The cloud's flexibility and promise of seamless auto-scaling notwithstanding, its ability to meet service level objectives (SLOs) typically calls for some form of control in resource usage. This seemingly traditional problem gives rise to new challenges in a cloud setting, and in particular a subtle yet significant trade-off involving load-distribution decisions (the distribution of workload across available cloud resources to optimize performance), and rate limiting (the capping of individual workloads to prevent global over-commitment). This paper investigates that trade-off through the design and implementation of a real-time messaging system motivated by Internet-of-Things (IoT) applications, and demonstrates a solution capable of realizing an effective compromise. The paper's contributions are in both explicating the source of this trade-off, and in demonstrating a possible solution.
@article{arxiv.2101.05865,
title = {Impact of Distributed Rate Limiting on Load Distribution in a Latency-sensitive Messaging Service},
author = {Chong Li and Jiangnan Liu and Chenyang Lu and Roch Guerin and Christopher D. Gill},
journal= {arXiv preprint arXiv:2101.05865},
year = {2021}
}