Project/Grant Period: 06/15/2020 - 05/31/2024

The goals of this project are to:

1. define a new abstraction and architecture for storage caches whereby storage stacks can easily embed lightweight CaaS clients within a distributed compute infrastructure.
2. formulate and theoretically analyze distributed caching algorithms that operate within the CaaS service such that individual CaaS server nodes cooperate towards achieving globally optimal caching decisions,
3. co-design client and server end-points to achieve strict durability and fault-tolerance in their implementations, and
4. drive all CaaS advancements using insights generated from a detailed whole-system simulator that models the diverse cache devices, network configurations, and application demand.

• Raju Rangaswami, Principal Investigator, FIU
• Ming Zhao, Principal Investigator, ASU
• Jason X Liu, Co-Principal Investigator
• Giri Narasimhan, Co-Principal Investigator

• Dr. Liana Valdes (PhD graduate)
• Alexis Gonzales (PhD student)
• Pratik Poudel (PhD student)
• Qirui Yang (PhD student)
• Kritshekhar Jha (PhD student)
• Daniel Nunez Dominguez (Undergraduate student)
• Fernando Cabanes (Undergraduate student)
• Lester Fernandez (Undergraduate student)
• Lillian Seebold (Undergraduate student)

• Unordered List Item

This work has been supported by the National Science Foundation award CNS-1956229.