is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor

is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor

importance, is largely overlooked/under-developed. To provide real-time guarantees, DVS must consider deadlines and periodicity of real-time tasks, requiring integration with the real-time scheduler. In this paper, we present a class of novel algorithms called real-time DVS (RT-DVS) that modify the OS

The paper presents exact schedulability analyses for real-time systems scheduled at run-time with a static priority pre-emptive dispatcher. The tasks to be scheduled are allowed to experience internal blocking (from other tasks with which they share resources) and (with certain restrictions

and minimum interarrival times, whereas multimedia and soft tasks are served based on mean parameters. The paper describes a server-based mechanism for scheduling soft and multimedia tasks without jeopardizing the a pri-ori guarantee of hard real-time activities. The performance of the proposed method

-fidelity computer graphics objects using imperfectly-measured data from the real world. Our approach contains three novel features: an implicit integration method to achieve efficiency, stability, and large time-steps; a scale-dependent Laplacian operator to improve the diffusion process; and finally, a robust

This report extends the current analysis associated with static priority pre-emptive based scheduling to address the wider problem of analysing schedulability of a distributed hard real-time system; in particular it derives analysis for a distributed system where tasks with arbitrary deadlines

Many scheduling algorithms have been studied to guarantee the time constraints of real-time processes. Scheduling decision of these algorithms is usually based on parameters which are assumed to be crisp. However, in many circumstances the values of these parameters are vague. The vagueness

This paper presents a feedback control real-time scheduling (FCS) framework for adaptive real-time systems. An advantage of the FCS framework is its use of feedback control theory (rather than ad hoc solutions) as a scientific underpinning. We apply a control theory based methodology

this paper is organized as follows. Section II describes the Bayesian decision method and a scheduler that implements it to perform its location policy. Section III introduces fuzzy set theory and a multiobjective fuzzy decision method and shows how this can be used to develop utility functions