在应用程序管理服务中度量和应用服务请求工作数据

Ying Li, K. Katircioglu
{"title":"在应用程序管理服务中度量和应用服务请求工作数据","authors":"Ying Li, K. Katircioglu","doi":"10.1109/SCC.2013.64","DOIUrl":null,"url":null,"abstract":"In Application Management Services (AMS), high resource utilization, effective resource planning and optimal assignment of service requests to resources are critical to success. Meeting these objectives requires a systematic and repeatable approach for determining the best way of measuring resource utilization, assessing workload and assigning service requests. In this paper, we present a two-step approach to help achieve the above objectives. We first measure the actual amount of effort that each resource spends on handling each service request (SR) based on a metadata model and a set of SR handling priority rules. Then, we proceed to measure resource utilization and assess SR assignment process based on the effort data calculated in step one.","PeriodicalId":370898,"journal":{"name":"2013 IEEE International Conference on Services Computing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Measuring and Applying Service Request Effort Data in Application Management Services\",\"authors\":\"Ying Li, K. Katircioglu\",\"doi\":\"10.1109/SCC.2013.64\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Application Management Services (AMS), high resource utilization, effective resource planning and optimal assignment of service requests to resources are critical to success. Meeting these objectives requires a systematic and repeatable approach for determining the best way of measuring resource utilization, assessing workload and assigning service requests. In this paper, we present a two-step approach to help achieve the above objectives. We first measure the actual amount of effort that each resource spends on handling each service request (SR) based on a metadata model and a set of SR handling priority rules. Then, we proceed to measure resource utilization and assess SR assignment process based on the effort data calculated in step one.\",\"PeriodicalId\":370898,\"journal\":{\"name\":\"2013 IEEE International Conference on Services Computing\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Services Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCC.2013.64\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Services Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCC.2013.64","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

在应用管理服务(AMS)中,高资源利用率、有效的资源规划和对资源的服务请求的最佳分配是成功的关键。要实现这些目标,需要一种系统的、可重复的方法来确定衡量资源利用、评估工作量和分配服务请求的最佳方法。在本文中,我们提出了一个两步走的方法来帮助实现上述目标。我们首先根据元数据模型和一组SR处理优先级规则度量每个资源在处理每个服务请求(SR)上花费的实际工作量。然后,基于第一步计算的工作数据,对资源利用率进行度量并评估SR分配过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Measuring and Applying Service Request Effort Data in Application Management Services
In Application Management Services (AMS), high resource utilization, effective resource planning and optimal assignment of service requests to resources are critical to success. Meeting these objectives requires a systematic and repeatable approach for determining the best way of measuring resource utilization, assessing workload and assigning service requests. In this paper, we present a two-step approach to help achieve the above objectives. We first measure the actual amount of effort that each resource spends on handling each service request (SR) based on a metadata model and a set of SR handling priority rules. Then, we proceed to measure resource utilization and assess SR assignment process based on the effort data calculated in step one.
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
期刊最新文献
IoT Mashup as a Service: Cloud-Based Mashup Service for the Internet of Things Cloud Service Negotiation: A Research Roadmap Formal Modeling of Elastic Service-Based Business Processes Security-Aware Resource Allocation in Clouds Integrated Syntax and Semantic Validation for Services Computing
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1