@inproceedings{ac13ae8c327c4b2e996f9ff748948838,
title = "Graph attention networks and deep Q-learning for service mesh optimization: a digital twinning approach",
abstract = "In the realm of cloud native environments, Ku-bernetes has emerged as the de facto orchestration system for containers, and the service mesh architecture, with its interconnected microservices, has become increasingly prominent. Efficient scheduling and resource allocation for these microservices play a pivotal role in achieving high performance and maintaining system reliability. In this paper, we introduce a novel approach for container scheduling within Kubernetes clusters, leveraging Graph Attention Networks (GATs) for representation learning. Our proposed method captures the intricate dependencies among containers and services by constructing a representation graph. The deep Q-learning algorithm is then employed to optimize scheduling decisions, focusing on container-to-node placements, CPU request-response allocation, and adherence to node affinity and anti-affinity rules. Our experiments demonstrate that our GATs-based method outperforms traditional scheduling strategies, leading to enhanced resource utilization, reduced service latency, and improved overall system throughput. The insights gleaned from this study pave the way for a new frontier in cloud native performance optimization and offer tangible benefits to industries adopting microservice-based architectures.",
keywords = "component, formatting, insert, style, styling",
author = "Khan, {Michel Gokan} and Javid Taheri and Andreas Kassler and Asl, {Arsineh Boodaghian}",
year = "2024",
month = aug,
day = "20",
doi = "10.1109/ICC51166.2024.10622616",
language = "English",
isbn = "9781728190556",
series = "IEEE International Conference on Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2913--2918",
editor = "Matthew Valenti and David Reed and Melissa Torres",
booktitle = "ICC 2024 - IEEE International Conference on Communications: Proceedings",
address = "United States",
note = "59th Annual IEEE International Conference on Communications, ICC 2024 ; Conference date: 09-06-2024 Through 13-06-2024",
}