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Award Abstract # 2213387
Collaborative Research: CNS Core: Large: Runtime Programmable Networks

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: UNIVERSITY OF WASHINGTON
Initial Amendment Date: July 14, 2022
Latest Amendment Date: August 21, 2024
Award Number: 2213387
Award Instrument: Continuing Grant
Program Manager: Ann Von Lehmen
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: July 15, 2022
End Date: June 30, 2026 (Estimated)
Total Intended Award Amount: $1,199,998.00
Total Awarded Amount to Date: $1,199,998.00
Funds Obligated to Date: FY 2022 = $282,818.00
FY 2023 = $599,526.00

FY 2024 = $317,654.00
History of Investigator:
  • Arvind Krishnamurthy (Principal Investigator)
    arvind@cs.washington.edu
  • Thomas Anderson (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Washington
4333 BROOKLYN AVE NE
SEATTLE
WA  US  98195-1016
(206)543-4043
Sponsor Congressional District: 07
Primary Place of Performance: University of Washington
185 Stevens Way CSE 101
Seattle
WA  US  98195-2350
Primary Place of Performance
Congressional District:
07
Unique Entity Identifier (UEI): HD1WMN6945W6
Parent UEI:
NSF Program(s): Networking Technology and Syst
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01002324DB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT

01002526DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7925
Program Element Code(s): 736300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Programmability is fuel for network innovation. In today?s programmable networks, new features can be easily developed without having to rely on vendor support. However, deploying new features still requires fleet-wide maintenance to avoid disruption because device reprogramming incurs downtime. This severely constrains the speed of change, as maintenance operations require meticulous planning well ahead of time. This project proposes runtime programmable networks, where the end-to-end network infrastructure, vertically from the host kernels down to the network interface cards, and horizontally extending across switches to the other end of the network, can be reprogrammed on-the-fly without packet drops and with strong consistency guarantees. This represents a major leap from today?s programmable networks, which are reconfigurable at compile time but become fixed functions at runtime after deployment.

According to this project's vision, FlexNet, the network infrastructure provides a collection of basic utilities and, on demand, extensions are partially reconfigured into the infrastructure by injecting, removing, or overriding specific functions. This accelerates the speed of delivering new features to end users, increases the manageability of large networks by lowering the barrier for change, and creates new possibilities unavailable in today?s programmable networks, such as powerful, dynamic security defenses. With FlexNet, this project can summon security defenses into the network precisely when needed. Defenses can migrate to the attack location or replicate across the network to maximize their effectiveness. They can even shapeshift in real time to mitigate changing attacks. When attacks subside, these defenses can be soon removed from the network to reduce overhead. This project aims to elevate network programming from a ?one-shot? endeavor at compile time to ?continuous? activities throughout the lifecycle of the network.

In order to realize our vision, this project needs to innovate across the stack. Concretely, this project proposes a four-pronged approach to programing, compiling, verifying, and managing runtime programmable networks end-to-end. First, runtime network programming requires controlling disparate datapaths and their real-time changes as a whole, while ensuring runtime portability across devices; thus, this project will develop a new programming system. Compiling a whole-network program to a heterogeneous substrate, while continuously reoptimizing for runtime changes, requires a new compiler design. To ensure the safety of network changes, this project must simultaneously innovate on runtime verification and validation. Finally, FlexNet programs have dynamic footprints in the network?migrating, expanding, and shrinking across devices?so this project needs a new management system to control such unprecedented dynamics. This project will produce an integrated platform upon which the FlexNet techniques will be evaluated comprehensively at various scales and with diverse workloads. To achieve a wider community engagement, this project will release software and hardware prototypes and educational materials in open source, and by collaborating with industry partners, this project will transition the FlexNet technologies into practice.

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Jingrong Chen, Yongji Wu "Remote Procedure Call as a Managed System Service" Networked Systems Design and Implementation , 2023 Citation Details
Lin, Will and Shan, Yizhou and Kosta, Ryan and Krishnamurthy, Arvind and Zhang, Yiying "SuperNIC: An FPGA-Based, Cloud-Oriented SmartNIC" , 2024 https://doi.org/10.1145/3626202.3637564 Citation Details
Xing, Jiarong and Qiu, Yiming and Hsu, Kuo-Feng and Sui, Songyuan and Manaa, Khalid and Shabtai, Omer and Piasetzky, Yonatan and Kadosh, Matty and Krishnamurthy, Arvind and Ng, T_S Eugene and Chen, Ang "Unleashing SmartNIC Packet Processing Performance in P4" , 2023 https://doi.org/10.1145/3603269.3604882 Citation Details
Zhu, Xiangfeng and Deng, Weixin and Liu, Banruo and Chen, Jingrong and Wu, Yongji and Anderson, Thomas and Krishnamurthy, Arvind and Mahajan, Ratul and Zhuo, Danyang "Application Defined Networks" , 2023 https://doi.org/10.1145/3626111.3628178 Citation Details

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