For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Adaptive Fair Sharing Control in Real-Time Systems Using Nonlinear Elastic Task Models
Toshimitsu USHIO Haruo KOHTAKI Masakazu ADACHI Fumiko HARADA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2007/06/01
Online ISSN: 1745-1337
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Nonlinear Problems
real-time systems, elastic task model, resource allocation, fair sharing control, QoS,
Full Text: PDF>>
In real-time systems, deadline misses of the tasks cause a degradation in the quality of their results. To improve the quality, we have to allocate CPU utilization for each task adaptively. Recently, Buttazzo et al. address a feedback scheduling algorithm, which dynamically adjusts task periods based on the current workloads by applying a linear elastic task model. In their model, the utilization allocated to each task is treated as the length of a linear spring and its flexibility is described by a constant elastic coefficient. In this paper, we first consider a nonlinear elastic task model, where the elastic coefficient depends on the utilization allocated to the task. We propose a simple iterative method for calculating the desired allocated resource and derive a sufficient condition for the convergence of the method. Next, we apply the nonlinear elastic model to an adaptive fair sharing controller. Finally, we show the effectiveness of the proposed method by computer simulation.