Delay Minimization of Task Offloading in O-RAN Architecture

In this paper, we propose a heuristic algorithm for minimizing the delay of task offloading within the open radio access network (O-RAN) architecture. We model the O-RAN architecture using a directed graph connecting its various components. Assuming that frequency-division multiplexing (FDM) is used between all users sharing the same communication link, and applying the M/M/1 queueing model at the O-RAN central units (O-CUs), we update the graph weights and design a heuristic algorithm to provide delay-efficient routing for all users. Numerical results demonstrate the performance of the algorithm and provide insights into the O-RAN architecture.

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Published
2024-10-15
DOI
https://doi.org/10.1109/fnwf63303.2024.11028799
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Delay Minimization of Task Offloading in O-RAN Architecture

Nikos A. Mitsiou, Panagiotis Sarigiannidis, George K. Karagiannidis, Θωμάς Λάγκας et al.
IoT and Edge/Fog Computing
article

Delay Minimization of Task Offloading in O-RAN Architecture

Nikos A. Mitsiou, Panagiotis Sarigiannidis, George K. Karagiannidis, Θωμάς Λάγκας, Sotiris A. Tegos
article en

Abstract

In this paper, we propose a heuristic algorithm for minimizing the delay of task offloading within the open radio access network (O-RAN) architecture. We model the O-RAN architecture using a directed graph connecting its various components. Assuming that frequency-division multiplexing (FDM) is used between all users sharing the same communication link, and applying the M/M/1 queueing model at the O-RAN central units (O-CUs), we update the graph weights and design a heuristic algorithm to provide delay-efficient routing for all users. Numerical results demonstrate the performance of the algorithm and provide insights into the O-RAN architecture.

Democritus University of Thrace (GR), Aristotle University of Thessaloniki (GR), University of Western Macedonia (GR)
HORIZON EUROPE Framework Programme
Openalex Percentile: Top 64%
IoT and Edge/Fog Computing
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