CNS Core: Small: RUI: Optimal and Efficient Resource Allocation in Policy-Driven Data Centers: A Network Flow Approach
CNS Core: Small: RUI: Optimal and Efficient Resource Allocation in Policy-Driven Data Centers: A Network Flow Approach
批准号:
1911191
负责人:
Bin Tang
金额:
$35.43万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-10-01 至 2023-09-30
中文摘要
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英文摘要
Emerging data- and communication-intensive applications such as online video streaming, social media, health and medical applications, scientific applications including high-energy physics and bioinformatics, and educational applications (such as the rapidly-growing Massive Open Online Courses) are all enabled by large cloud data centers. However, this underpinning infrastructure is increasingly stressed by the growing complexities of managing data center resources. This is evidenced by the frequent outages of cloud services from leading tech companies, including Amazon Cloud Storage and Microsoft Skype, and popular mobile apps such as Gmail and Whatsapp. To address this challenge, this project will create an optimal and efficient resource allocation framework for policy driven data centers (PDDCs), to manage cloud user applications and cloud resources (i.e., servers, networks, and power) in an integrated fashion. The goal of this project is to integrate compute, data, and middleboxes (MBs), three building blocks of PDDCs, into one framework to achieve optimal cloud resource management. A variety of important problems in PDDCs, including virtual machine (VM) migration and placement, load balancing, flow priority and fault tolerance can all be solved using network flow techniques that provide optimal and efficient resource allocation solutions. In particular, the project identifies a series of new policy-preserving problems that adaptively coordinate compute, data, and MBs, and invents a suite of policy-preserving algorithms that satisfy diverse cloud policies while consuming cloud resources efficiently. The proposed techniques include placing, migrating, replicating, and traffic engineering compute, data, and MBs in the PDDC. The project will compare results with integer linear programming (ILP)-based solutions and extend the approach to multi-objective optimization problems. Expected outcomes are fundamental theories, architectures, algorithms, and protocols for the PDDCs, and prototypes that provide long term policy-preserving cloud services.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(11)
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科研奖励(0)
会议论文
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DOI:
10.1109/ipdps53621.2022.00094
发表时间:
2022-05
期刊:
2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
影响因子:
--
作者:
[Vincent Tran;Jingsong Sun;Bin Tang;Deng Pan]
通讯作者:
Vincent Tran;Jingsong Sun;Bin Tang;Deng Pan
DOI:
10.1109/icccn54977.2022.9868897
发表时间:
2022-07
期刊:
2022 International Conference on Computer Communications and Networks (ICCCN)
影响因子:
--
作者:
[Enrique Rodicio;Deng Pan;Jason Liu;Bin Tang]
通讯作者:
Enrique Rodicio;Deng Pan;Jason Liu;Bin Tang
DOI:
10.1109/infocom41043.2020.9155472
发表时间:
2020-07
期刊:
IEEE INFOCOM 2020 - IEEE Conference on Computer Communications
影响因子:
--
作者:
[Hugo Flores;Vincent Tran;Bin Tang]
通讯作者:
Hugo Flores;Vincent Tran;Bin Tang
DRE2: Achieving Data Resilience in Wireless Sensor Networks: A Quadratic Programming
DRE2:在无线传感器网络中实现数据弹性:二次规划
DOI:
--
发表时间:
2020
期刊:
IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS 2020
影响因子:
--
作者:
[Hsu, Shanglin, Yu, Yuning, Tang, Bin]
通讯作者:
Tang, Bin
DOI:
10.1109/icc45855.2022.9839019
发表时间:
2022-05
期刊:
ICC 2022 - IEEE International Conference on Communications
影响因子:
--
作者:
[Phillip Aguilera;Christopher Gonzalez;Bin Tang]
通讯作者:
Phillip Aguilera;Christopher Gonzalez;Bin Tang
共 10 条
Collaborative Research: CISE-MSI: DP: CNS: An Edge-Based Approach to Robust Multi-Robot Systems in Dynamic Environments
-
批准号:2240517
-
项目类别:Standard Grant
-
资助金额:$9.5万
-
财政年份:2022
-
负责人:Bin Tang
-
依托单位:
NeTS: Small: Adaptive Data Preservation in Intermittently Connected Sensor Networks: A Unified Storage-Energy Optimization Approach
-
批准号:1419952
-
项目类别:Standard Grant
-
资助金额:$8.82万
-
财政年份:2013
-
负责人:Bin Tang
-
依托单位:
NeTS: Small: Adaptive Data Preservation in Intermittently Connected Sensor Networks: A Unified Storage-Energy Optimization Approach
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批准号:1248315
-
项目类别:Standard Grant
-
资助金额:$20.77万
-
财政年份:2012
-
负责人:Bin Tang
-
依托单位:
NeTS: Small: Adaptive Data Preservation in Intermittently Connected Sensor Networks: A Unified Storage-Energy Optimization Approach
-
批准号:1116849
-
项目类别:Standard Grant
-
资助金额:$29.39万
-
财政年份:2011
-
负责人:Bin Tang
-
依托单位:
国内基金
海外基金
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