A Cloud-Native Approach for Orchestrating 6G-Enabled Services at the Computing Continuum

The cloudification of 6G services and the rise of edge and cloud computing have significantly increased the complexity of service lifecycle management, resulting in intricate networks deployed across interconnected infrastructures. The transition from traditional monitoring to modern cloud-native and network observability tools is crucial for providing a fine-grained view of application, infrastructure, and network performance. This paper proposes a novel orchestration methodology that enhances monitoring insights and effectively manages computing and network resources from the extreme edge to the cloud. Our approach encompasses synergetic orchestration mechanisms leveraging multi-agent systems, data fusion from various observability signals, and machine learning techniques wherever possible. Beyond conceptualizing and designing this methodology, we detail a tangible closed-loop architecture capable of supporting and realizing the proposed mechanisms. Finally, we validate a prototype implementation and evaluate its performance through a proof of concept involving realistic experimental trials, demonstrating our solution's effectiveness in orchestrating a 6G- enabled application with stringent latency requirements.

Authors

Institutions

Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/camad62243.2024.10942907
Citations
2
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.70
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Cloud-Native Approach for Orchestrating 6G-Enabled Services at the Computing Continuum

Symeon Papavassiliou, Ioannis Tzanettis, Grigorios Kakkavas, Anastasios Zafeiropoulos et al.
2 citations
IoT and Edge/Fog Computing
0.70
article

A Cloud-Native Approach for Orchestrating 6G-Enabled Services at the Computing Continuum

Symeon Papavassiliou, Ioannis Tzanettis, Grigorios Kakkavas, Anastasios Zafeiropoulos, Alexandros Stylos
article en
2 citations

Abstract

The cloudification of 6G services and the rise of edge and cloud computing have significantly increased the complexity of service lifecycle management, resulting in intricate networks deployed across interconnected infrastructures. The transition from traditional monitoring to modern cloud-native and network observability tools is crucial for providing a fine-grained view of application, infrastructure, and network performance. This paper proposes a novel orchestration methodology that enhances monitoring insights and effectively manages computing and network resources from the extreme edge to the cloud. Our approach encompasses synergetic orchestration mechanisms leveraging multi-agent systems, data fusion from various observability signals, and machine learning techniques wherever possible. Beyond conceptualizing and designing this methodology, we detail a tangible closed-loop architecture capable of supporting and realizing the proposed mechanisms. Finally, we validate a prototype implementation and evaluate its performance through a proof of concept involving realistic experimental trials, demonstrating our solution's effectiveness in orchestrating a 6G- enabled application with stringent latency requirements.

Institute of Communication and Computer Systems (GR)
Openalex Percentile: Top 25%
IoT and Edge/Fog Computing
0.70
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.

A Cloud-Native Approach for Orchestrating 6G-Enabled Services at the Computing Continuum — Symeon Papavassiliou, Ioannis Tzanettis, et al. · (2024) | TGRS Research Map | TGRS