Safe-ERfair – A priori Overload Handling in Fair Scheduled Embedded Systems

This paper presents Safe-ERfair, an efficient resource allocation strategy for handling overloads in real-time ERfair scheduled embedded systems. Each task has an assigned criticality value and consists of a mandatory part and an optional part. The scheduler employs an a priori look-ahead mechanism at the time of arrival of a new job to examine the occurrence of possible overloads during the execution period of the job and decide whether to accept/reject the new job and whether to execute the optional part in case the job is accepted. Execution time revisions are not allowed once the task is scheduled and this criterion is important in a large class of systems where such changes are not permitted. The objective is to maximize processor utilization by maximizing the reward for executing optional parts while not sacrificing the ERfairness timing constraints of the system and ensuring that all tasks are able to execute atleast their mandatory parts.

[1]  Giuseppe Lipari,et al.  Elastic Scheduling for Flexible Workload Management , 2002, IEEE Trans. Computers.

[2]  Luca Abeni,et al.  Adaptive rate control through elastic scheduling , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[3]  Steve Goddard,et al.  A theory of rate-based execution , 1999, Proceedings 20th IEEE Real-Time Systems Symposium (Cat. No.99CB37054).

[4]  Jörgen Hansson,et al.  Imprecise task scheduling and overload management using OR-ULD , 2000, Proceedings Seventh International Conference on Real-Time Computing Systems and Applications.

[5]  Sanjoy K. Baruah,et al.  Proportionate progress: A notion of fairness in resource allocation , 1993, Algorithmica.

[6]  Maryline Chetto,et al.  Dynamic scheduling of periodic skippable tasks in an overloaded real-time system , 2008, 2008 IEEE/ACS International Conference on Computer Systems and Applications.

[7]  Abhay Parekh,et al.  A generalized processor sharing approach to flow control in integrated services networks-the single node case , 1992, [Proceedings] IEEE INFOCOM '92: The Conference on Computer Communications.

[8]  H. Aydin,et al.  An Incremental Server for Scheduling Overloaded Real-Time Systems , 2003, IEEE Trans. Computers.

[9]  Sanjoy K. Baruah,et al.  The case for fair multiprocessor scheduling , 2003, Proceedings International Parallel and Distributed Processing Symposium.

[10]  Abhay Parekh,et al.  A generalized processor sharing approach to flow control in integrated services networks: the single-node case , 1993, TNET.

[11]  Gihyun Jung,et al.  Real-Time Scheduling Algorithm for Minimizing Maximum Weighted Error with O(N log N + cN) Complexity , 1998, Inf. Process. Lett..

[12]  James H. Anderson,et al.  Early-release fair scheduling , 2000, Proceedings 12th Euromicro Conference on Real-Time Systems. Euromicro RTS 2000.

[13]  Gerhard Fohler,et al.  Value Based Overload Handling of Aperiodic Tasks in Offline Scheduled Real-Time Systems , 2001 .

[14]  Steve Goddard,et al.  Rate-Based Resource Allocation Models for Embedded Systems , 2001, EMSOFT.

[15]  Sanjoy K. Baruah,et al.  Fast scheduling of periodic tasks on multiple resources , 1995, Proceedings of 9th International Parallel Processing Symposium.

[16]  M. C. Woodward,et al.  Avoiding deadline decay under transient overloads , 1995, Proceedings of Third Workshop on Parallel and Distributed Real-Time Systems.

[17]  Sanjoy K. Baruah,et al.  Proportionate progress: a notion of fairness in resource allocation , 1993, STOC '93.

[18]  James H. Anderson,et al.  Mixed Pfair/ERfair scheduling of asynchronous periodic tasks , 2004, J. Comput. Syst. Sci..

[19]  Jane W.-S. Liu,et al.  i . ' il ' . Imprecise Results : Utilizing Partial Computations in Real-Time Systems , 2004 .