HyperDrive: Scheduling Serverless Functions in the Edge-Cloud-Space 3D Continuum

The number of Low Earth Orbit (LEO) satellites has grown enormously in the past years. Their abundance and low orbits allow for low latency communication with a satellite almost anywhere on Earth, and high-speed inter-satellite laser links (ISLs) enable a quick exchange of large amounts of data among satellites. As the computational capabilities of LEO satellites grow, they are becoming eligible as general-purpose compute nodes. In the 3D continuum, which combines Cloud and Edge nodes on Earth and satellites in space into a seamless computing fabric, workloads can be executed on any of the aforementioned compute nodes, depending on where it is most beneficial. However, scheduling on LEO satellites moving at approx. 27,000 km/h requires picking the satellite with the lowest latency to all data sources (ground and, possibly, earth observation satellites). Dissipating heat from onboard hardware is challenging when facing the sun and workloads must not drain the satellite's batteries. These factors make meeting SLOs more challenging than in the Edge-Cloud continuum, i.e., on Earth alone. We present HyperDrive, an SLOaware scheduler for serverless functions specifically designed for the 3D continuum. It places functions on Cloud, Edge, or Space compute nodes, based on their availability and ability to meet the SLO requirements of the workflow. We evaluate HyperDrive using a wildfire disaster response use case with high Earth Observation data processing requirements and stringent SLOs, showing that it enables the design and execution of such next-generation 3D scenarios with 71% lower network latency than the best baseline scheduler.

Authors

Institutions

Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1109/sec62691.2024.00028
Citations
6
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
2.09

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

HyperDrive: Scheduling Serverless Functions in the Edge-Cloud-Space 3D Continuum

Thomas Pusztai, Cynthia Marcelino, Stefan Nastić
6 citations
Distributed and Parallel Computing Systems
2.09
article

HyperDrive: Scheduling Serverless Functions in the Edge-Cloud-Space 3D Continuum

Thomas Pusztai, Cynthia Marcelino, Stefan Nastić
article en
6 citations

Abstract

The number of Low Earth Orbit (LEO) satellites has grown enormously in the past years. Their abundance and low orbits allow for low latency communication with a satellite almost anywhere on Earth, and high-speed inter-satellite laser links (ISLs) enable a quick exchange of large amounts of data among satellites. As the computational capabilities of LEO satellites grow, they are becoming eligible as general-purpose compute nodes. In the 3D continuum, which combines Cloud and Edge nodes on Earth and satellites in space into a seamless computing fabric, workloads can be executed on any of the aforementioned compute nodes, depending on where it is most beneficial. However, scheduling on LEO satellites moving at approx. 27,000 km/h requires picking the satellite with the lowest latency to all data sources (ground and, possibly, earth observation satellites). Dissipating heat from onboard hardware is challenging when facing the sun and workloads must not drain the satellite's batteries. These factors make meeting SLOs more challenging than in the Edge-Cloud continuum, i.e., on Earth alone. We present HyperDrive, an SLOaware scheduler for serverless functions specifically designed for the 3D continuum. It places functions on Cloud, Edge, or Space compute nodes, based on their availability and ability to meet the SLO requirements of the workflow. We evaluate HyperDrive using a wildfire disaster response use case with high Earth Observation data processing requirements and stringent SLOs, showing that it enables the design and execution of such next-generation 3D scenarios with 71% lower network latency than the best baseline scheduler.

TU Wien (AT)
HORIZON EUROPE Reforming and enhancing the European Research and Innovation system
Openalex Percentile: Top 11%
Distributed and Parallel Computing Systems
2.09
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

HyperDrive: Scheduling Serverless Functions in the Edge-Cloud-Space 3D Continuum — Thomas Pusztai, Cynthia Marcelino, et al. · (2024) | TGRS Research Map | TGRS