The cloudcomputing basic idea was given by 1960 by Professor John, "The future computers will be just like, the telephone services and according to requirement we use their services"and this computer idea h...
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Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and other pressing scientific challenges. These computations produce a tremendous amount of data;however, many of the pr...
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ISBN:
(纸本)9780769543024
Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and other pressing scientific challenges. These computations produce a tremendous amount of data;however, many of the programs used to analyze this data currently only run a single processor. In this work, we explore the possibility of using the emerging cloudcomputing platform to parallelize such sequential data analysis tasks. As a proof of concept, we wrap a program for analyzing trends of tropical cyclones in a set of virtual machines (VMs). This approach allows the user to keep their familiar data analysis environment in the VMs, while we provide the coordination and data transfer services to ensure the necessary input and output are directed to the desired locations. This work extensively exercises the networking capability of the cloudcomputing systems and has revealed a number of weaknesses in the current cloud system software. In our tests, we are able to scale the parallel data analysis job to a modest number of VMs and achieve a speedup that is comparable to running the same analysis task using MPI. However, compared to MPI based parallelization, the cloud-based approach has a number of advantages. The cloud-based approach is more flexible because the VMs can capture arbitrary software dependencies without requiring the user to rewrite their programs. The cloud-based approach is also more resilient to failure;as long as a single VM is running, it can make progress while as soon as one MPI node fails the whole analysis job fails. In short, this initial work demonstrates that a cloudcomputing system is a viable platform for distributed scientific data analyses traditionally conducted on dedicated supercomputing systems.
Meteorology gridcomputing aims to provide scientist with seamless, reliable, secure and inexpensive access to meteorological resources. In this paper, we presented a semantic-based meteorology grid service registry, ...
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Simple Web services can be provided directly from one mobile device acting as a server. However, complex services need a mobile cloud to provide computing resources and infrastructure to support seamless provision of ...
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Meteorology gridcomputing aims to provide scientist with seamless, reliable, secure and inexpensive access to meteorological resources. In this paper, we presented a semantic-based meteorology grid service registry, ...
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The idea of multi-cloudcomputing has broadened the field of cloudcomputing and has emerged as a popular term currently. The term "multi-cloud"refers to the use of services from numerous heterogeneous cloud...
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Currently cloudcomputing (CC) has dramatic changes in secured task scheduling in emerging countries, the volume of the company must cost-effectively process large amounts of data security to process the data for solv...
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Model-based Systems engineering plays a pivotal role in the design of distributed embedded systems by enabling early virtual integration of the different parts of the system. Traditionally, the system model is compose...
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ISBN:
(纸本)9781467394734
Model-based Systems engineering plays a pivotal role in the design of distributed embedded systems by enabling early virtual integration of the different parts of the system. Traditionally, the system model is composed of subsystem models at the same level of abstraction and with one particular view. However, in some cases the system model may comprise subsystem models at different levels of abstraction. Integration of these different abstraction level models imposes some important drawbacks which hinder the overall system simulations. These drawbacks need to be addressed to facilitate the simulation of systems composed with multi-level subsystem models. In this paper we report on modelling techniques for embedded and distributed systems to deal with this heterogeneity. We describe a methodology to (semi-)automatically generate an executable multi-level system simulation model starting from an abstract system architecture of the system. A platooning system example is used to demonstrate the new modelling techniques.
Although grid systems andgridcomputing have greatly evolved during the past few years, parallel application support remains somewhat limited. A new method for integrating parallel applications as grid services is pr...
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ISBN:
(纸本)9789898111555
Although grid systems andgridcomputing have greatly evolved during the past few years, parallel application support remains somewhat limited. A new method for integrating parallel applications as grid services is presented. This method assumes that underlying parallel applications are resources for grid services;also, it implies that service resources may be clients for some predefined helper grid services. The design of the grid service is based on a Factory Service / Instance Service architecture, aiming to offer support for managing multiple resources. The tests were performed on the GRAI grid (Academic grid for Complex Applications), using Globus Toolkit 4 - versions 4.0.3 and 4.0.5 - as the base middleware.
Split-protocol computing paradigm uses web services on geographically distributed Web servers. A network of large Split-servers that form the cloud to handles computing and storage task that would otherwise create a h...
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ISBN:
(纸本)9781467393003
Split-protocol computing paradigm uses web services on geographically distributed Web servers. A network of large Split-servers that form the cloud to handles computing and storage task that would otherwise create a heavy CPU utilization for the traditional individual server. The split-protocol concept was devised for load balancing and faster data transmission. Connection and data communication phases are clearly divided between servers without involving the client or the central controlling mechanism, like a dispatcher or a load balancer. In an earlier paper, we demonstrated that the application Split-protocol produces higher performance compared to traditional clusters. Based on the need, different types of split configurations are implemented for throughput, response time, and connection time. The observed throughput improvement was within the range 6.5% - 25% over non-split systems. This paper first time examines the empirical results of Split-system to understand its analytical behavior and compares with traditional non-split systems. Also, this paper prepares the groundwork for the scientific understanding of Split-systems. The split-system technique with given sets of constraints can produce better throughput than conventional equivalent server systems. The performance improvement resulted because of the Split-system operates as a fine-grained pipeline of the parallel system.
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