Work

Framework for Task Offloading in O‐RAN Architecture for Heterogeneous Computing Applications

Year: 2026

Type: article

Abstract: ABSTRACT Computational offloading transfers tasks from resource‐constrained devices to more capable servers or cloud platforms, improving processing speed and user experience. Open radio access networks (O‐RAN's) disaggregated architecture and open interfaces make it suitable for offloading delay‐sensitive tasks, enhancing real‐time application performance. This study focuses on task offloading in O‐RAN, a reference network architecture. Although research on O‐RAN is limited, existing work lacks a comprehensive approach to offloading, including offloading layer determination, node selection, and resource allocation based on task types and their latency needs. We propose a delay‐aware task offloading framework within O‐RAN to support diverse delay requirements, improving offloading efficiency. To address this, we introduce COOR (Computation Offloading for O‐RAN), a centralized approach that leverages network‐wide data. Using Genetic Algorithms (GA), we manage computational complexity effectively. Simulation results show COOR's superior performance in reducing latency.

Source: Transactions on Emerging Telecommunications Technologies

DOI: 10.1002/ett.70354

Authors: Samira Taheri, Neda Moghim, Naser Movahhedinia, Sachin Shetty

Institutions: University of Isfahan, Old Dominion University

Language: English

Topic: IoT and Edge/Fog Computing

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $2,850