Skip to main content
Kent Academic Repository

Scheduling Hard Real-Time Garbage Collection

Kalibera, Tomas and Pizlo, Filip and Hosking, Antony L. and Vitek, Jan (2009) Scheduling Hard Real-Time Garbage Collection. In: 2009 30th IEEE Real-Time Systems Symposium. IEEE, pp. 182-196. ISBN 978-0-7695-3875-4. (doi:10.1109/RTSS.2009.40) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:30567)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/RTSS.2009.40

Abstract

Managed languages such as Java and C# are increasingly being considered for hard real-time applications because of their productivity and software engineering advantages. Automatic memory management, or garbage collection, is a key enabler for robust, reusable libraries, yet remains a challenge for analysis and implementation of real-time execution environments. This paper comprehensively compares the two leading approaches to hard real-time garbage collection. While there are many design decisions involved in selecting a real-time garbage collection algorithm, for time-based garbage collectors researchers and practitioners remain undecided as to whether to choose periodic scheduling or slack-based scheduling. A significant impediment to valid experimental comparison is that the commercial implementations use completely different proprietary infrastructures. Here, we present Minuteman, a framework for experimenting with real-time collection algorithms in the context of a high-performance execution environment for real-time Java. We provide the first comparison of the two approaches, both experimentally using realistic workloads, and analytically in terms of schedulability.

Item Type: Book section
DOI/Identification number: 10.1109/RTSS.2009.40
Uncontrolled keywords: determinacy analysis; Craig interpolants; Java; engineering management; application software; productivity; software engineering; memory management; environmental management; robustness; software libraries; algorithm design and analysis
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Tomas Kalibera
Date Deposited: 21 Sep 2012 09:49 UTC
Last Modified: 16 Nov 2021 10:08 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/30567 (The current URI for this page, for reference purposes)

University of Kent Author Information

Kalibera, Tomas.

Creator's ORCID:
CReDIT Contributor Roles:
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.