| 1. |
- Kiani, Vahdaneh, et al.
(författare)
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Real-time Scheduling for CPU and Hard Disk Requirements-Based Periodic Task with Aim of Minimising Energy Consumption
- 2015
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Ingår i: International Journal of Information Technology and Computer Science. - : Modern education and computer science press. - 2074-9007 .- 2074-9015. ; 7:10, s. 54-60
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, with an increasing number ofrequests, energy, power and temperature have beenimportant keys in embedded systems, which decrease thelifetime of both CPUs and hard disks. The energyconsumption is an important issue in computer systems,particularly real-time embedded systems. The frequencyand the Revolutions Per Minute are major factors in thereduction of energy consumption in both processors andhard disk drives. Therefore, the main goal of this paper isto present a scheduling mechanism for a real timeperiodic task that can save more energy. This mechanismis based on increasing, as much as possible, the executiontime of the CPU and/or the Read/Write time of the harddisk without passing the task deadline. This will be doneby dynamically changing the CPU frequency and/or theRPM of hard disk. Our experimental results demonstratethat the proposed algorithm manages to lower energyconsumption by an average of 25% and to reduce thenumber of missed tasks by 80%.
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| 2. |
- Mohseni, Zeynab, et al.
(författare)
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A Task Scheduling Model for Multi-CPU and Multi-Hard Disk Drive in Soft Real-time Systems
- 2019
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Ingår i: International Journal of Information Technology and Computer Science. - : Modern education and computer science press. - 2074-9007 .- 2074-9015. ; 11:1
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, by increasing CPU and I/O devices demands, running multiple tasks simultaneously becomes a crucial issue. This paper presents a new task scheduling algorithm for multi-CPU and multi-Hard Disk Drive (HDD) in soft Real-Time (RT) systems, which reduces the number of missed tasks. The aim of this paper is to execute more parallel tasks by considering an efficient trade-off between energy consumption and total execution time. For study purposes, we analyzed the proposed scheduling algorithm, named HCS (Hard disk drive and CPU Scheduling) in terms of the task set utilization, the total execution time, the average waiting time and the number of missed tasks from their deadlines. The results show that HCS algorithm improves the above mentioned criteria compared to the HCS_UE (Hard disk drive and CPU Scheduling _Unchanged Execution time) algorithm.
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