2 citations · 2 across the 7 of their papers we have counts for
7 papers
Carbon-aware Resource Management for Latency-Sensitive Cloud Computing Environments: A Taxonomy and Future Directions
Tharindu B. Hewage, Shashikant Ilager, Maria Rodriguez Read +1
The proliferation of cloud-based latency-sensitive workloads, such as autonomous driving, real-time healthcare services, industrial automation, immersive interactive services, and…
ADASCALE: An Adaptive Scaling and Placement Framework for Microservices Under Dynamics
Ming Chen, Muhammed Tawfiqul Islam, Maria Rodriguez Read +1
Microservice applications are increasingly deployed across cloud--edge environments, where heterogeneous nodes and time-varying inter-node delays amplify the impact of placement de…
Adaptive Management of Microservices in Dynamic Computing Environments: A Taxonomy and Future Directions
Ming Chen, Muhammed Tawfiqul Islam, Maria Rodriguez Read +1
Microservice-based cloud applications face changing workloads, evolving request paths, variable network conditions, interference, and failures. These dynamics couple autoscaling, p…
iDynamics: A Configurable Emulation Framework for Evaluating Microservice Scheduling Policies under Controllable Cloud-Edge Dynamics
Ming Chen, Muhammed Tawfiqul Islam, Maria Rodriguez Read +1
This paper presents iDynamics, a configurable emulation framework that exposes these dynamics as controllable experimental factors while running real microservice code on a Kuberne…
Aging-aware CPU Core Management for Embodied Carbon Amortization in Cloud LLM Inference
Tharindu B. Hewage, Shashikant Ilager, Maria Rodriguez Read +1
Broad adoption of Large Language Models (LLM) demands rapid expansions of cloud LLM inference clusters, leading to accumulation of embodied carbonthe emissions from manufacturin…
TraDE: Network and Traffic-aware Adaptive Scheduling for Microservices Under Dynamics
Ming Chen, Muhammed Tawfiqul Islam, Maria Rodriguez Read +1
The transition from monolithic architecture to microservices has enhanced flexibility in application design and its scalable execution. This approach typically uses a computing clu…
Deep Reinforcement Learning (DRL)-based Methods for Serverless Stream Processing Engines: A Vision, Architectural Elements, and Future Directions
Maria R. Read, Chinmaya Dehury, Satish Narayana Srirama +1
Streaming applications are becoming widespread across an extensive range of business domains as an increasing number of sources continuously produce data that need to be processed…