logo SBA

ETD

Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-07062022-122510


Tipo di tesi
Tesi di laurea magistrale
Autore
FRASCA, FAUSTO FRANCESCO
URN
etd-07062022-122510
Titolo
Evaluating Linux Kernel Mechanisms for Scheduling Streaming Queries on Multicores
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA
Relatori
relatore Prof. Mencagli, Gabriele
relatore Prof. Rodríguez Moreno, Andrés
Parole chiave
  • data stream processing
  • middleware
  • real-time thread
  • scheduling
Data inizio appello
22/07/2022
Consultabilità
Completa
Riassunto
Recent years have seen a growth in the volume of available data, often in the form of streams, produced by various sources (social networks, IoT devices and so on). One of the objectives of the data stream processing paradigm is to analyse this volume of data in order to extract information, alerts and knowledge. Whereas in the past stream processing was carried out on centralised platforms such as clouds or clusters of workstations, the trend today is to perform parts of the analysis of streaming data close to those who produce it, i.e., at the edge of highly distributed computing systems where resources are limited. Because of the limited resources available, a scheduling of these applications that takes into account specific metrics within the application itself ensures a gain in performance. The purpose of Lachesis, a middleware developed by the Parallel Programming Models research group of the University of Pisa and the Distributed Systems group at the Chalmers University of Technology, is to help the operating system scheduler to better schedule data stream processing applications. Building on what had been done with Lachesis in the past, in this thesis we explore new optimisations and kernel mechanisms that allow Lachesis to apply a finer and more effective scheduling of running applications, by taking advantage of mechanisms offered by the operating system that had never been tested before. The experiments, conducted on an Edge computing device, showed improvements in both throughput and latency over both the original version of Lachesis and the OS scheduler.
File