Wirth, Maximilian ; Ortiz Jimenez, Andrea Patricia ; Klein, Anja (2023)
Contextual Multi-Armed Bandits for Non-Stationary Heterogeneous Mobile Edge Computing.
2023 IEEE Global Communications Conference. Kuala Lumpur, Malaysia (04.12.2023-08.12.2023)
doi: 10.1109/GLOBECOM54140.2023.10437572
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Base station (BS) selection for task offloading in Mobile Edge Computing (MEC) is a challenging problem due to the dynamic nature of MEC systems. The wireless channel as well as the load of BSs are stochastic quantities that can change in a statistically non-stationary fashion. Moreover, the computation capabilities of the BSs are heterogeneous. As the dynamic behaviour of a MEC system is, in practical scenarios, not known in advance, deciding where to offload has to be done under uncertainty about the MEC system and considering its non-stationary and heterogeneous characteristics. This paper in- vestigates latency minimization in MEC with heterogeneous BSs. In order to meet low latency demands, a mobile unit (MU) has to quickly identify the best BS for offloading different computation tasks while facing uncertainty about the non-stationary system dynamics. To solve this problem, we propose a novel piece-wise stationary contextual Multi-Armed Bandit (MAB) algorithm that treats different task types as context and detects non-stationary changes in the BSs’ performance. With the use of extensive simulations, we show that our proposed approach outperforms state-of-the-art algorithms, as it quickly adapts to changes in the MEC system and exhibits no penalty during stationary phases.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Wirth, Maximilian ; Ortiz Jimenez, Andrea Patricia ; Klein, Anja |
| Art des Eintrags: | Bibliographie |
| Titel: | Contextual Multi-Armed Bandits for Non-Stationary Heterogeneous Mobile Edge Computing |
| Sprache: | Englisch |
| Publikationsjahr: | 4 Dezember 2023 |
| Veranstaltungstitel: | 2023 IEEE Global Communications Conference |
| Veranstaltungsort: | Kuala Lumpur, Malaysia |
| Veranstaltungsdatum: | 04.12.2023-08.12.2023 |
| DOI: | 10.1109/GLOBECOM54140.2023.10437572 |
| URL / URN: | https://ieeexplore.ieee.org/abstract/document/10437572 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | Base station (BS) selection for task offloading in Mobile Edge Computing (MEC) is a challenging problem due to the dynamic nature of MEC systems. The wireless channel as well as the load of BSs are stochastic quantities that can change in a statistically non-stationary fashion. Moreover, the computation capabilities of the BSs are heterogeneous. As the dynamic behaviour of a MEC system is, in practical scenarios, not known in advance, deciding where to offload has to be done under uncertainty about the MEC system and considering its non-stationary and heterogeneous characteristics. This paper in- vestigates latency minimization in MEC with heterogeneous BSs. In order to meet low latency demands, a mobile unit (MU) has to quickly identify the best BS for offloading different computation tasks while facing uncertainty about the non-stationary system dynamics. To solve this problem, we propose a novel piece-wise stationary contextual Multi-Armed Bandit (MAB) algorithm that treats different task types as context and detects non-stationary changes in the BSs’ performance. With the use of extensive simulations, we show that our proposed approach outperforms state-of-the-art algorithms, as it quickly adapts to changes in the MEC system and exhibits no penalty during stationary phases. |
| Freie Schlagworte: | Open6GHub, emergenCITY, emergenCITY_KOM |
| Zusätzliche Informationen: | Selected Areas in Communications: Cloud/edge Computing, Networking, and Data Storage |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Kommunikationstechnik DFG-Sonderforschungsbereiche (inkl. Transregio) DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche LOEWE LOEWE > LOEWE-Zentren LOEWE > LOEWE-Zentren > emergenCITY DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet |
| Hinterlegungsdatum: | 25 Jan 2024 10:46 |
| Letzte Änderung: | 30 Apr 2024 05:51 |
| PPN: | 517663546 |
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