Tahir, Anam ; Alt, Bastian ; Rizk, Amr ; Koeppl, Heinz (2023)
Load Balancing in Compute Clusters with Delayed Feedback.
In: IEEE Transactions on Computers, 72 (6)
doi: 10.1109/TC.2022.3215907
Artikel, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
Load balancing arises as a fundamental problem, underlying the dimensioning and operation of many computing andcommunication systems, such as job routing in data center clusters, multipath communication, Big Data and queueing systems. Inessence, the decision-making agent maps each arriving job to one of the possibly heterogeneous servers while aiming at anoptimization goal such as load balancing, low average delay or low loss rate. One main difficulty in finding optimal load balancingpolicies here is that the agent only partially observes the impact of its decisions, e.g., through the delayed acknowledgements of theserved jobs. In this paper, we provide a partially observable (PO) model that captures the load balancing decisions in parallel bufferedsystems under limited information of delayed acknowledgements. We present a simulation model for this PO system to find a loadbalancing policy in real-time using a scalable Monte Carlo tree search algorithm. We numerically show that the resulting policyoutperforms other limited information load balancing strategies such as variants of Join-the-Most-Observations and has comparableperformance to full information strategies like: Join-the-Shortest-Queue, Join-the-Shortest-Queue(d) and Shortest-Expected-Delay.Finally, we show that our approach can optimise the real-time parallel processing by using network data provided by Kaggle.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Tahir, Anam ; Alt, Bastian ; Rizk, Amr ; Koeppl, Heinz |
| Art des Eintrags: | Bibliographie |
| Titel: | Load Balancing in Compute Clusters with Delayed Feedback |
| Sprache: | Englisch |
| Publikationsjahr: | 1 Juni 2023 |
| Verlag: | IEEE |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IEEE Transactions on Computers |
| Jahrgang/Volume einer Zeitschrift: | 72 |
| (Heft-)Nummer: | 6 |
| Kollation: | 13 Seiten |
| DOI: | 10.1109/TC.2022.3215907 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | Load balancing arises as a fundamental problem, underlying the dimensioning and operation of many computing andcommunication systems, such as job routing in data center clusters, multipath communication, Big Data and queueing systems. Inessence, the decision-making agent maps each arriving job to one of the possibly heterogeneous servers while aiming at anoptimization goal such as load balancing, low average delay or low loss rate. One main difficulty in finding optimal load balancingpolicies here is that the agent only partially observes the impact of its decisions, e.g., through the delayed acknowledgements of theserved jobs. In this paper, we provide a partially observable (PO) model that captures the load balancing decisions in parallel bufferedsystems under limited information of delayed acknowledgements. We present a simulation model for this PO system to find a loadbalancing policy in real-time using a scalable Monte Carlo tree search algorithm. We numerically show that the resulting policyoutperforms other limited information load balancing strategies such as variants of Join-the-Most-Observations and has comparableperformance to full information strategies like: Join-the-Shortest-Queue, Join-the-Shortest-Queue(d) and Shortest-Expected-Delay.Finally, we show that our approach can optimise the real-time parallel processing by using network data provided by Kaggle. |
| Freie Schlagworte: | Parallel systems, load balancing, partial observability |
| Zusätzliche Informationen: | Erstveröffentlichung |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Self-Organizing Systems Lab DFG-Sonderforschungsbereiche (inkl. Transregio) DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet > B: Adaptionsmechanismen DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet > B: Adaptionsmechanismen > Teilprojekt B4: Planung DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet > C: Kommunikationsmechanismen DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet > C: Kommunikationsmechanismen > Teilprojekt C3: Inhaltszentrische Sicht |
| Hinterlegungsdatum: | 06 Jun 2023 11:59 |
| Letzte Änderung: | 11 Okt 2024 14:43 |
| PPN: | 510085253 |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
Verfügbare Versionen dieses Eintrags
-
Load Balancing in Compute Clusters With Delayed Feedback. (deposited 30 Sep 2024 09:48)
- Load Balancing in Compute Clusters with Delayed Feedback. (deposited 06 Jun 2023 11:59) [Gegenwärtig angezeigt]
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum