A QoE and Availability-Aware Framework for Network Slice Placement and Resource Allocation
In 5G networks, the deployment of network slices enabled by Software-Defined Networking (SDN) is becoming a critical component for delivering tailored services to meet diverse application needs. However, this introduces challenges in network management, particularly in efficiently allocating resourc...
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2025-01-01
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| author | Gergely Dobreff Attila Bader Alija Pasic |
| author_facet | Gergely Dobreff Attila Bader Alija Pasic |
| author_sort | Gergely Dobreff |
| collection | DOAJ |
| description | In 5G networks, the deployment of network slices enabled by Software-Defined Networking (SDN) is becoming a critical component for delivering tailored services to meet diverse application needs. However, this introduces challenges in network management, particularly in efficiently allocating resources to ensure that each network slice meets its specific Quality of Service (QoS) and availability requirements. Simultaneously, it must optimize overall network performance and network operator’s profit, which is linked to the Quality of Experience (QoE) of the end-users. Existing works offer either an availability-based solution or a QoE-aware solution to this problem, but not both. This paper addresses the end-to-end network slice resource allocation problem by simultaneously considering QoS and availability requirements in slice placement, while employing a QoE-aware strategy for resource allocation. We propose a framework that optimizes the network operator profit i.e. the highest QoE with the least resource usage, and can be flexibly configured to model realistic scenarios. Arbitrary network slice requirements can be defined using slice-specific QoS/QoE mapping, resource requirements, end-to-end latency and availability. For solving the formulated problem a Mixed Integer Nonlinear Programming (MINLP) formulation and efficient heuristic methods are proposed. Our solution accounts for the non-linear QoS/QoE relationship, utilizes redundantly placed Service Function Chains (SFCs) to increase availability, and supports the sharing of Virtual Network Functions (VNFs) among SFCs to optimize resource usage. Through extensive simulations on realistic network topologies and slice requests, we demonstrate the framework’s effectiveness in offering flexible and efficient network slice placement and resource allocation, utilizing a baseline heuristic from related studies. The results indicate that while the exact method delivers an optimal solution, heuristic approaches are suitable for time-sensitive tasks, such as dynamic slice configuration. |
| format | Article |
| id | doaj-art-2f334b80b78e487e8fb5e4cba8c47418 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-2f334b80b78e487e8fb5e4cba8c474182025-01-07T00:01:37ZengIEEEIEEE Access2169-35362025-01-01131481149510.1109/ACCESS.2024.352390010818479A QoE and Availability-Aware Framework for Network Slice Placement and Resource AllocationGergely Dobreff0https://orcid.org/0000-0003-0226-6139Attila Bader1Alija Pasic2https://orcid.org/0000-0001-6346-496XDepartment of Telecommunications and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, HungaryEricsson Hungary, Budapest, HungaryDepartment of Telecommunications and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, HungaryIn 5G networks, the deployment of network slices enabled by Software-Defined Networking (SDN) is becoming a critical component for delivering tailored services to meet diverse application needs. However, this introduces challenges in network management, particularly in efficiently allocating resources to ensure that each network slice meets its specific Quality of Service (QoS) and availability requirements. Simultaneously, it must optimize overall network performance and network operator’s profit, which is linked to the Quality of Experience (QoE) of the end-users. Existing works offer either an availability-based solution or a QoE-aware solution to this problem, but not both. This paper addresses the end-to-end network slice resource allocation problem by simultaneously considering QoS and availability requirements in slice placement, while employing a QoE-aware strategy for resource allocation. We propose a framework that optimizes the network operator profit i.e. the highest QoE with the least resource usage, and can be flexibly configured to model realistic scenarios. Arbitrary network slice requirements can be defined using slice-specific QoS/QoE mapping, resource requirements, end-to-end latency and availability. For solving the formulated problem a Mixed Integer Nonlinear Programming (MINLP) formulation and efficient heuristic methods are proposed. Our solution accounts for the non-linear QoS/QoE relationship, utilizes redundantly placed Service Function Chains (SFCs) to increase availability, and supports the sharing of Virtual Network Functions (VNFs) among SFCs to optimize resource usage. Through extensive simulations on realistic network topologies and slice requests, we demonstrate the framework’s effectiveness in offering flexible and efficient network slice placement and resource allocation, utilizing a baseline heuristic from related studies. The results indicate that while the exact method delivers an optimal solution, heuristic approaches are suitable for time-sensitive tasks, such as dynamic slice configuration.https://ieeexplore.ieee.org/document/10818479/Availabilitymixed integer nonlinear programmingE2E network slicingplacementquality of experience (QoE)quality of service (QoS) |
| spellingShingle | Gergely Dobreff Attila Bader Alija Pasic A QoE and Availability-Aware Framework for Network Slice Placement and Resource Allocation IEEE Access Availability mixed integer nonlinear programming E2E network slicing placement quality of experience (QoE) quality of service (QoS) |
| title | A QoE and Availability-Aware Framework for Network Slice Placement and Resource Allocation |
| title_full | A QoE and Availability-Aware Framework for Network Slice Placement and Resource Allocation |
| title_fullStr | A QoE and Availability-Aware Framework for Network Slice Placement and Resource Allocation |
| title_full_unstemmed | A QoE and Availability-Aware Framework for Network Slice Placement and Resource Allocation |
| title_short | A QoE and Availability-Aware Framework for Network Slice Placement and Resource Allocation |
| title_sort | qoe and availability aware framework for network slice placement and resource allocation |
| topic | Availability mixed integer nonlinear programming E2E network slicing placement quality of experience (QoE) quality of service (QoS) |
| url | https://ieeexplore.ieee.org/document/10818479/ |
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