CAREER: Theory and Algorithms for Efficient Control of Wireless Networks with Jointly Optimized Performance: High Throughput, Low Delay, and Low Complexity

职业:具有联合优化性能的无线网络高效控制的理论和算法:高吞吐量、低延迟和低复杂性

基本信息

  • 批准号:
    1651947
  • 负责人:
  • 金额:
    $ 49.68万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-05-01 至 2021-02-28
  • 项目状态:
    已结题

项目摘要

With the advent of smart devices and the Internet of things, wireless technology has spawned a plethora of services that span business, science and engineering, entertainment, safety and security, health monitoring, and cover a large portion of our social interactions. Due to the prevalence of these new services, today's wireless networks are witnessing not only an unprecedented growth in the volume of traffic, but also a significant change in the types of traffic (e.g., a much higher percentage of voice/video traffic with more stringent delay requirements). These new trends require next-generation wireless networks to provide not only high data rates (tens of gigabits per second), but also ultra-low latencies (sub-millisecond). Moreover, as wireless networks grow and support an increasingly large number of users, network control algorithms must also incur low complexity in order to be implemented in practice. However, the question of how to simultaneously achieve high throughput, low delay and low complexity remains largely open. Addressing this major research challenge is a main goal of this project. Not only is this research expected to substantially advance our understanding of designing efficient control algorithms for wireless networks with jointly optimized performance, but it would also expand/create the much-needed theoretical foundations for developing simple and practical protocols to optimize the key performance metrics needed in the design of next-generation wireless networks. This research will also be closely integrated with a comprehensive educational plan, which is focused on providing research experiences to undergraduate and K-12 students, recruiting and training underrepresented students, and engaging in curriculum development activities. The goal of this project is to create new theoretical foundations for designing provably efficient network control algorithms that perform well in all three dimensions of throughput, delay, and complexity. Specifically, this research will be carried out around three main thrusts: (i) it focuses on intra-cell control for a multi-channel cellular network, and aims to build a theoretical framework for designing low-complexity scheduling algorithms with provably guaranteed optimal throughput and optimal (or near-optimal) large-deviations delay rate-function; (ii) it considers a more challenging setting of network-wide control for larger systems (e.g., a dense multi-cell system or an ad hoc wireless network), and aims to develop a new node-based approach for designing efficient scheduling algorithms with provable throughput and evacuation time performance; and (iii) it considers distributed network-side control and aims to design low-complexity algorithms that achieve high throughput and low delay.
随着智能设备和物联网的出现,无线技术催生了大量服务,涵盖了商业、科学和工程、娱乐、安全和安保、健康监测,并覆盖了我们大部分的社交活动。由于这些新服务的普及,今天的无线网络不仅见证了流量的空前增长,而且还见证了流量类型的显著变化(例如,具有更严格的延迟要求的语音/视频流量的比例要高得多)。这些新趋势要求下一代无线网络不仅要提供高数据速率(每秒数百吉比特),还要提供超低延迟(亚毫秒)。此外,随着无线网络的发展和支持越来越多的用户,网络控制算法也必须产生较低的复杂性才能在实践中实现。然而,如何同时实现高吞吐量、低延迟和低复杂度的问题在很大程度上仍然悬而未决。解决这一重大研究挑战是该项目的主要目标。这项研究不仅有望大大提高我们对设计具有联合优化性能的无线网络的高效控制算法的理解,而且还将扩展/创建急需的理论基础,用于开发简单实用的协议,以优化下一代无线网络设计所需的关键性能指标。这项研究还将与一项全面的教育计划密切结合,该计划的重点是向本科生和K-12学生提供研究经验,招收和培训代表性不足的学生,并参与课程开发活动。本项目的目标是为设计在吞吐量、延迟和复杂性这三个方面都表现良好的高效网络控制算法创造新的理论基础。具体地说,本研究将围绕三个主要方面展开:(I)针对多信道蜂窝网络的小区内控制,旨在建立一个理论框架来设计具有可证明保证的最优吞吐量和最优(或接近最优)大偏差延迟率函数的低复杂度调度算法;(Ii)考虑对于较大系统(例如,密集多小区系统或自组织无线网络)更具挑战性的全网控制设置,并旨在开发一种新的基于节点的方法来设计具有可证明吞吐量和疏散时间性能的高效调度算法;它考虑分布式网络侧控制,旨在设计低复杂度的算法,以实现高吞吐量和低延迟。

项目成果

期刊论文数量(23)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Combinatorial Sleeping Bandits With Fairness Constraints
Enabling Fair Spectrum Sharing between Wi-Fi and LTE-Unlicensed
Joint Placement and Allocation of VNF Nodes With Budget and Capacity Constraints
Providing wireless coverage to high-rise buildings using UAVs
Age-based Scheduling: Improving Data Freshness for Wireless Real-Time Traffic
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Bo Ji其他文献

A moving weak and small target detection algorithm for multispectral image sequences
多光谱图像序列的运动弱小目标检测算法
Algal Toxins in Water
水中的藻类毒素
  • DOI:
    10.1002/047147844x.wq23
  • 发表时间:
    2005
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Bo Ji;M. Wong;R. Wong;Yu’e Jiang
  • 通讯作者:
    Yu’e Jiang
Deep Learning Models for Biomedical Image Analysis
用于生物医学图像分析的深度学习模型
Securing Bystander Privacy in Mixed Reality While Protecting the User Experience
保护混合现实中的旁观者隐私,同时保护用户体验
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    1.9
  • 作者:
    Matthew Corbett;Brendan David;Jiacheng Shang;Y. C. Hu;Bo Ji
  • 通讯作者:
    Bo Ji
Diagnosis Expert System for Oesophagus Cancer in Early Stage
食管癌早期诊断专家系统

