Scheduling algorithms and operating systems support for real-time systems

Ramamritham, Krithi; Stankovic, John A.

doi:10.1109/5.259426

Cited by 330 publications

(181 citation statements)

References 54 publications

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“…Most techniques explore how to combine IP-blocks such that the system cost (albeit performance, energy or area) is reduced. In this context, the ordering and assignment of the tasks to the processing elements plays an important role in the system's performance (see [47,48] for an overview). However, in recent years, the energy consumption has become an important bottleneck too.…”

Section: Memory Optimisation In Multi-threaded Applicationsmentioning

confidence: 99%

Power aware data and memory management for dynamic applications

Marchal

Perez

Atienza

et al. 2005

IEE Proc., Comput. Digit. Tech.

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In recent years, the semiconductor industry has turned its focus towards heterogeneous multiprocessor platforms. They are an economically viable solution for coping with the growing setup and manufacturing cost of silicon systems. Furthermore, their inherent flexibility perfectly supports the emerging market of interactive, mobile data and content services. The platform's performance and energy depend largely on how well the data-dominated services are mapped on the memory subsystem. A crucial aspect thereby is how efficient data is transferred between the different memory layers. Several compilation techniques have been developed to optimally use the available bandwidth. Unfortunately, they do not take the interaction between multiple threads into account and do not deal with the dynamic behaviour of these novel applications. The main limitations of current techniques are outlined and an approach for dealing with them is introduced. Design challenges of media-rich servicesBusiness analysts forecast a 250 billion dollar market for media-rich, mobile wireless terminals [1]. These systems require an enormous computational performance: 40 gigaoperations per second (GOPS). Even though current PCs could provide sufficient performance, they are too powerhungry (10 -100 W). Mobile devices should consume at least two or three orders of magnitude less [2]. Furthermore, they should be cheap to successfully penetrate the consumer market. Consequently, and in spite of the design issues, the engineering and manufacturing costs need to be reduced. Industry strongly believes that platforms are a potential way to meet the above challenges. Era of platform-based designA platform is a fixed microarchitecture together with a programming environment that minimises mask-making costs and is flexible enough to work for a set of applications [3]. The production volumes can then remain high over an extended chip lifetime.To cope with the energy constraints, platforms usually consist of multiple processors. Since power is cubic to the processing frequency, parallelism is an effective way to reduce it. Therefore, on most platforms two or more processors are integrated. Besides parallelism, heterogeneity is an alternative way to decrease the energy cost. For instance, the TI OMAP platform combines a RISC processor with a digital signal processor (DSP). The RISC is more energy-efficient for the input=output processing and control-dominated applications. The DSP, however, provides the computational performance for audio and video processing, while keeping the energy cost bounded. Indeed, taking a look to the current market offers (e.g. ST Nomadik

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Section: Memory Optimisation In Multi-threaded Applicationsmentioning

confidence: 99%

Power aware data and memory management for dynamic applications

Marchal

Perez

Atienza

et al. 2005

IEE Proc., Comput. Digit. Tech.

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“…Scheduling is the strategy by which the system decides which task should be executed at any given time. Generally, it is used for load balance and system resources to be served effectively and with desired quality [4]. Scheduling algorithms are classified as preemptive and non preemptive.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Multi Threshold Priority Packet Scheduling Algorithms

Dağ

Uzungenc

2016

MATEC Web Conf.

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Abstract.Packet scheduling algorithms are developed in order to use shared transmission resources efficiently. Various application packets such as real and non-real time packets might have different QoS requirements and traditional scheduling algorithms might be insufficient to respond to the applications needs. In this paper, two packet scheduling algorithms are proposed to overcome this problem: Dynamic multi threshold priority packet scheduling (DMTPS) and dynamic multi threshold priority with urgency packet scheduling (DMTPUS). The proposed algorithms aim to provide a better QoS level with a decrease in delay time and loss ratio for the low priority packets while still maintaining acceptable fairness towards high priority packets. To evaluate the performance of DMTPS and DMTPUS algorithms, they are compared with the commonly used scheduling algorithms such as first come first served (FCFS) and fixed priority. Simulation results illustrate that the dynamic multi threshold priority packet scheduling algorithms can provide a better QoS for low priority packets without decreasing the QoS levels of high priority packets.

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“…[14] and references therein), call centers (see e.g. [8] and references) and telecommunications (see [4]).…”

Section: Introductionmentioning

confidence: 99%

Analysis of a discrete-time preemptive resume priority buffer

Walraevens

Steyaert

Bruneel

2008

European Journal of Operational Research

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In this paper, we analyze a discrete-time preemptive resume priority queue. We consider two classes of customers which have to be served, where customers of one class have preemptive resume priority over customers of the other. Both classes contain customers with generally distributed service times. We show that the use of probability generating functions is beneficial for analyzing the system contents and customer delays of both classes. It is shown (theoretically as well as by some practical procedures) how moments and approximate tail probabilities of system contents and customer delays are calculated.The influence of the priority scheduling discipline and the service time distributions on the performance measures is shown by some numerical examples.

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Scheduling algorithms and operating systems support for real-time systems

Cited by 330 publications

References 54 publications

Power aware data and memory management for dynamic applications

Power aware data and memory management for dynamic applications

Dynamic Multi Threshold Priority Packet Scheduling Algorithms

Analysis of a discrete-time preemptive resume priority buffer

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