Placement of microservices-based IoT applications in fog computing: A taxonomy and future directions

S Pallewatta, V Kostakos, R Buyya - ACM Computing Surveys, 2023 - dl.acm.org
The Fog computing paradigm utilises distributed, heterogeneous and resource-constrained
devices at the edge of the network for efficient deployment of latency-critical and bandwidth …

Characterizing microservice dependency and performance: Alibaba trace analysis

S Luo, H Xu, C Lu, K Ye, G Xu, L Zhang… - Proceedings of the …, 2021 - dl.acm.org
Loosely-coupled and light-weight microservices running in containers are replacing
monolithic applications gradually. Understanding the characteristics of microservices is …

Autopilot: workload autoscaling at google

K Rzadca, P Findeisen, J Swiderski, P Zych… - Proceedings of the …, 2020 - dl.acm.org
In many public and private Cloud systems, users need to specify a limit for the amount of
resources (CPU cores and RAM) to provision for their workloads. A job that exceeds its limits …

Carbon-aware computing for datacenters

A Radovanović, R Koningstein… - … on Power Systems, 2022 - ieeexplore.ieee.org
The amount of CO emitted per kilowatt-hour on an electricity grid varies by time of day and
substantially varies by location due to the types of generation. Networked collections of …

{AIFM}:{High-Performance},{Application-Integrated} far memory

Z Ruan, M Schwarzkopf, MK Aguilera… - 14th USENIX Symposium …, 2020 - usenix.org
Memory is the most contended and least elastic resource in datacenter servers today.
Applications can use only local memory—which may be scarce—even though memory …

Protean:{VM} allocation service at scale

O Hadary, L Marshall, I Menache, A Pan… - … USENIX Symposium on …, 2020 - usenix.org
We describe the design and implementation of Protean--the Microsoft Azure service
responsible for allocating Virtual Machines (VMs) to millions of servers around the globe. A …

Carbon explorer: A holistic framework for designing carbon aware datacenters

B Acun, B Lee, F Kazhamiaka, K Maeng… - Proceedings of the 28th …, 2023 - dl.acm.org
Technology companies reduce their datacenters' carbon footprint by investing in renewable
energy generation and receiving credits from power purchase agreements. Annually …

Characterization and prediction of deep learning workloads in large-scale gpu datacenters

Q Hu, P Sun, S Yan, Y Wen, T Zhang - Proceedings of the International …, 2021 - dl.acm.org
Modern GPU datacenters are critical for delivering Deep Learning (DL) models and services
in both the research community and industry. When operating a datacenter, optimization of …

Rethinking software runtimes for disaggregated memory

I Calciu, MT Imran, I Puddu, S Kashyap… - Proceedings of the 26th …, 2021 - dl.acm.org
Disaggregated memory can address resource provisioning inefficiencies in current
datacenters. Multiple software runtimes for disaggregated memory have been proposed in …

From cloud to edge: a first look at public edge platforms

M Xu, Z Fu, X Ma, L Zhang, Y Li, F Qian… - Proceedings of the 21st …, 2021 - dl.acm.org
Public edge platforms have drawn increasing attention from both academia and industry. In
this study, we perform a first-of-its-kind measurement study on a leading public edge …