一种基于容错集群计算的图像复杂度测量方法

D. Z. Rodríguez, R. L. Rosa, Eduardo Costa Alfaia
{"title":"一种基于容错集群计算的图像复杂度测量方法","authors":"D. Z. Rodríguez, R. L. Rosa, Eduardo Costa Alfaia","doi":"10.1109/AICT.2010.30","DOIUrl":null,"url":null,"abstract":"The cluster computing is widely used for image processing in entertainment applications. Measuring the required number of nodes to be used in a cluster computing helps saving nodes processing time, even if this occurs on a fault tolerant scenario. The paper analyzes the images rendering process by ray tracing on the cluster computing using the freeware software fault tolerant message-passing interface with Povray software in a Linux-based operating system. This paper uses a simple method of image complexity measure, it is shown that depending on the images complexity level, a minimum number of cluster nodes is chose to render the image instead of using all the cluster nodes. It is useful to save machine processing time and meanwhile another image can be rendered in a parallel process with a previous one and where the solution is applied in a Fault Tolerant scenario, so independent of the network fault, the cluster continues working.","PeriodicalId":339151,"journal":{"name":"2010 Sixth Advanced International Conference on Telecommunications","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Simple Method to Measure the Image Complexity on a Fault Tolerant Cluster Computing\",\"authors\":\"D. Z. Rodríguez, R. L. Rosa, Eduardo Costa Alfaia\",\"doi\":\"10.1109/AICT.2010.30\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The cluster computing is widely used for image processing in entertainment applications. Measuring the required number of nodes to be used in a cluster computing helps saving nodes processing time, even if this occurs on a fault tolerant scenario. The paper analyzes the images rendering process by ray tracing on the cluster computing using the freeware software fault tolerant message-passing interface with Povray software in a Linux-based operating system. This paper uses a simple method of image complexity measure, it is shown that depending on the images complexity level, a minimum number of cluster nodes is chose to render the image instead of using all the cluster nodes. It is useful to save machine processing time and meanwhile another image can be rendered in a parallel process with a previous one and where the solution is applied in a Fault Tolerant scenario, so independent of the network fault, the cluster continues working.\",\"PeriodicalId\":339151,\"journal\":{\"name\":\"2010 Sixth Advanced International Conference on Telecommunications\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Sixth Advanced International Conference on Telecommunications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AICT.2010.30\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Sixth Advanced International Conference on Telecommunications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICT.2010.30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

集群计算被广泛应用于娱乐应用中的图像处理。测量集群计算所需的节点数量有助于节省节点处理时间,即使是在容错场景中也是如此。本文在linux操作系统下,利用免费软件Povray容错消息传递接口,分析了在集群计算中光线追踪图像绘制过程。本文采用一种简单的图像复杂度度量方法,根据图像的复杂程度,选择最小数量的集群节点来渲染图像,而不是使用所有的集群节点。这有利于节省机器处理时间,同时可以在与前一个图像并行的过程中呈现另一个图像,并且在容错场景中应用该解决方案,因此独立于网络故障,集群继续工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Simple Method to Measure the Image Complexity on a Fault Tolerant Cluster Computing
The cluster computing is widely used for image processing in entertainment applications. Measuring the required number of nodes to be used in a cluster computing helps saving nodes processing time, even if this occurs on a fault tolerant scenario. The paper analyzes the images rendering process by ray tracing on the cluster computing using the freeware software fault tolerant message-passing interface with Povray software in a Linux-based operating system. This paper uses a simple method of image complexity measure, it is shown that depending on the images complexity level, a minimum number of cluster nodes is chose to render the image instead of using all the cluster nodes. It is useful to save machine processing time and meanwhile another image can be rendered in a parallel process with a previous one and where the solution is applied in a Fault Tolerant scenario, so independent of the network fault, the cluster continues working.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信