Improving Resource and Energy Efficiency for Cloud 3D through Excessive Rendering Reduction

Mon, 01 Jan 2024 00:00:00 +0000

Performance Testing for Cloud and Serverless Computing

Sun, 01 Jan 2023 00:00:00 +0000

Overview

Cloud computing introduces fundamental challenges for performance testing due to resource contention, hidden scheduling policies, and passive auto-scaling. These challenges are amplified in serverless computing environments where the resource abstraction level is higher and auto-scaling behaviors are not well-characterized.

Research Thrusts

Serverless Auto-Scaling Characterization: We define and characterize auto-scaling stages for serverless platforms, decomposing performance uncertainty into resource contention during execution and cold start-up latencies during environment initiation.

Monte Carlo Simulation-Based Testing: We develop simulation-based methodologies that can predict performance distributions of serverless applications, accounting for the stochastic nature of cloud performance fluctuations.

AI-Based Cloud Emulation: Building systems that emulate cloud environments on local machines to help users obtain accurate performance results at reduced testing costs, particularly when multiple applications need to be evaluated.

Performance Assurance in DevOps: Using development and operational data to detect performance regressions early in the software delivery cycle, with attention to end-user impact.

A Cloud 3D Dataset and Application-Specific Learned Image Compression in Cloud 3D

Sat, 01 Jan 2022 00:00:00 +0000

Performance Testing for Cloud Computing with Dependent Data Bootstrapping

Fri, 01 Jan 2021 00:00:00 +0000

A benchmarking framework for interactive 3D applications in the cloud

Wed, 01 Jan 2020 00:00:00 +0000