scholarly journals Energy harvesting earliest deadline first scheduling algorithm for increasing lifetime of real time systems

Author(s):  
Arvind Kumar ◽  
Bashir Alam

<span lang="EN-US">In this paper, a new approach for energy minimization in energy harvesting real time systems has been investigated. Lifetime of a real time systems is depend upon its battery life.  Energy is a parameter by which the lifetime of system can be enhanced.  To work continuously and successively, energy harvesting is used as a regular source of energy. EDF (Earliest Deadline First) is a traditional real time tasks scheduling algorithm and DVS (Dynamic Voltage Scaling) is used for reducing energy consumption. In this paper, we propose an Energy Harvesting Earliest Deadline First (EH-EDF) scheduling algorithm for increasing lifetime of real time systems using DVS for reducing energy consumption and EDF for tasks scheduling with energy harvesting as regular energy supply. Our experimental results show that the proposed approach perform better to reduce energy consumption and increases the system lifetime as compared with existing approaches.  </span>

2019 ◽  
Vol 118 (4) ◽  
pp. 160
Author(s):  
G. Madhumita ◽  
G. Rajini ◽  
B. Subisha

In this paper, a new approach for energy minimization in energy harvesting real time systems has been investigated. Lifetime of a real time systems is depend upon its battery life.  Energy is a parameter by which the lifetime of system can be enhanced.  To work continuously and successively, energy harvesting is used as a regular source of energy. EDF (Earliest Deadline First) is a traditional real time tasks scheduling algorithm and DVS (Dynamic Voltage Scaling) is used for reducing energy consumption. In this paper, we propose an Energy Harvesting Earliest Deadline First (EH-EDF) scheduling algorithm for increasing lifetime of real time systems using DVS for reducing energy consumption and EDF for tasks scheduling with energy harvesting as regular energy supply. Our experimental results show that the proposed approach perform better to reduce energy consumption and increases the system lifetime as compared with existing approaches.  


Author(s):  
Apurva Shah ◽  
Ketan Kotecha

The Ant Colony Optimization (ACO) algorithms are computational models inspired by the collective foraging behavior of ants. The ACO algorithms provide inherent parallelism, which is very useful in multiprocessor environments. They provide balance between exploration and exploitation along with robustness and simplicity of individual agent. In this paper, ACO based dynamic scheduling algorithm for homogeneous multiprocessor real-time systems is proposed. The results obtained during simulation are measured in terms of Success Ratio (SR) and Effective CPU Utilization (ECU) and compared with the results of Earliest Deadline First (EDF) algorithm in the same environment. It has been observed that the proposed algorithm is very efficient in underloaded conditions and it performs very well during overloaded conditions also. Moreover, the proposed algorithm can schedule some typical instances successfully which are not possible to schedule using EDF algorithm.


2014 ◽  
Vol 50 (5-6) ◽  
pp. 592-619 ◽  
Author(s):  
Qiushi Han ◽  
Linwei Niu ◽  
Gang Quan ◽  
Shaolei Ren ◽  
Shangping Ren

2011 ◽  
Vol 3 (3) ◽  
pp. 20-30 ◽  
Author(s):  
Apurva Shah ◽  
Ketan Kotecha

The Ant Colony Optimization (ACO) algorithms are computational models inspired by the collective foraging behavior of ants. The ACO algorithms provide inherent parallelism, which is very useful in multiprocessor environments. They provide balance between exploration and exploitation along with robustness and simplicity of individual agent. In this paper, ACO based dynamic scheduling algorithm for homogeneous multiprocessor real-time systems is proposed. The results obtained during simulation are measured in terms of Success Ratio (SR) and Effective CPU Utilization (ECU) and compared with the results of Earliest Deadline First (EDF) algorithm in the same environment. It has been observed that the proposed algorithm is very efficient in underloaded conditions and it performs very well during overloaded conditions also. Moreover, the proposed algorithm can schedule some typical instances successfully which are not possible to schedule using EDF algorithm.


2014 ◽  
Vol 644-650 ◽  
pp. 2253-2257
Author(s):  
Jian Lang Wu ◽  
Jing Kai Shi ◽  
Yi Bin Wang

In real-time systems, periodic tasks and aperiodic tasks exist simultaneously. In a uniprocessor system, mainly there are Deferrable Server algorithm (DS) [1], Slack Stealing algorithm (SSA) [2] and their extended version for software/hardware hybrid real-time task scheduling. DS algorithm sets a high priority periodic task server to provide services for aperiodic tasks, while SSA algorithm computes tasks unoccupied time offline, and then schedule aperiodic tasks during the unoccupied period. The two algorithms are both proposed for soft real-time tasks, reducing the response time of the real-time tasks, but cannot guarantee that these aperiodic real-time tasks received can meet deadlines. In this paper, through combination of DS algorithm and EDF (Earliest Deadline First) algorithm [6], a new algorithm called DS-EDF is introduced, which can scheduling hard real-time aperiodic tasks on the DS server. This algorithm is not only suitable for uniprocessor systems, but also has the ability to extend to multiprocessor systems.


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