Flocky: Decentralized Intent-Based Edge Orchestration Using Open Application Model

Continuum computing has emerged as a paradigm to improve various aspects of service orchestration by offloading computation from the cloud to the network edge. However, edge orchestration poses two significant challenges compared to cloud computing. On one hand, cloud software scheduling algorithms make suboptimal decisions when applied to the network edge, as edge devices and networks are more hetereogeneous than cloud data centers, and orchestration requires different parameters. On the other hand, most orchestration platforms assume highly centralized cloud data centers, with each server running many easily migrated software instances, whereas edge devices have limited hardware capabilities and migration of tasks between devices is significantly slower than in the cloud. As a result, there is a need for a decentralized orchestration platform that allows scheduling algorithms to take into account a wide variety of device properties and deployment requirements in placement decisions. This article presents Flocky, a decentralized device discovery and service orchestration framework based on Open Application Model (OAM), to address this gap. The architecture of Flocky is elaborated, showing how OAM enables flexible intent modeling in the edge, and combined with a Gossip-like algorithm allows individual edge devices to discover devices in their neighborhoods, map their capabilities, and optimally deploy parts of applications to individual nodes. Evaluation shows Flocky to be highly scalable and mainly dependent on local node density, with nodes discovering over 97% of their viable neighbours on average within two discovery rounds, while using 84% less memory than a centralized orchestrator such as Kubernetes.

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Publication Details

Journal
IEEE Transactions on Services Computing
Published
2025-11-10
DOI
https://doi.org/10.1109/tsc.2025.3631387
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
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article

Flocky: Decentralized Intent-Based Edge Orchestration Using Open Application Model

Tom Goethals, Merlijn Sebrechts, Mays Al-Naday, Filip De Turck et al.
IEEE Transactions on Services Computing
IoT and Edge/Fog Computing
article

Flocky: Decentralized Intent-Based Edge Orchestration Using Open Application Model

Tom Goethals, Merlijn Sebrechts, Mays Al-Naday, Filip De Turck, Bruno Volckaert
article en

Abstract

Continuum computing has emerged as a paradigm to improve various aspects of service orchestration by offloading computation from the cloud to the network edge. However, edge orchestration poses two significant challenges compared to cloud computing. On one hand, cloud software scheduling algorithms make suboptimal decisions when applied to the network edge, as edge devices and networks are more hetereogeneous than cloud data centers, and orchestration requires different parameters. On the other hand, most orchestration platforms assume highly centralized cloud data centers, with each server running many easily migrated software instances, whereas edge devices have limited hardware capabilities and migration of tasks between devices is significantly slower than in the cloud. As a result, there is a need for a decentralized orchestration platform that allows scheduling algorithms to take into account a wide variety of device properties and deployment requirements in placement decisions. This article presents Flocky, a decentralized device discovery and service orchestration framework based on Open Application Model (OAM), to address this gap. The architecture of Flocky is elaborated, showing how OAM enables flexible intent modeling in the edge, and combined with a Gossip-like algorithm allows individual edge devices to discover devices in their neighborhoods, map their capabilities, and optimally deploy parts of applications to individual nodes. Evaluation shows Flocky to be highly scalable and mainly dependent on local node density, with nodes discovering over 97% of their viable neighbours on average within two discovery rounds, while using 84% less memory than a centralized orchestrator such as Kubernetes.

IEEE Transactions on Services ComputingVol. 19(1)
University of Essex (GB), Ghent University (BE)
Openalex Percentile: Top 61%
IoT and Edge/Fog Computing
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