One Computer Science MSc thesis to be presented on 17 May

Friday, 17 May there will be a master thesis presentation in Computer Science at Lund University, Faculty of Engineering.

The presentation will take place in E:4130 (LUCAS).

Note to potential opponents: Register as an opponent to the presentation of your choice by sending an email to the examiner for that presentation (firstname.lastname@cs.lth.se). Do not forget to specify the presentation you register for! Note that the number of opponents may be limited (often to two), so you might be forced to choose another presentation if you register too late. Registrations are individual, just as the oppositions are! More instructions are found on this page.

14:15-15:00 in E:4130 (LUCAS)

Presenters: Hannes Brinklert, Johan Åkerman
Title: Navigating Failures in Distributed Systems: A Comparative Study of Failure Detection Algorithms
Examiner: Michael Doggett
Supervisors: Jonas Skeppstedt (LTH), Aleksey Karasavov (Neo4j)

Failure detection algorithms are used to identify unhealthy nodes in distributed systems. The goal of this study was to improve Neo4j's use of failure detection algorithms by exploring two paths: either optimizing their existing Lighthouse algorithm or by implementing a new algorithm.

Existing algorithms were surveyed and the SWIM algorithm was implemented. A baseline was established and evaluated against parameter-optimised versions of SWIM and Lighthouse in a simulated network. The results show that Baseline is scalable and reliable but slow, Lighthouse is fast but less accurate, and SWIM is moderately fast and the least accurate but generates the least network load.

In conclusion, the chosen parameters of a failure detector are to a great extent more important than the algorithm itself. Furthermore, to successfully optimise parameters it is crucial to have a scalable simulator and precise system requirement to manage the trade-off between speed, accuracy, and network load.

Link to popular science summary: https://fileadmin.cs.lth.se/cs/Education/Examensarbete/Popsci/240517_14BrinklertAkerman.pdf