CSR: Small: RUI: Octopus OS: A High-Performance Cloud OS with Accurate Resource Abstraction.

This project aims to develop a high-performance cloud operating system (OS), called Octopus OS, that can adapt to the dynamic cloud environment. Instead of running on a physical machine, the OS now is often running in a virtual machine (VM) in the modern cloud where the resources are highly dynamic due to resource sharing and VM migration. However, the traditional OS

cannot manage the virtualized resources efficiently due to being unaware of the resource dynamics, leading to low resource utilization and poor application performance in the cloud. Therefore, the proposed Octopus OS would create and manage the accurate abstractions of the dynamic resources, and develop new algorithms to fully leverage the unique characteristics of the virtualized

resource, which would greatly improve application performance and resource utilization in the dynamic cloud. This work can advance the cloud OS by serving as a framework for optimizing the utilization of various virtualized resources. The outcomes will be released for public use. Hands on projects will be created during the project development to enrich existing courses related to

OS and cloud computing. This project will involve students from underrepresented groups and promote research in computer systems for all undergraduates. Four steps will be taken to achieve the project goal. First, the mismatches in major virtualized resource abstractions (i.e., CPU, memory, and cache) will be analyzed in a controlled environment

to understand their impacts, including resultant system abnormal behavior and application performance degradation. Second, accurate resource abstractions will be created to fix the identified mismatches using probing techniques. Specifically, a set of micro-benchmarks, called vProbers, will be developed to profile the dynamic nature of the virtualized resources without relying

on the hypervisor support or application porting, making this solution practical in the emerging multi-cloud environment. The accurate resource abstractions probed within Octopus OS can also be leveraged by cloud application and language runtime, and are critical to provide resource visibility for cross-cloud optimizations. Third, the new abstractions will be exposed to Octopus OS to

make it virtualization-aware. New algorithms will be developed to fix existing system abnormal behavior and unlock the potential performance benefits of the dynamic resources. Fourth, experiments with resource-demanding benchmarks in various public clouds will be conducted to evaluate the ability of

the proposed Octopus OS to adapt to the dynamic resources in the multi-cloud environment.

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.