TY - CHAP
T1 - O-RAN and MEC Integration and Orchestration
T2 - 25th IEEE Wireless Communications and Networking Conference, WCNC 2024
AU - Amiri, Esmaeil
AU - Mahmoodi, Toktam
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024/4
Y1 - 2024/4
N2 - Multi-Access Edge Computing (MEC) and Open Radio Access Network (O-RAN) have emerged as promising paradigms to address diverse applications and service require-ments. MEC brings computational power to the network edge, enabling efficient offloading of compute-intensive tasks, while O-RAN facilitates network disaggregation for centralized deployment. The inherent conflict between MEC's user-centric proximity and O-RAN's disaggregation goals poses challenges in their integration. In this paper, we introduce a comprehensive analytical framework to optimize the integration of RAN dis-aggregation and MEC services. This framework models RAN functions and considers both full and partial task offloading strategies. This collaborative approach aims to minimize costs related to bandwidth usage and computing resource utilization. The simulation results indicate that the integration of MEC can significantly increase network costs. However, this impact can be mitigated by enhancing the centralization of computing resources. Additionally, doubling the weight of the link cost leads to a significant increase in the number of full compared to partial offloading, highlighting the tradeoff between these two strategies regarding computing resources and bandwidth utilization.
AB - Multi-Access Edge Computing (MEC) and Open Radio Access Network (O-RAN) have emerged as promising paradigms to address diverse applications and service require-ments. MEC brings computational power to the network edge, enabling efficient offloading of compute-intensive tasks, while O-RAN facilitates network disaggregation for centralized deployment. The inherent conflict between MEC's user-centric proximity and O-RAN's disaggregation goals poses challenges in their integration. In this paper, we introduce a comprehensive analytical framework to optimize the integration of RAN dis-aggregation and MEC services. This framework models RAN functions and considers both full and partial task offloading strategies. This collaborative approach aims to minimize costs related to bandwidth usage and computing resource utilization. The simulation results indicate that the integration of MEC can significantly increase network costs. However, this impact can be mitigated by enhancing the centralization of computing resources. Additionally, doubling the weight of the link cost leads to a significant increase in the number of full compared to partial offloading, highlighting the tradeoff between these two strategies regarding computing resources and bandwidth utilization.
KW - Multi-Access Edge Computing (MEC)
KW - Open Radio Access Network (O-RAN)
KW - Task Offloading
UR - http://www.scopus.com/inward/record.url?scp=85198846808&partnerID=8YFLogxK
U2 - 10.1109/WCNC57260.2024.10571112
DO - 10.1109/WCNC57260.2024.10571112
M3 - Conference paper
AN - SCOPUS:85198846808
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2024 IEEE Wireless Communications and Networking Conference, WCNC 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 21 April 2024 through 24 April 2024
ER -