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Robust Optimization for Resource Allocation in Cloud Providers

云提供商资源分配的稳健优化

基本信息

批准号：
21K17733
负责人：
HE FUJUN
金额：
$ 2.75万
依托单位：
Kyoto University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Early-Career Scientists
财政年份：
2021
资助国家：
日本
起止时间：
2021-04-01 至 2022-03-31
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-21K17733/
关键词：
robust optimization resource allocation NFV queueing theory cloud computing probabilistic protection survivability

项目摘要

Three articles (one as the 1st author) have been accepted by high-level conferences; one article (1st author) has been published at a top-level journal. Three journal articles have been submitted. These works focused on resource allocation problems in different applications; it includes cloud computing and network function virtualization (NFV), where network failures and traffic uncertainty typically exist, which degrade the network performance.One work developed a backup computing and transmission resource allocation model against multiple node failures. Probabilistic protection is provided for computing resource to reduce the required computing capacity. It analyzed backup transmission resource sharing in the case of multiple failures to compute the minimum required backup transmission capacity. With our analyses, a network operator can set an appropriate degree of backup transmission resource sharing based on practical requirements. For future extensions, we plan to apply probabilistic protection for both computing and transmission resources to further reduce the required network resources.Another work introduced a robust optimization model to handle the traffic uncertainty for service deployment in NFV. It provided different approaches to solve the deployment problem. Based on it, a network operator can develop services against traffic uncertainty in a cost-efficient way. For future work, we plan to address a more accurate model to further reduce the deployment cost introduced by conservative approximation in the current one.

3篇文章（1篇为第一作者）已被高级别会议接受; 1篇文章（第一作者）已在顶级期刊上发表。已提交三篇期刊文章。这些工作集中在不同的应用程序中的资源分配问题，它包括云计算和网络功能虚拟化（NFV），其中网络故障和流量的不确定性通常存在，这会降低网络性能。为计算资源提供概率保护，以减少所需的计算能力。分析了多故障情况下的备用传输资源共享问题，计算出所需的最小备用传输容量。通过我们的分析，网络运营商可以根据实际需求设置适当程度的备份传输资源共享。在未来的扩展中，我们计划对计算和传输资源应用概率保护，以进一步减少所需的网络资源。另一项工作引入了一个鲁棒的优化模型来处理NFV中服务部署的流量不确定性。它提供了不同的方法来解决部署问题。在此基础上，网络运营商可以以具有成本效益的方式开发针对流量不确定性的服务。对于未来的工作，我们计划解决一个更准确的模型，以进一步减少部署成本所引入的保守近似在当前的。