Scheduling and energy savings for small scale embedded FreeRTOS-based real-time systems

被引:2
作者
Oliveira, Gesse [1 ]
Lima, George [1 ]
机构
[1] Univ Fed Bahia, Inst Comp, Salvador, BA, Brazil
关键词
FreeRTOS; Real-time systems; Embedded systems; Microcontroller; EDF; Energy savings; ALGORITHMS;
D O I
10.1007/s10617-023-09267-7
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Evaluating the effectiveness of system scheduling and energy savings in embedded real-time systems with low-computing resources is the problem addressed in this paper. In such systems, the characteristics of the implemented scheduling policy play a relevant role in both schedulability and energy consumption. Ideally, the scheduling policy should provide higher schedulability bounds and low runtime overheads, allowing for better usage of available slack in the schedule for energy saving purposes. Due its low overhead and simple implementation, the usual scheduling policy employed in real-time embedded systems is based on fixed priority scheduling (FPS). Under this scheme, as the priority of all system tasks are assigned at design time, a simple priority vector suffices to indicate the current ready task to run. System schedulability, however, is usually lower than that provided by dynamic priority scheduling (DPS) according to which task priorities are assigned at runtime. Managing dynamic priority queues incurs higher overheads, though. Deciding whether DPS is a viable choice for such embedded systems requires careful evaluation. We evaluate two implementations of Earliest Deadline First (EDF), a classical DPS policy, implemented in FreeRTOS running on an ARM-M4 architecture. EDF is compared against an optimal FPS, namely Rate-Monotonic (RM). Further, two mechanisms for energy savings are described. They differ by the manner they compute the slack available in an EDF schedule, statically (SS-EDF) or dynamically (DS-EDF). These two approaches are experimentally evaluated. Results indicate that EDF can be effectively used for energy savings.
引用
收藏
页码:3 / 29
页数:27
相关论文
共 50 条
  • [41] Real-time scheduling in video systems
    deKock, EA
    Aarts, EHL
    Essink, G
    PROCEEDINGS OF THE JOINT WORKSHOP ON PARALLEL AND DISTRIBUTED REAL-TIME SYSTEMS: FIFTH INTERNATIONAL WORKSHOP ON PARALLEL AND DISTRIBUTED REAL-TIME SYSTEMS (WPDRTS) AND THE THIRD WORKSHOP ON OBJECT-ORIENTED REAL-TIME SYSTEMS (OORTS), 1997, : 309 - 318
  • [42] Scheduling for overload in real-time systems
    Baruah, SK
    Haritsa, JR
    IEEE TRANSACTIONS ON COMPUTERS, 1997, 46 (09) : 1034 - 1039
  • [43] Dynamic memory management for embedded real-time systems
    Crespo, A.
    Ripoll, I.
    Masmano, M.
    FROM MODEL-DRIVEN DESIGN TO RESOURCE MANAGEMENT FOR DISTRIBUTED EMBEDDED SYSTEMS, 2006, 225 : 195 - +
  • [44] Modeling of real-time embedded systems using SDL
    Babau, JP
    Alkhodre, A
    Schwarz, JJ
    SYSTEM ON CHIP DESIGN LANGUAGES: EXTENDED PAPERS: BEST OF FDL'01 AND HDLCON'01, 2002, : 257 - 265
  • [45] Power Optimization of Embedded Real-Time Systems and their Adaptability
    Baums, A.
    Zaznova, N.
    AUTOMATIC CONTROL AND COMPUTER SCIENCES, 2008, 42 (03) : 153 - 162
  • [46] Performance estimation for real-time distributed embedded systems
    Yen, TY
    Wolf, W
    IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 1998, 9 (11) : 1125 - 1136
  • [47] Procrastination scheduling in fixed priority real-time systems
    Jejurikar, R
    Gupta, R
    ACM SIGPLAN NOTICES, 2004, 39 (07) : 57 - 65
  • [48] NSGA-II Based Energy Efficient Scheduling in Real-Time Embedded Systems for Tasks with Deadlines and Execution Times as Type-2 Fuzzy Numbers
    Nath, Rahul
    Shukla, Amit K.
    Muhuri, Pranab K.
    Lohani, Q. M. Danish
    2013 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ - IEEE 2013), 2013,
  • [49] Minimax Method in Optimizing Energy Consumption in Real-Time Embedded Systems
    Baums, A.
    AUTOMATIC CONTROL AND COMPUTER SCIENCES, 2009, 43 (02) : 57 - 62
  • [50] Millisecond-Scale Real-Time Scheduling of Buses: A Controller-Based Approach
    Wang, Feiyang
    Zuo, Xingquan
    Wu, Binglin
    Zhou, Mengchu
    Wan, Xing
    Liu, Yahong
    Zhao, Xinchao
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2024, 25 (07) : 7893 - 7906