A Multithreading Based Enhanced Process Scheduling Technique for Heterogeneous Distributed Environment
Keywords:
MATLAB, computing units, CPU caches, translation lookaside bufferAbstract
Multithreading is ability of a central processing unit (CPU) or a single core within a multi-core processor to execute multiple processes or threads concurrently, appropriately supported by operating system. This approach differs from multiprocessing, as with multithreading processes & threads have to share resources of a single or multiple cores: computing units, CPU caches, & translation lookaside buffer (TLB). Multiprocessing systems include multiple complete processing units, multithreading aims to increase utilization of a single core by using thread-level as well as instruction-level parallelism. Objective of research is increase efficiency of scheduling dependent task using enhanced multithreading. gang scheduling of parallel implicit-deadline periodic task systems upon identical multiprocessor platforms is considered. In this scheduling problem, parallel tasks use several processors simultaneously. first algorithm is based on linear programming & is first one to be proved optimal for considered gang scheduling problem. Furthermore, it runs in polynomial time for a fixed number m of processors & an efficient implementation is fully detailed. Second algorithm is an approximation algorithm based on a fixed-priority rule that is competitive under resource augmentation analysis in order to compute an optimal schedule pattern. Precisely, its speedup factor is bounded by (2?1/m). Both algorithms are also evaluated through intensive numerical experiments. In our research we have enhanced capability of Gang Scheduling by integration of multi core processor & Cache & make simulation of performance in MATLAB.
References
- Abraham Silberschatz, Peter Baer Galvin & Greg Gagne (2013). Operating System Concepts 9. John Wiley & Sons,Inc. ISBN 978-1-118-06333-0.
- Yeh-Ching Chung and Sanjay Ranka, Applications and Performance Analysis of A Compile-Time Optimization Approach for List Scheduling Algorithms on Distributed Memory Multiprocessors, 1063-953Y92 $3.00 0 1992 IEEE
- Ishfaq 5. Wayne F. Boyer, Gurdeep S. Hurab, Non-evolutionary algorithm for scheduling dependent tasks in distributed heterogeneous computing environments, J. Parallel Distrib. Comput. 65 (2005) 1035 - 1046
- Ahmad and Yu-Kwong Kwok, On Parallelizing the Multiprocessor Scheduling Problem,1998
- Maruf Ahmed , Sharif M. H. Chowdhury and Masud Hasan, List Heuristic Scheduling Algorithms for Distributed Memory Systems with Improved Time Complexity.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRCSEIT

This work is licensed under a Creative Commons Attribution 4.0 International License.