CRII: CNS: A Hybrid Software Defined Networking-Information Centric Networking Framework for the Reuse of Computation at the Network Edge

CRII：CNS：一种混合软件定义网络-以信息为中心的网络框架，用于在网络边缘重用计算

• 批准号: 2104700
• 负责人: Spyridon Mastorakis
• 金额: $ 17.47万
• 依托单位: University of Nebraska at Omaha
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2104700&HistoricalAwards=false
• 关键词: CRII; CNS; Hybrid; Software; Defined

The adoption of next-generation applications, such as Augmented Reality and Internet-of-Things (IoT), is expected to grow rapidly in the years to come. The number of IoT devices is expected to reach 75 billion by 2025, while the scale of potential use-cases (e.g., smart cities with hundreds of thousands or millions of residents) is also expected to grow. In such use-cases, users may request the processing of data with temporal, spatial, or semantic similarity by servers physically close to them. The repeated processing of considerably similar data may result in the same processing outputs and thus the execution of duplicate (redundant) computation. This project advances our understanding of the notion of “computation reuse”, where the processing outputs are reused/shared among processing requests for similar data, having the potential to: (i) reduce the time for the processing of similar data and thus the overall latency perceived by next-generation applications; and (ii) eliminate the execution of redundant computation, so that the available computing resources are effectively utilized. Our project will result in a novel network framework, so that requests for the processing of similar data are identified and forwarded to the same servers, facilitating the reuse of computation in realistic infrastructure deployments. The research outcomes of this project will be incorporated into university course curriculum, while this project will also offer opportunities that broaden participation and diversity in STEM.This project aims to advance the state-of-the art in edge computing architectures in order to facilitate the reuse of computation through a novel, hybrid network framework based on Information-Centric Networking (ICN)/Named-Data Networking (NDN) and Software-Defined Networking (SDN). The proposed framework capitalizes on the best of both ICN/NDN and SDN to realize a service-centric, computation reuse-aware, and “softwarized” architecture through: (i) the semantically meaningful ICN/NDN naming and stateful forwarding plane for the seamless and adaptive task forwarding towards edge servers that can reuse similar previously executed tasks; and (ii) the separation of forwarding and control planes and the programmable (logically) centralized SDN intelligence for the orchestration of the computation reuse semantics. This project will tackle fundamental challenges in the design and development of network systems for the realization of computation reuse in realistic edge computing environments, where multiple edge servers may be available for redundancy, fault tolerance, and load balancing purposes, facilitating the pervasive edge computing deployment.This project is jointly funded by Networking Technology and Systems(NeTS)program and the Established Program to Stimulate Competitive Research (EPSCoR).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.

下一代应用的采用，如增强现实和物联网（IoT），预计将在未来几年迅速增长。到2025年，物联网设备的数量预计将达到750亿，而潜在用例的规模（例如，拥有数十万或数百万居民的智能城市）也有望增长。在这样的用例中，用户可以请求物理上靠近他们的服务器处理具有时间、空间或语义相似性的数据。重复处理相当相似的数据可能会导致相同的处理输出，从而导致重复（冗余）计算的执行。该项目推进了我们对“计算重用”概念的理解，其中处理输出在对类似数据的处理请求之间被重用/共享，具有以下潜力：（i）减少处理类似数据的时间，从而减少下一代应用程序感知的整体延迟;以及（ii）消除冗余计算的执行，从而有效利用可用的计算资源。我们的项目将产生一个新的网络框架，以便识别处理类似数据的请求并将其转发到相同的服务器，从而促进在实际基础设施部署中重复使用计算。该项目的研究成果将被纳入大学课程，同时该项目也将提供扩大STEM参与和多样性的机会。该项目旨在推进边缘计算架构的最新技术，以促进计算的重用，基于信息中心网络（ICN）/命名数据网络（NDN）和软件定义网络（SDN）的混合网络框架。所提出的框架利用ICN/NDN和SDN两者的优点来实现以服务为中心的、计算重用感知的和“软件化”的架构，通过：（i）语义上有意义的ICN/NDN命名和有状态转发平面，用于向边缘服务器的无缝和自适应任务转发，边缘服务器可以重用类似的先前执行的任务;以及（ii）转发和控制平面的分离以及用于计算重用语义的编排的可编程（逻辑）集中式SDN智能。该项目将解决网络系统设计和开发中的基本挑战，以实现现实边缘计算环境中的计算重用，其中多个边缘服务器可用于冗余，容错和负载平衡目的，促进普及的边缘计算部署。该项目由网络技术和系统（NetTS）联合资助该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Reservoir: Named Data for Pervasive Computation Reuse at the Network Edge

• DOI: 10.1109/percom53586.2022.9762397
• 发表时间: 2021-12
• 期刊: 2022 IEEE International Conference on Pervasive Computing and Communications (PerCom)
• 作者: Md Washik Al Azad;Spyridon Mastorakis

The Promise and Challenges of Computation Deduplication and Reuse at the Network Edge

• DOI: 10.1109/mwc.010.2100575
• 发表时间: 2021-09
• 期刊: IEEE Wireless Communications
• 影响因子: 12.9
• 作者: Md Washik Al Azad;Spyridon Mastorakis

An Information Centric Framework for Weather Sensing Data

以信息为中心的天气传感数据框架

• DOI: 10.1109/iccworkshops53468.2022.9882164
• 发表时间: 2022
• 期刊: 2022 IEEE International Conference on Communications Workshops (ICC Workshops
• 作者: Thompson, Robert;Lyons, Eric;Dasgupta, Ishita;Mastorakis, Spyridon;Zink, Michael;Shannigrahi, Susmit
• 通讯作者: Shannigrahi, Susmit

An Optimized IoT-Enabled Big Data Analytics Architecture for Edge-Cloud Computing

• DOI: 10.1109/jiot.2022.3157552
• 发表时间: 2023-03-01
• 期刊: IEEE INTERNET OF THINGS JOURNAL
• 影响因子: 10.6
• 作者: Babar, Muhammad;Jan, Mian Ahmad;Alturki, Ryan
• 通讯作者: Alturki, Ryan

Harpocrates: Anonymous Data Publication in Named Data Networking

• DOI: 10.1145/3532105.3535025
• 发表时间: 2022-01
• 期刊: Proceedings of the 27th ACM on Symposium on Access Control Models and Technologies
• 作者: Md Washik Al Azad;R. Tourani;Abderrahmen Mtibaa;Spyridon Mastorakis