Joint Wireless and Computing Resource Management with Optimal Slice Selection in in-network-edge Metaverse System

This paper presents an approach to joint wireless and computing resource management in slice-enabled metaverse networks, addressing the challenges of inter-slice and intra-slice resource allocation in the presence of in-network computing. We formulate the problem as a mixed-integer nonlinear programming (MINLP) problem and derive an optimal solution using standard optimization techniques. Through extensive simulations, we demonstrate that our proposed method significantly improves system performance by effectively balancing the allocation of radio and computing resources across multiple slices. Our approach outperforms existing benchmarks, particularly in scenarios with high user demand and varying computational tasks.

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Publication Details

Published
2024-10-16
DOI
https://doi.org/10.1109/ictc62082.2024.10827552
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.35

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article

Joint Wireless and Computing Resource Management with Optimal Slice Selection in in-network-edge Metaverse System

Minsoo Hahn, Ibrahim Aliyu, Abubakar Isah, Sangwon Oh et al.
1 citations
IoT and Edge/Fog Computing
0.35
article

Joint Wireless and Computing Resource Management with Optimal Slice Selection in in-network-edge Metaverse System

Minsoo Hahn, Ibrahim Aliyu, Abubakar Isah, Sangwon Oh, Jinsul Kim, Jihoon Lee, Sulaiman Muhammad Rashid
article en
1 citations

Abstract

This paper presents an approach to joint wireless and computing resource management in slice-enabled metaverse networks, addressing the challenges of inter-slice and intra-slice resource allocation in the presence of in-network computing. We formulate the problem as a mixed-integer nonlinear programming (MINLP) problem and derive an optimal solution using standard optimization techniques. Through extensive simulations, we demonstrate that our proposed method significantly improves system performance by effectively balancing the allocation of radio and computing resources across multiple slices. Our approach outperforms existing benchmarks, particularly in scenarios with high user demand and varying computational tasks.

Chonnam National University (KR), Astana Medical University (KZ)
Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion, Division of Human Resource Development
Decent work and economic growth
Openalex Percentile: Top 34%
IoT and Edge/Fog Computing
0.35
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Joint Wireless and Computing Resource Management with Optimal Slice Selection in in-network-edge Metaverse System — Minsoo Hahn, Ibrahim Aliyu, et al. · (2024) | TGRS Research Map | TGRS