Current Issue : January - March Volume : 2012 Issue Number : 1 Articles : 8 Articles
Courseware must work. In this work, we verify the synthesis of 128 bit architectures,\r\nwhich embodies the intuitive principles of hardware and architecture. Our objective\r\nhere is to set the record straight. In order to realize this objective, we disprove not only\r\nthat expert systems and evolutionary programming can agree to answer this riddle, but that the same is true for superpages [1]....
Information-communications systems, consisting of three core categories: information (content), communication mechanism (currently dominated by Internet), and services (data/information processing, content delivery, etc.) were changing over time from the distributed processing to the cloud computing. Current cloud computing development gives the basis for delegated information processing deployment. These systems differentiate from traditional distributed data processing that was the predecessor to the information-communications systems development. Computer communities assume most of the structural and functional characteristics of the business communities and ecosystems that evolve in their complexity and functionality. Thus, in the context of information-communications systems development process, started with the distributed data processing systems and maturating through the deployment of grid and cloud computing, there is the need for delegated information processing systems that build new information-communications ecosystem. It is a digital environment populated by digital units presented by software components, applications, services, information, information processing models, etc. It is close to the term of digital ecosystem, which is in the same time a network where nodes can be added or removed allowing delegated person, machine, service or application to interact with or share the data. Basic conceptual issues and the ecosystem model are presented in order to introduce novelty in the field of data processing management architecture, and to distinguish distributed processing model from the grid and cloud semantic architectures. The delegated information processing is introduced as the platform that should incorporate the most acceptable elements from the grid and cloud computing, providing business community with the new information processing paradigm. Delegated information processing, as a new information-communications ecosystem, comprises also a complexity of security and privacy issues, which are presented with the thoughts on new areas of research....
Medical technologies are indispensable to modern medicine. However, they have become exceedingly expensive and complex and are not available to the economically disadvantaged majority of the world population in underdeveloped as well as developed parts of the world. For example, according to the World Health Organization about two thirds of the world population does not have access to medical imaging. In this paper we introduce a new medical technology paradigm centered on wireless technology and cloud computing that was designed to overcome the problems of increasing health technology costs. We demonstrate the value of the concept with an example; the design of a wireless, distributed network and central (cloud) computing enabled three-dimensional (3-D) ultrasound system. Specifically, we demonstrate the feasibility of producing a 3-D high end ultrasound scan at a central computing facility using the raw data acquired at the remote patient site with an inexpensive low end ultrasound transducer designed for 2-D, through a mobile device and wireless connection link between them. Producing high-end 3D ultrasound images with simple low-end transducers reduces the cost of imaging by orders of magnitude. It also removes the requirement of having a highly trained imaging expert at the patient site, since the need for hand-eye coordination and the ability to reconstruct a 3-D mental image from 2-D scans, which is a necessity for high quality ultrasound imaging, is eliminated. This could enable relatively untrained medical workers in developing nations to administer imaging and a more accurate diagnosis, effectively saving the lives of people....
This paper discusses variant implementations of an MIPOG strategy based on our earlier work. Here, we adopt more scalable design and implementation for the MIPOG strategy. In doing so, a grid-based implementation is proposed; namely Grid_MIPOG. Unlike the previous implementation of MIPOG and MC_MIPOG, GRID_MIPOG utilizes the computing power from loosely coupled machines. Here, Grid_MIPOG provides more speedup and better memory distribution as far as the numbers of parameters, number of variables, and the strength of coverage are concerned....
Background\r\nClouds and MapReduce have shown themselves to be a broadly useful approach to scientific computing especially for parallel data intensive applications. However they have limited applicability to some areas such as data mining because MapReduce has poor performance on problems with an iterative structure present in the linear algebra that underlies much data analysis. Such problems can be run efficiently on clusters using MPI leading to a hybrid cloud and cluster environment. This motivates the design and implementation of an open source Iterative MapReduce system Twister.\r\nResults\r\nComparisons of Amazon, Azure, and traditional Linux and Windows environments on common applications have shown encouraging performance and usability comparisons in several important non iterative cases. These are linked to MPI applications for final stages of the data analysis. Further we have released the open source Twister Iterative MapReduce and benchmarked it against basic MapReduce (Hadoop) and MPI in information retrieval and life sciences applications.\r\nConclusions\r\nThe hybrid cloud (MapReduce) and cluster (MPI) approach offers an attractive production environment while Twister promises a uniform programming environment for many Life Sciences applications.\r\nMethods\r\nWe used commercial clouds Amazon and Azure and the NSF resource FutureGrid to perform detailed comparisons and evaluations of different approaches to data intensive computing. Several applications were developed in MPI, MapReduce and Twister in these different environments....
