Dynamic task scheduling using a directed neural network

被引：32

作者：

Tripathy, Binodini ^{[1
]}

Dash, Smita ^{[2
]}

Padhy, Sasmita Kumari ^{[3
]}

机构：

[1] KIIT Univ, Bhubaneswar, Orissa, India

[2] SOA Univ, Bhubaneswar, Odisha, India

[3] Natl Inst Technol, Patna, Bihar, India

来源：

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING | 2015年 / 75卷

关键词：

Task scheduling; Directed search optimization; Neural network; ALGORITHM; SYSTEMS;

D O I：

10.1016/j.jpdc.2014.09.015

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This article is based on the problem of work flow scheduling in grid environment of multi-processors. We, in this paper, introduce three novel approaches for the task scheduling problem using recently proposed Directed Search Optimization (DSO). In the first attempt, task scheduling is framed as an optimization problem and solved by DSO. Next, this paper makes use of DSO as a training algorithm to train (a) a three layer Artificial Neural Network (ANN) and then (b) Radial Basis Function Neural Networks (RBFNN). These'DSO trained networks are used for task Scheduling and interstingly yield better performance than contemporary algorithms as evidenced by simulation results. (C) 2014 Elsevier Inc. All rights reserved.

引用

收藏

页码：101 / 106

页数：6

相关论文

共 23 条

[11] A performance study of multiprocessor task scheduling algorithms [J].

Jin, Shiyuan ;

Schiavone, Guy ;

Turgut, Damla .

JOURNAL OF SUPERCOMPUTING, 2008, 43 (01) :77-97

[12]

Kaur H., 2013, International Journal of Information and Electronics Engineering, V3, P204

[13] Daily combined economic emission scheduling of hydrothermal systems with cascaded reservoirs using self organizing hierarchical particle swarm optimization technique [J].

Mandal, K. K. ;

Chakraborty, N. .

EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (03) :3438-3445

[14] Genetic algorithms for task scheduling problem [J].

Omara, Fatma A. ;

Arafa, Mona M. .

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2010, 70 (01) :13-22

[15] Assignment and scheduling communicating periodic tasks in distributed real-time systems [J].

Peng, DT ;

Shin, KG ;

Abdelzaher, TF .

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 1997, 23 (12) :745-758

[16] Approximation of nonlinear systems with radial basis function neural networks [J].

Schilling, RJ ;

Carroll, JJ ;

Al-Ajlouni, AF .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2001, 12 (01) :1-15

[17] Perspectives on grid computing [J].

Schwiegelshohn, