TY - GEN
T1 - Joint UPF and Edge Applications Placement and Routing in 5G & Beyond
AU - Goshi, Endri
AU - Harkous, Hasanin
AU - Ahvar, Shohreh
AU - Pries, Rastin
AU - Mehmeti, Fidan
AU - Kellerer, Wolfgang
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The development of 5G networks has enabled support for a vast number of applications with stringent traffic requirements, both in terms of communication and computation. Furthermore, the proximity of the entities, such as edge servers and User Plane Functions (UPFs) that provide these resources is of paramount importance. However, with the ever-increasing demand from these applications, operators often find their resources insufficient to accommodate all requests. Some of these demands can be forwarded to external entities, not owned by the operator. This introduces a cost, reducing the operator's profit. Hence, to maximize operator's profit, it is important to place the demands optimally in internal or external edge nodes. To this end, we formulate a constrained optimization problem that captures this objective and the inter-play between different parameters, which turns out to be NP-hard. Therefore, we resort to proposing a heuristic algorithm which ranks the demands according to their value to the operator and amount of resources they need. Results show that our approach outperforms the benchmark algorithms, deviating from the optimal solution by only 3% on average.
AB - The development of 5G networks has enabled support for a vast number of applications with stringent traffic requirements, both in terms of communication and computation. Furthermore, the proximity of the entities, such as edge servers and User Plane Functions (UPFs) that provide these resources is of paramount importance. However, with the ever-increasing demand from these applications, operators often find their resources insufficient to accommodate all requests. Some of these demands can be forwarded to external entities, not owned by the operator. This introduces a cost, reducing the operator's profit. Hence, to maximize operator's profit, it is important to place the demands optimally in internal or external edge nodes. To this end, we formulate a constrained optimization problem that captures this objective and the inter-play between different parameters, which turns out to be NP-hard. Therefore, we resort to proposing a heuristic algorithm which ranks the demands according to their value to the operator and amount of resources they need. Results show that our approach outperforms the benchmark algorithms, deviating from the optimal solution by only 3% on average.
KW - 5G core
KW - Edge clouds
KW - Routing
KW - UPF
UR - http://www.scopus.com/inward/record.url?scp=85210253479&partnerID=8YFLogxK
U2 - 10.1109/MASS62177.2024.00065
DO - 10.1109/MASS62177.2024.00065
M3 - Conference contribution
AN - SCOPUS:85210253479
T3 - Proceedings - 2024 IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems, MASS 2024
SP - 446
EP - 452
BT - Proceedings - 2024 IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems, MASS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st IEEE International Conference on Mobile Ad-Hoc and Smart Systems, MASS 2024
Y2 - 23 September 2024 through 25 September 2024
ER -