Exploring efficient ml-based scheduler for microservices in heterogenous clusters

R Mahapatra, BH Ahn, ST Wang, H Xu… - Machine Learning for …, 2022 - openreview.net
In the recent years, cloud computing is going though a major transformation throughout its
system stack, from its application to hardware. Its services are increasingly shifting from …

DRS: A deep reinforcement learning enhanced Kubernetes scheduler for microservice‐based system

Z Jian, X Xie, Y Fang, Y Jiang, Y Lu… - Software: Practice …, 2024 - Wiley Online Library
Recently, Kubernetes is widely used to manage and schedule the resources of
microservices in cloud‐native distributed applications, as the most famous container …

Topology-aware scheduling framework for microservice applications in cloud

X Li, J Zhou, X Wei, D Li, Z Qian, J Wu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Loosely coupled and highly cohesived microservices running in containers are becoming
the new paradigm for application development. Compared with monolithic applications …

Deep learning research and development platform: Characterizing and scheduling with qos guarantees on gpu clusters

Z Chen, W Quan, M Wen, J Fang, J Yu… - … on Parallel and …, 2019 - ieeexplore.ieee.org
Deep learning (DL) has been widely adopted in various domains of artificial intelligence (AI),
achieving dramatic developments in industry and academia. Besides giant AI companies …

Energy-efficient VM scheduling based on deep reinforcement learning

B Wang, F Liu, W Lin - Future Generation Computer Systems, 2021 - Elsevier
Achieving data center resource optimization and QoS guarantee driven by high energy
efficiency has become a research hotspot. However, QoS information directly sampled from …

Qos-aware scheduling of heterogeneous servers for inference in deep neural networks

Z Fang, T Yu, OJ Mengshoel, RK Gupta - Proceedings of the 2017 ACM …, 2017 - dl.acm.org
Deep neural networks (DNNs) are popular in diverse fields such as computer vision and
natural language processing. DNN inference tasks are emerging as a service provided by …

Epsilon: A microservices based distributed scheduler for kubernetes cluster

ANJ Hui, BS Lee - 2021 18th International Joint Conference on …, 2021 - ieeexplore.ieee.org
Kubernetes is a popular container orchestration platform designed to simplify the
deployment of containers in a compute cluster. Kubernetes provides a monolithic cluster …

Efficient microservice deployment in kubernetes multi-clusters through reinforcement learning

J Santos, M Zaccarini, F Poltronieri… - NOMS 2024-2024 …, 2024 - ieeexplore.ieee.org
Microservices have revolutionized application deployment in popular cloud platforms,
offering flexible scheduling of loosely-coupled containers and improving operational …

[HTML][HTML] Evolving High-Performance Computing Data Centers with Kubernetes, Performance Analysis, and Dynamic Workload Placement Based on Machine Learning …

V Dakić, M Kovač, J Slovinac - Electronics, 2024 - mdpi.com
In the past twenty years, the IT industry has moved away from using physical servers for
workload management to workloads consolidated via virtualization and, in the next iteration …

Characterizing bottlenecks in scheduling microservices on serverless platforms

JR Gunasekaran, P Thinakaran… - 2020 IEEE 40th …, 2020 - ieeexplore.ieee.org
Datacenters are witnessing an increasing trend in adopting microservice-based architecture
for application design, which consists of a combination of different microservices. Typically …