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Practical Real-Time with Look-Ahead Scheduling

Authors :
Härtig, Hermann
Fohler, Gerhard
Technische Universität Dresden
Roitzsch, Michael
Härtig, Hermann
Fohler, Gerhard
Technische Universität Dresden
Roitzsch, Michael
Publication Year :
2013

Abstract

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

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1135776853
Document Type :
Electronic Resource