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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

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1

Practical Real-Time with Look-Ahead Scheduling / Praktikable Echtzeit durch vorausschauende Einplanung

Roitzsch, Michael 21 October 2013 (has links) (PDF)
In my dissertation, I present ATLAS — the Auto-Training Look-Ahead Scheduler. ATLAS improves service to applications with regard to two non-functional properties: timeliness and overload detection. Timeliness is an important requirement to ensure user interface responsiveness and the smoothness of multimedia operations. Overload can occur when applications ask for more computation time than the machine can offer. Interactive systems have to handle overload situations dynamically at runtime. ATLAS provides timely service to applications, accessible through an easy-to-use interface. Deadlines specify timing requirements, workload metrics describe jobs. ATLAS employs machine learning to predict job execution times. Deadline misses are detected before they occur, so applications can react early.
Betriebssystem
Einplanung
Echtzeit
weiche Echtzeit
Voraussicht
vorausschauend
Warteschlangen
asynchrone Lambdas
Deadlines
Fristen
Operating System
Scheduling
Real-Time
Soft Real-Time
Look-Ahead
Work Queues
Asynchronous Lambdas
Deadlines
ddc:004
rvk:ST 234
Betriebssystem
Scheduling
2

Practical Real-Time with Look-Ahead Scheduling

Roitzsch, Michael 19 September 2013 (has links)
In my dissertation, I present ATLAS — the Auto-Training Look-Ahead Scheduler. ATLAS improves service to applications with regard to two non-functional properties: timeliness and overload detection. Timeliness is an important requirement to ensure user interface responsiveness and the smoothness of multimedia operations. Overload can occur when applications ask for more computation time than the machine can offer. Interactive systems have to handle overload situations dynamically at runtime. ATLAS provides timely service to applications, accessible through an easy-to-use interface. Deadlines specify timing requirements, workload metrics describe jobs. ATLAS employs machine learning to predict job execution times. Deadline misses are detected before they occur, so applications can react early.:1 Introduction 2 Anatomy of a Desktop Application 3 Real Simple Real-Time 4 Execution Time Prediction 5 System Scheduler 6 Timely Service 7 The Road Ahead Bibliography Index
info:eu-repo/classification/ddc/004
ddc:004
Betriebssystem; Scheduling

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