X-MAPE: Extending 6G-Connected Self-Adaptive Systems with Reflexive Actions
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
Future connected applications require distributed processing on different layers in the network to orchestrate and optimize their behavior. This necessitates a change in the processing architecture, especially regarding the ability to self-adapt to changing circumstances, such as environmental changes or fault scenarios. Self-adaptivity in computing systems was previously often achieved with the MAPE-K concept. However, in real-time and low-latency environments with a distributed, hierarchical processing architecture, the reaction time of the MAPE-K cycle can be limited by its complexity. In this paper, we propose a possible solution to a quicker reaction by introducing X-MAPE: extending self-adaptivity with predefined, configurable, reflexive actions. In essence, X-MAPE aims to construct a low-latency path between monitoring the system and executing actions to influence it, to reflexively react to a changing system state and improving the system's behavior until a more optimal decision can be made in a less time-critical manner. We present possible realizations of this principle on different layers and components of future 6G networks, providing a vision and framework for adaptive computing systems with reflexive reactions.
Details
Originalsprache | Englisch |
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Titel | 2023 IEEE Conference on Network Function Virtualization and Software Defined Networks, NFV-SDN 2023 - Proceedings |
Redakteure/-innen | Frank H.P. Fitzek, Larry Horner, Molka Gharbaoui, Giang Nguyen, Rentao Gu, Tobias Meuser |
Herausgeber (Verlag) | IEEE |
Seiten | 163-167 |
Seitenumfang | 5 |
ISBN (elektronisch) | 9798350302547 |
ISBN (Print) | 979-8-3503-0255-4 |
Publikationsstatus | Veröffentlicht - 9 Nov. 2023 |
Peer-Review-Status | Ja |
Konferenz
Titel | 2023 IEEE Conference on Network Function Virtualization and Software Defined Networks |
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Kurztitel | IEEE NFV-SDN 2023 |
Veranstaltungsnummer | 9 |
Dauer | 7 - 9 November 2023 |
Webseite | |
Bekanntheitsgrad | Internationale Veranstaltung |
Ort | TU Dresden |
Stadt | Dresden |
Land | Deutschland |
Externe IDs
ORCID | /0000-0001-7436-0103/work/148605968 |
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ORCID | /0000-0003-2571-8441/work/148605977 |
ORCID | /0000-0002-6200-4707/work/148606614 |
ORCID | /0000-0002-0757-3325/work/148607142 |
Scopus | 85180374394 |
Mendeley | 9ab306ac-d74b-3cea-829e-9121e3877b0b |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- 6G mobile communication, Distributed processing, Computer architecture, Real-time systems, Behavioral sciences, Network function virtualization, Time factors, 6G, Autonomic Computing, Self-adaptive