Bo Ji的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Bo Ji', 18)}}的其他基金

Collaborative Research: NeTS: Medium: Black-box Optimization of White-box Networks: Online Learning for Autonomous Resource Management in NextG Wireless Networks
合作研究:NeTS:中:白盒网络的黑盒优化:下一代无线网络中自主资源管理的在线学习
  • 批准号:
    2312833
  • 财政年份:
    2023
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Medium: Information Freshness in Scalable and Energy Constrained Machine to Machine Wireless Networks
合作研究:CNS 核心:中:可扩展且能量受限的机器对机器无线网络中的信息新鲜度
  • 批准号:
    2106427
  • 财政年份:
    2021
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
NSF Student Travel Grant for 2020 ACM International Conference on Measurement and Modeling of Computer Systems (ACM SIGMETRICS 2020)
NSF 学生旅费资助 2020 年 ACM 国际计算机系统测量和建模会议 (ACM SIGMETRICS 2020)
  • 批准号:
    2013729
  • 财政年份:
    2020
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Standard Grant
NSF Student Travel Grant for 2020 ACM International Conference on Measurement and Modeling of Computer Systems (ACM SIGMETRICS 2020)
NSF 学生旅费资助 2020 年 ACM 国际计算机系统测量和建模会议 (ACM SIGMETRICS 2020)
  • 批准号:
    2110139
  • 财政年份:
    2020
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Standard Grant
CAREER: Theory and Algorithms for Efficient Control of Wireless Networks with Jointly Optimized Performance: High Throughput, Low Delay, and Low Complexity
职业:具有联合优化性能的无线网络高效控制的理论和算法:高吞吐量、低延迟和低复杂性
  • 批准号:
    2112694
  • 财政年份:
    2020
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
CRII: CIF: Models, Theories and Algorithms for Timeliness Optimization in Information-update Systems
CRII:CIF:信息更新系统时效性优化的模型、理论和算法
  • 批准号:
    1657162
  • 财政年份:
    2017
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Standard Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
基于isomorph theory研究尘埃等离子体物理量的微观动力学机制
  • 批准号:
    12247163
  • 批准年份:
    2022
  • 资助金额:
    18.00 万元
  • 项目类别:
    专项项目
Toward a general theory of intermittent aeolian and fluvial nonsuspended sediment transport
  • 批准号:
  • 批准年份:
    2022
  • 资助金额:
    55 万元
  • 项目类别:
英文专著《FRACTIONAL INTEGRALS AND DERIVATIVES: Theory and Applications》的翻译
  • 批准号:
    12126512
  • 批准年份:
    2021
  • 资助金额:
    12.0 万元
  • 项目类别:
    数学天元基金项目
基于Restriction-Centered Theory的自然语言模糊语义理论研究及应用
  • 批准号:
    61671064
  • 批准年份:
    2016
  • 资助金额:
    65.0 万元
  • 项目类别:
    面上项目

相似海外基金

CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
CAREER: Theory and Algorithms for Learning with Frozen Pretrained Models
职业:使用冻结的预训练模型进行学习的理论和算法
  • 批准号:
    2339978
  • 财政年份:
    2024
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
CAREER: Continual Learning with Evolving Memory, Soft Supervision, and Cross-Domain Knowledge - Foundational Theory and Advanced Algorithms
职业:利用进化记忆、软监督和跨领域知识进行持续学习——基础理论和高级算法
  • 批准号:
    2338506
  • 财政年份:
    2024
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
CAREER: Theory for Dynamic Graph Algorithms
职业:动态图算法理论
  • 批准号:
    2238138
  • 财政年份:
    2023
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
CAREER: Parallel Algorithms: Theory for Practice
职业:并行算法:理论实践
  • 批准号:
    2238358
  • 财政年份:
    2023
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
CAREER: Developing a unified theory of descriptive combinatorics and local algorithms
职业:发展描述性组合学和局部算法的统一理论
  • 批准号:
    2239187
  • 财政年份:
    2023
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
CAREER: Learning Kernels in Operators from Data: Learning Theory, Scalable Algorithms and Applications
职业:从数据中学习算子的内核:学习理论、可扩展算法和应用
  • 批准号:
    2238486
  • 财政年份:
    2023
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
CAREER: Toward Real-Time, Constraint-Aware Control of Complex Dynamical Systems: from Theory and Algorithms to Software Tools
职业:实现复杂动力系统的实时、约束感知控制:从理论和算法到软件工具
  • 批准号:
    2238424
  • 财政年份:
    2023
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Standard Grant
CAREER: Efficient Uncertainty Quantification in Turbulent Combustion Simulations: Theory, Algorithms, and Computations
职业:湍流燃烧模拟中的高效不确定性量化:理论、算法和计算
  • 批准号:
    2143625
  • 财政年份:
    2022
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
CAREER: Nonsmooth Control Systems for Societal Networks with Data-Assisted Feedback Loops: Theory and Algorithms
职业:具有数据辅助反馈环的社会网络的非平滑控制系统:理论和算法
  • 批准号:
    2305756
  • 财政年份:
    2022
  • 资助金额:
    $ 49.68万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了