Background\r\nSince the introduction of next-generation DNA sequencers the rapid increase in sequencer throughput, and associated drop in costs, has resulted in more than a dozen human genomes being resequenced over the last few years. These efforts are merely a prelude for a future in which genome resequencing will be commonplace for both biomedical research and clinical applications. The dramatic increase in sequencer output strains all facets of computational infrastructure, especially databases and query interfaces. The advent of cloud computing, and a variety of powerful tools designed to process petascale datasets, provide a compelling solution to these ever increasing demands.\r\nResults\r\nIn this work, we present the SeqWare Query Engine which has been created using modern cloud computing technologies and designed to support databasing information from thousands of genomes. Our backend implementation was built using the highly scalable, NoSQL HBase database from the Hadoop project. We also created a web-based frontend that provides both a programmatic and interactive query interface and integrates with widely used genome browsers and tools. Using the query engine, users can load and query variants (SNVs, indels, translocations, etc) with a rich level of annotations including coverage and functional consequences. As a proof of concept we loaded several whole genome datasets including the U87MG cell line. We also used a glioblastoma multiforme tumor/normal pair to both profile performance and provide an example of using the Hadoop MapReduce framework within the query engine. This software is open source and freely available from the SeqWare project (http://seqware.sourceforge.net webcite).\r\nConclusions\r\nThe SeqWare Query Engine provided an easy way to make the U87MG genome accessible to programmers and non-programmers alike. This enabled a faster and more open exploration of results, quicker tuning of parameters for heuristic variant calling filters, and a common data interface to simplify development of analytical tools. The range of data types supported, the ease of querying and integrating with existing tools, and the robust scalability of the underlying cloud-based technologies make SeqWare Query Engine a nature fit for storing and searching ever-growing genome sequence datasets....
The use of cloud computing is rapidly growing in all over the world. The clouds of information technology are commonly referred to as ââ?¬Å?Cloud Computingââ?¬Â. Cloud computing is a general term for anything that involves delivering hosted services over the Internet. Cloud computing is the next big thing after the Internet and it will revolutionize the way IT services are provided, due to its many advantages like Highly scalable, on-demand, web-accessed IT resources with major cost and flexibility. Various companies around the world using cloud computing as a means to increasing efficiency and reducing cost of their IT services. In this research paper efforts have been made to analyze the use of hybrid cloud computing model with security and scalability in business and information system. There are many challenges in using cloud computing. The main challenges are security and because all essential services are generally outsourced to a third party. The outsourcing makes it harder to maintain data integrity and privacy, security of data etc. Using public cloud model only in the business is very risky because of its security reasons and using private cloud only will not solve our purpose because in that case we are not be able to use advantages of public cloud model. To solve these security problems in business and information system we can use hybrid cloud computing model where we can use advantages of public cloud and security of private cloud, in which we can elect to store highly sensitive data of the company in the private storage cloud and less sensitive data in public storage cloud. This research mainly focused upon the security problems in business and information system. Research suggests a hybrid cloud computing model where converging advantages of public cloud and security of private cloud can be used....
Cloud computing in one of the hottest topics in enterprise today. It is lot of further along than science project. Whenever we talk of cloud computing, we always talk about its impact on business. In all my previous articles, I have done the same, speaking about how cloud computing can improve efficiencies, cut costs, save time and in general, give businesses a great return on investment. However, today I am going to speak on something quite different ââ?¬â?? how cloud computing can help in the noblest human pursuit of all, education. The worth of human society is not in how much it earns but how much it knows. For it is knowledge that drives advancement, and ultimately, human comfort. And is not comfort the ultimate aim of increased earnings? However, the worth of knowledge goes far beyond the limitations of material wealth. It is knowledge that makes man, Man. That being said, I believe that cloud computing has a prominent role to play in the classrooms of tomorrow. Let me provide a few examples. Many of our nationââ?¬â?¢s schools suffer from low graduation rates directly attributable to insufficient infrastructure ââ?¬â?? shorthanded staff, tiny classrooms, lack of teachers. Cloud computing solutions can solve many of these problems....
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