Agnihotri, Pratyush (2021)
Autonomous Resource Management in Distributed Stream Processing Systems.
22nd International Middleware Conference: Doctoral Symposium. virtual Conference (06.12.2021-10.12.2021)
doi: 10.1145/3491087.3493680
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Resource management in Distributed Stream Processing Systems (DSPS) defines the way queries are deployed on in-network resources to deliver query results while fulfilling the Quality of Service (QoS) requirements of the end-users. Various resource management mechanisms have been proposed in DSPS; however, they become inefficient in challenging conditions imposed by the dynamic environment and heterogeneous resources. This is because they focus on pre-configuration of both single and static QoS requirements. In addition, they lack cooperation between heterogeneous resources which amplify the problem of coordination between resources. This could lead to severe performance degradation such as inconsistent and incorrect query results in comparison to homogeneous resources. To solve the above challenges, in this research work, we will propose mechanisms: (i) to forecast the performance of network and heterogeneous resources, (ii) to select an efficient resource management approach, and (iii) for cooperation between resources in a dynamic environment.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2021 |
| Autor(en): | Agnihotri, Pratyush |
| Art des Eintrags: | Bibliographie |
| Titel: | Autonomous Resource Management in Distributed Stream Processing Systems |
| Sprache: | Englisch |
| Publikationsjahr: | 6 Dezember 2021 |
| Verlag: | ACM |
| Buchtitel: | Middleware '21: Proceedings of the 22nd International Middleware Conference: Doctoral Symposium |
| Veranstaltungstitel: | 22nd International Middleware Conference: Doctoral Symposium |
| Veranstaltungsort: | virtual Conference |
| Veranstaltungsdatum: | 06.12.2021-10.12.2021 |
| DOI: | 10.1145/3491087.3493680 |
| Kurzbeschreibung (Abstract): | Resource management in Distributed Stream Processing Systems (DSPS) defines the way queries are deployed on in-network resources to deliver query results while fulfilling the Quality of Service (QoS) requirements of the end-users. Various resource management mechanisms have been proposed in DSPS; however, they become inefficient in challenging conditions imposed by the dynamic environment and heterogeneous resources. This is because they focus on pre-configuration of both single and static QoS requirements. In addition, they lack cooperation between heterogeneous resources which amplify the problem of coordination between resources. This could lead to severe performance degradation such as inconsistent and incorrect query results in comparison to homogeneous resources. To solve the above challenges, in this research work, we will propose mechanisms: (i) to forecast the performance of network and heterogeneous resources, (ii) to select an efficient resource management approach, and (iii) for cooperation between resources in a dynamic environment. |
| Freie Schlagworte: | C2 |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik > Multimedia Kommunikation 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 > C: Kommunikationsmechanismen DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet > C: Kommunikationsmechanismen > Teilprojekt C2: Informationszentrische Sicht |
| Hinterlegungsdatum: | 21 Apr 2022 07:43 |
| Letzte Änderung: | 17 Dez 2024 10:34 |
| PPN: | 496007971 |
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