TU Darmstadt / ULB / TUbiblio

Dynamic Multi-objective Scheduling of Microservices in the Cloud

Fard, Hamid Mohammadi ; Prodan, Radu ; Wolf, Felix (2020)
Dynamic Multi-objective Scheduling of Microservices in the Cloud.
13th International Conference on Utility and Cloud Computing (UCC 2020). virtual Conference (07.-10.12.2020)
doi: 10.1109/UCC48980.2020.00061
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

For many applications, a microservices architecture promises better performance and flexibility compared to a conventional monolithic architecture. In spite of the advantages of a microservices architecture, deploying microservices poses various challenges for service developers and providers alike. One of these challenges is the efficient placement of microservices on the cluster nodes. Improper allocation of microservices can quickly waste resource capacities and cause low system throughput. In the last few years, new technologies in orchestration frameworks, such as the possibility of multiple schedulers for pods in Kubernetes, have improved scheduling solutions of microservices but using these technologies needs to involve both the service developer and the service provider in the behavior analysis of workloads. Using memory and CPU requests specified in the service manifest, we propose a general microservices scheduling mechanism that can operate efficiently in private clusters or enterprise clouds. We model the scheduling problem as a complex variant of the knapsack problem and solve it using a multi-objective optimization approach. Our experiments show that the proposed mechanism is highly scalable and simultaneously increases utilization of both memory and CPU, which in turn leads to better throughput when compared to the state-of-the-art.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2020
Autor(en): Fard, Hamid Mohammadi ; Prodan, Radu ; Wolf, Felix
Art des Eintrags: Bibliographie
Titel: Dynamic Multi-objective Scheduling of Microservices in the Cloud
Sprache: Englisch
Publikationsjahr: 30 Dezember 2020
Verlag: IEEE
Buchtitel: Proceedings: 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing
Veranstaltungstitel: 13th International Conference on Utility and Cloud Computing (UCC 2020)
Veranstaltungsort: virtual Conference
Veranstaltungsdatum: 07.-10.12.2020
DOI: 10.1109/UCC48980.2020.00061
Kurzbeschreibung (Abstract):

For many applications, a microservices architecture promises better performance and flexibility compared to a conventional monolithic architecture. In spite of the advantages of a microservices architecture, deploying microservices poses various challenges for service developers and providers alike. One of these challenges is the efficient placement of microservices on the cluster nodes. Improper allocation of microservices can quickly waste resource capacities and cause low system throughput. In the last few years, new technologies in orchestration frameworks, such as the possibility of multiple schedulers for pods in Kubernetes, have improved scheduling solutions of microservices but using these technologies needs to involve both the service developer and the service provider in the behavior analysis of workloads. Using memory and CPU requests specified in the service manifest, we propose a general microservices scheduling mechanism that can operate efficiently in private clusters or enterprise clouds. We model the scheduling problem as a complex variant of the knapsack problem and solve it using a multi-objective optimization approach. Our experiments show that the proposed mechanism is highly scalable and simultaneously increases utilization of both memory and CPU, which in turn leads to better throughput when compared to the state-of-the-art.

Freie Schlagworte: EU|GA 785907, EU|GA 945539, DFG|323299120, EU, DFG
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Parallele Programmierung
Hinterlegungsdatum: 04 Apr 2024 09:57
Letzte Änderung: 04 Apr 2024 09:57
PPN:
Export:
Suche nach Titel in: TUfind oder in Google
Frage zum Eintrag Frage zum Eintrag

Optionen (nur für Redakteure)
Redaktionelle Details anzeigen Redaktionelle Details anzeigen