Near-optimal cloud-network integrated resource allocation for latency-sensitive B5G |
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Author: | Shokrnezhad, Masoud1; Taleb, Tarik1 |
Organizations: |
1Centre for Wireless Communications (CWC), Oulu University, Oulu, Finland |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 1 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2023020625930 |
Language: | English |
Published: |
IEEE,
2022
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Publish Date: | 2023-02-06 |
Description: |
AbstractNowadays, while the demand for capacity continues to expand, the blossoming of Internet of Everything is bringing in a paradigm shift to new perceptions of communication networks, ushering in a plethora of totally unique services. To provide these services, Virtual Network Functions (VNFs) must be established and reachable by end-users, which will generate and consume massive volumes of data that must be processed locally for service responsiveness and scalability. For this to be realized, a solid cloud-network Integrated infrastructure is a necessity, and since cloud and network domains would be diverse in terms of characteristics but limited in terms of capability, communication and computing resources should be jointly controlled to unleash its full potential. Although several innovative methods have been proposed to allocate the resources, most of them either ignored network resources or relaxed the network as a simple graph, which are not applicable to Beyond 5G because of its dynamism and stringent QoS requirements. This paper fills in the gap by studying the joint problem of communication and computing resource allocation, dubbed CCRA, including VNF placement and assignment, traffic prioritization, and path selection considering capacity constraints as well as link and queuing delays, with the goal of minimizing overall cost. We formulate the problem as a non-linear programming model, and propose two approaches, dubbed B&B-CCRA and WF-CCRA respectively, based on the Branch & Bound and Water-Filling algorithms. Numerical simulations show that B&B-CCRA can solve the problem optimally, whereas WF-CCRA can provide near-optimal solutions in significantly less time. see all
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ISBN: | 978-1-6654-3540-6 |
ISBN Print: | 978-1-6654-3541-3 |
Pages: | 4498 - 4503 |
DOI: | 10.1109/globecom48099.2022.10001109 |
OADOI: | https://oadoi.org/10.1109/globecom48099.2022.10001109 |
Host publication: |
GLOBECOM 2022 : 2022 IEEE Global Communications Conference |
Conference: |
IEEE Global Communications Conference |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
213 Electronic, automation and communications engineering, electronics |
Subjects: | |
Funding: |
This research work is partially supported by the Academy of Finland 6G Flagship, by the European Union’s Horizon 2020 ICT Cloud Computing program under the ACCORDION project with grant agreement No. 871793, and by the European Union’s Horizon 2020 research and innovation program under the CHARITY project with grant agreement No. 101016509. It is also partially funded by the Academy of Finland Project 6Genesis under grant agreements No. 318927. |
Academy of Finland Grant Number: |
318927 |
Detailed Information: |
318927 (Academy of Finland Funding decision) |
Copyright information: |
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