scholarly journals The Earliest Deadline First Scheduling with Active Buffer Management for Real-Time Traffic in the Internet

2001 ◽  
pp. 45-54
Author(s):  
Xiaojun Hei ◽  
Danny H. K. Tsang
Keyword(s):  
Real Time ◽  
Buffer Management ◽  
The Internet ◽  
Earliest Deadline First ◽  
Real Time Traffic ◽  
Earliest Deadline

The Global Limited Preemptive Earliest Deadline First Feasibility of Sporadic Real-Time Tasks

2014 ◽  
Author(s):  
Abhilash Thekkilakattil ◽  
Sanjoy Baruah ◽  
Radu Dobrin ◽  
Sasikumar Punnekkat
Keyword(s):  
Real Time ◽  
Earliest Deadline First ◽  
Earliest Deadline

ACO Based Dynamic Scheduling Algorithm for Real-Time Multiprocessor Systems

2013 ◽  
pp. 85-96
Author(s):  
Apurva Shah ◽  
Ketan Kotecha
Keyword(s):  
Real Time ◽  
Computational Models ◽  
Dynamic Scheduling ◽  
Scheduling Algorithm ◽  
Earliest Deadline First ◽  
Multiprocessor Systems ◽  
Individual Agent ◽  
Collective Foraging ◽  
Time Systems ◽  
Earliest Deadline

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.

Buffer Management in Cellular IP Networks using Evolutionary Algorithms

2010 ◽  
Vol 1 (4) ◽  
pp. 1-22 ◽  
Author(s):  
Mohammad Anbar ◽  
Deo P. Vidyarthi
Keyword(s):  
Evolutionary Algorithms ◽  
Real Time ◽  
Optimization Problems ◽  
Buffer Management ◽  
Complex Problem ◽  
Base Station ◽  
Base Stations ◽  
Real Time Traffic ◽  
Ip Network ◽  
Cellular Ip

Real-time traffic in Cellular IP network is considered to be important and therefore given priority over non-real-time. Buffer is an important but scarce resource and to optimize Quality of Service by managing buffers of the network is an important and complex problem. Evolutionary Algorithms are quite useful in solving such complex optimization problems, and in this regard, a two-tier model for buffer, Gateway and Base Station, management in Cellular IP network has been propsed. The first tier applies a prioritization algorithm for prioritizing real-time packets in the buffer of the gateway with a specified threshold. Packets which couldn’t be served, after the threshold, is given to the nearest cells of the network to be dealt with in the second tier, while Evolutionary Algorithm (EA) based procedures are applied in order to optimally store these packets in the buffer of the base stations. Experiments have been conducted to observe the performance of the proposed models and a comparative study of the models, GA based and PSO based, has been carried out to depict the advantage and disadvantage of the proposed models.

scholarly journals Thermal Analysis of Fair Scheduling in Real-time Embedded Systems

2018 ◽  
Vol 7 (1) ◽  
pp. 48
Author(s):  
Tayyaba Bokhari ◽  
Sajjad Haider Shami ◽  
Farhan Haseeb
Keyword(s):  
Real Time ◽  
Thermal Management ◽  
System Reliability ◽  
Operating Temperature ◽  
Multiprocessor Scheduling ◽  
Earliest Deadline First ◽  
Fair Scheduling ◽  
The Past ◽  
Reliability Performance ◽  
Earliest Deadline

Over the past few decades, increased demand of highly sophisticated real-time applications with complex functionalities has directly led to exponentially increased power consumption and significantly elevated system temperatures. These elevated temperature and thermal variations present formidable challenges towards system reliability, performance, cooling cost and leakages. This article explores the thermal management strength of two fairness based algorithms, namely Proportional Fair (PFair) and Deadline Partitioning Fair (DP-Fair). In related literature, the introduction of fairness is often considered as a tool to achieve optimality in multiprocessor scheduling algorithms. This work shows that these algorithms bring about better thermal profile when compared with the commonly used Earliest Deadline First (EDF) algorithm in similar conditions both in uniprocessor and multiprocessor environments. A simulation is conducted for periodic task set model. The obtained results are encouraging and show that use of fairness based algorithms reduces the operating temperature, peak temperature, and thermal variations.

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

2019 ◽  
Vol 118 (4) ◽  
pp. 160
Author(s):  
G. Madhumita ◽  
G. Rajini ◽  
B. Subisha
Keyword(s):  
Energy Consumption ◽  
Energy Harvesting ◽  
Real Time ◽  
Scheduling Algorithm ◽  
Earliest Deadline First ◽  
Real Time Systems ◽  
Tasks Scheduling ◽  
Time Systems ◽  
Earliest Deadline ◽  
Reducing Energy

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.  

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