18 citations · 22 across the 5 of their papers we have counts for
5 papers
DMSConfig: Automated Configuration Tuning for Distributed IoT Message Systems Using Deep Reinforcement Learning
Zhuangwei Kang, Yogesh D. Barve, Shunxing Bao +2
The Distributed Messaging Systems (DMSs) used in IoT systems require timely and reliable data dissemination, which can be achieved through configurable parameters. However, the hig…
Risk-Aware Scene Sampling for Dynamic Assurance of Autonomous Systems
Shreyas Ramakrishna, Baiting Luo, Yogesh Barve +2
Autonomous Cyber-Physical Systems must often operate under uncertainties like sensor degradation and shifts in the operating conditions, which increases its operational risk. Dynam…
FECBench: A Holistic Interference-aware Approach for Application Performance Modeling
Yogesh D. Barve, Shashank Shekhar, Ajay Dev Chhokra +5
Services hosted in multi-tenant cloud platforms often encounter performance interference due to contention for non-partitionable resources, which in turn causes unpredictable behav…
CloudCAMP: Automating Cloud Services Deployment and Management
Anirban Bhattacharjee, Yogesh Barve, Aniruddha Gokhale +1
Users of cloud platforms often must expend significant manual efforts in the deployment and orchestration of their services on cloud platforms due primarily to having to deal with…
Stratum: A Serverless Framework for Lifecycle Management of Machine Learning based Data Analytics Tasks
Anirban Bhattacharjee, Yogesh Barve, Shweta Khare +3
With the proliferation of machine learning (ML) libraries and frameworks, and the programming languages that they use, along with operations of data loading, transformation, prepar…