Delay aware resource allocation in ORAN through network optimization
Abstract A multi variable resource allocation problem is investigated in network environments, specifically focusing on the consideration of quality of service in open radio access network. The main objective is to minimise the combined latency of various servers while complying with network limitat...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-12-01
|
| Series: | IET Wireless Sensor Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/wss2.12087 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846110621957881856 |
|---|---|
| author | Basit N. Khalaf Wisam Hasan Ali Raad S. Alhumaima Haider Ali Jasim Alshamary |
| author_facet | Basit N. Khalaf Wisam Hasan Ali Raad S. Alhumaima Haider Ali Jasim Alshamary |
| author_sort | Basit N. Khalaf |
| collection | DOAJ |
| description | Abstract A multi variable resource allocation problem is investigated in network environments, specifically focusing on the consideration of quality of service in open radio access network. The main objective is to minimise the combined latency of various servers while complying with network limitations. The delay of each server is represented by a non‐linear function that has exponentially based. This characteristic inherently brings non‐convexity into the objective function. In contrast, the constraints comprise various linear combinations of network variables, including resource block allocations, power consumption, and number of virtual machines. The purpose of these constraints is to guarantee that the allocation of resources adheres to practical limitations and upholds fairness among servers. Nevertheless, the inclusion of a non‐convex objective function significantly adds complexity to the optimisation problem and non‐convex behaviour, requiring specialised algorithms and techniques to identify solutions. Subsequently, the Lagrange multiplier method has been used to solve this problem mathematically. Numerically, three algorithms have been utilised and compared to solve the problem, these are active‐set, interior point and sequential quadratic programming. Note that the total delay as an objective function is based on the total power consumption of the servers. Previous to optimising the total delay, a delay model is proposed and compared with two research works that are based on experimental and real time data. The proposed model shows data matching with the other works and permits for more adaptation/integration with any other works that uses different servers’ characteristics and network parameters. |
| format | Article |
| id | doaj-art-8d82f32f5bb24e7ab93df98eb05a8d46 |
| institution | Kabale University |
| issn | 2043-6386 2043-6394 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Wireless Sensor Systems |
| spelling | doaj-art-8d82f32f5bb24e7ab93df98eb05a8d462024-12-23T18:42:04ZengWileyIET Wireless Sensor Systems2043-63862043-63942024-12-0114652853810.1049/wss2.12087Delay aware resource allocation in ORAN through network optimizationBasit N. Khalaf0Wisam Hasan Ali1Raad S. Alhumaima2Haider Ali Jasim Alshamary3Department of Communications University of Diyala Baqubah Diyala IraqDepartment of Computers Middle Technical University Baqubah Diyala IraqDepartment of Communications University of Diyala Baqubah Diyala IraqDepartment of Communications University of Diyala Baqubah Diyala IraqAbstract A multi variable resource allocation problem is investigated in network environments, specifically focusing on the consideration of quality of service in open radio access network. The main objective is to minimise the combined latency of various servers while complying with network limitations. The delay of each server is represented by a non‐linear function that has exponentially based. This characteristic inherently brings non‐convexity into the objective function. In contrast, the constraints comprise various linear combinations of network variables, including resource block allocations, power consumption, and number of virtual machines. The purpose of these constraints is to guarantee that the allocation of resources adheres to practical limitations and upholds fairness among servers. Nevertheless, the inclusion of a non‐convex objective function significantly adds complexity to the optimisation problem and non‐convex behaviour, requiring specialised algorithms and techniques to identify solutions. Subsequently, the Lagrange multiplier method has been used to solve this problem mathematically. Numerically, three algorithms have been utilised and compared to solve the problem, these are active‐set, interior point and sequential quadratic programming. Note that the total delay as an objective function is based on the total power consumption of the servers. Previous to optimising the total delay, a delay model is proposed and compared with two research works that are based on experimental and real time data. The proposed model shows data matching with the other works and permits for more adaptation/integration with any other works that uses different servers’ characteristics and network parameters.https://doi.org/10.1049/wss2.12087delaysmobile communicationoptimisation |
| spellingShingle | Basit N. Khalaf Wisam Hasan Ali Raad S. Alhumaima Haider Ali Jasim Alshamary Delay aware resource allocation in ORAN through network optimization IET Wireless Sensor Systems delays mobile communication optimisation |
| title | Delay aware resource allocation in ORAN through network optimization |
| title_full | Delay aware resource allocation in ORAN through network optimization |
| title_fullStr | Delay aware resource allocation in ORAN through network optimization |
| title_full_unstemmed | Delay aware resource allocation in ORAN through network optimization |
| title_short | Delay aware resource allocation in ORAN through network optimization |
| title_sort | delay aware resource allocation in oran through network optimization |
| topic | delays mobile communication optimisation |
| url | https://doi.org/10.1049/wss2.12087 |
| work_keys_str_mv | AT basitnkhalaf delayawareresourceallocationinoranthroughnetworkoptimization AT wisamhasanali delayawareresourceallocationinoranthroughnetworkoptimization AT raadsalhumaima delayawareresourceallocationinoranthroughnetworkoptimization AT haideralijasimalshamary delayawareresourceallocationinoranthroughnetworkoptimization |