کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
461213 1364717 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Low power fixed priority scheduling sporadic task with shared resources in hard real time systems
ترجمه فارسی عنوان
کار پراکنده برنامه ریزی اولویت ثابت با قدرت پایین با منابع اشتراکی در سیستم های زمان واقعی سخت
کلمات کلیدی
کار پراکنده؛ به اشتراک گذاری منابع؛ مدیریت انرژی؛ طرح اولویت ثابت
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی


• We consider a scheduling problem of the sporadic task that shares resources.
• We present a new scheduling policy based on a fixed-priority scheduling.
• The energy management problem is considered in a real time system.
• Two techniques are presented to solve a sporadic task shared resources problem.

Dynamic voltage scaling (DVS) and dynamic power management (DPM) are two effective techniques in a real time system. In this paper, we address the problem of the canonical sporadic task scheduling based on a fixed-priority scheduling scheme and take a generalized power model into account. The sporadic tasks share a set serially reusable, single-unit resources. First, we present a rate monotonic with dual priority scheduling policy, called RM/DPP, to solve the sporadic tasks shared resources scheduling problem and discuss the feasibility of the RM/DPP algorithm. Second, a static fixed-priority sporadic tasks scheduling algorithm with shared resources, called SFPSASR, has been put forward, which considers the off-chip workload and assumes that each task executes with its worst case execution time. Third, for energy efficiency, a dynamic fixed-priority sporadic tasks scheduling algorithm with shared resources, called DFPSASR, has been put forward, which considers the speed transition overhead and combines the DVS and the DPM technology. The experimental results show that the proposed SFPSASR algorithm can reduce the energy consumption by 42.14%∼51.73% over the RM/DPP algorithm and the DFPSASR algorithm can reduce the energy consumption by 79.37%∼82.94% over the SFPSASR algorithm.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Microprocessors and Microsystems - Volume 45, Part A, August 2016, Pages 164–175
نویسندگان
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