Energy-Efficient Scheduling for Hybrid Tasks in Control Devices for the Internet of Things

Sensors

Zhigang Gao¹  Yifan Wu¹  Guojun Dai¹ 

[1] College of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, China; E-Mails:

关键词: IoT;    control devices;    hybrid tasks;    DVS;    slowdown factors;    slack time;   

DOI  :  10.3390/s120811334

来源: mdpi

【 摘 要 】

In control devices for the Internet of Things (IoT), energy is one of the critical restriction factors. Dynamic voltage scaling (DVS) has been proved to be an effective method for reducing the energy consumption of processors. This paper proposes an energy-efficient scheduling algorithm for IoT control devices with hard real-time control tasks (HRCTs) and soft real-time tasks (SRTs). The main contribution of this paper includes two parts. First, it builds the Hybrid tasks with multi-subtasks of different function Weight (HoW) task model for IoT control devices. HoW describes the structure of HRCTs and SRTs, and their properties, e.g., deadlines, execution time, preemption properties, and energy-saving goals, etc. Second, it presents the Hybrid Tasks' Dynamic Voltage Scaling (HTDVS) algorithm. HTDVS first sets the slowdown factors of subtasks while meeting the different real-time requirements of HRCTs and SRTs, and then dynamically reclaims, reserves, and reuses the slack time of the subtasks to meet their ideal energy-saving goals. Experimental results show HTDVS can reduce energy consumption about 10%–80% while meeting the real-time requirements of HRCTs, HRCTs help to reduce the deadline miss ratio (DMR) of systems, and HTDVS has comparable performance with the greedy algorithm and is more favorable to keep the subtasks' ideal speeds.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.