storage not limited to the local hard drive. Furthermore, with cloud computing, users can access applicat...
Abstract—High Performance Computing (HPC) provides support to run advanced application programs efficiently. Java adaptation in HPC has become an apparent choice for new endeavors, because of its significant characteristics. These include object-oriented, platform independent, portable, secure, built-in networking, multithreading, and an extensive set of Application Programming Interfaces (APIs). Consequently multi-core systems and multi-core programming tools are becoming popular. However, today the leading HPC programming model is Message Passing Interface (MPI). In present day computing, while writing a parallel program for multi-core systems in distributed environment may deploy an approach where both shared and distributed memory models are used. Moreover an interoperable, asynchronous, and reliable working environment is required for programmers and researchers to build the HPC applications. This paper reviews the existing MPI implementations in Java. Several assessment parameters are identified to analyze the Java based MPI models; including their strengths and weaknesses.
Big data originated with web search companies that encountered problems with querying large amounts of both structured and unstructured data. With regard to its background, “big data came into being when web search companies developed ways to perform distributed computing on large data sets on computer clusters” Floyer (2014: 1). Big data then spread to enterprises due to their adoption of developing, processing and dissemination of data.
This white paper identifies some of the considerations and techniques which can significantly improve the performance of the systems handling large amounts of data.
In cloud computing, the word cloud is used as a metaphor for “the internet”. So the cloud computing means “a type of internet-based computing”, where different services such as servers, storage and applications are delivered to an organization’s computers and devices through the internet.