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Reseach Article

Energy Efficient Task Scheduling and Data Allocation Strategy in Heterogeneous Environment with Real Time Constraints

by Rakesh D. More
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 11
Year of Publication: 2014
Authors: Rakesh D. More
10.5120/17566-8225

Rakesh D. More . Energy Efficient Task Scheduling and Data Allocation Strategy in Heterogeneous Environment with Real Time Constraints. International Journal of Computer Applications. 100, 11 ( August 2014), 1-6. DOI=10.5120/17566-8225

@article{ 10.5120/17566-8225,
author = { Rakesh D. More },
title = { Energy Efficient Task Scheduling and Data Allocation Strategy in Heterogeneous Environment with Real Time Constraints },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 11 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number11/17566-8225/ },
doi = { 10.5120/17566-8225 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:29:40.095637+05:30
%A Rakesh D. More
%T Energy Efficient Task Scheduling and Data Allocation Strategy in Heterogeneous Environment with Real Time Constraints
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 11
%P 1-6
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we concentrate on the problem of high Energy consumption in heterogeneous environment regarding data allocation scheme in distributed database and task scheduling policies in real-time system. We will focus on soft real time system application having if any deadline is missed then time penalty is occurred. Here we will combine both shared memory as well as in-memory database concepts in heterogeneous database environment. Basically in our paper we will concentrate on try to perform task within deadline having various type of databases responsible to store data. An important problem is how to assign processors to real-time application tasks, obvious here basically concentrate on real time scheduling strategy. As per studied that algorithm concentrate on EDF algorithm having preemptive nature. When higher priority transaction currently going to allocate processor and execute that transaction but another transaction is most needful to execute primary so using preemptive scheduling policy try to overcome that type of problem. Here global index is maintain into the local cache that is responsible to fast search particular server where that result is available and try to give response within time constraint and the total system energy consumption can be minimized. In this paper concentrate on replicas of databases due to this when any specific system crash then able to restore that database.

References
  1. Yan Wang, Kenli Li, Hao Chen, Ligang He, and Keqin Li, "Energy Aware Data Allocation & Task Scheduling on Heterogeneous Multiprocessor Systems with Time Constraints", IEEE Transactions on Emerging Topics in Computing, VOL. X, NO. Y, MONTH 2014.
  2. http://belhob. wordpress. com/2007/10/page/4/
  3. http://en. wikibooks. org/wiki/Microprocessor_Design/Real-Time_Operating_System
  4. http://www. queryhome. com/15864/what-is-the-major-difference-between-normal-os-and-rtos#. U0-mJKIm2tk
  5. http://rakeshvarimalla. blogspot. in/2008/08/difference-between-rtos-and-os. html
  6. Prof. Kasim M. Al-Aubidy, "Classification of Real Time Systems",Computer Engineering Department, Philadelphia University, Summer semester,2011.
  7. Arezou Mohammadi," Scheduling Algorithms for Real-Time Systems", Queen's University, Kingston, Ontario, Canada, April 2009.
  8. Arezou Mohammadi & Selim G. Akl, "Scheduling Algorithm for Real Time Systems", Technical report No-2005-499, School of Computing, Queen's University, Kingston, Ontario,Canada,July 15,2005.
  9. Arezou Mohammadi & Selim G. Akl, "Number of Processors for Scheduling a Set of Real-Time Tasks: Upper and Lower Bounds", Technical Report Number 2007-535, School of Computing, Queen's University, Kingston, Ontario, Canada K7L 3N6, June 13, 2007.
  10. Jan Lindstrom Solid , "Real Time Database Systems", an IBM Company It ? alahdenkatu 22 B 00210 Helsinki, Finland March 25, 2008.
  11. http://www. ukessays. com/essays/computerscience/embedded-hardware-operating-systems-omputer-science essay. php
  12. Himanshu Poddar, Jagtar Singh, ,G. S. Sekhon," Dynamic Scheduling for Hard Real-Time Multiprocessor Systems ", Proceedings of National Conference on Challenges & Opportunities in Information Technology (COIT-2007) RIMT-IET, Mandi Gobindgarh. March 23,2007.
Index Terms

Computer Science
Information Sciences

Keywords

Distributed System Shared Memory DB In-Memory DB Global Index RTOS RT Scheduling Algorithm.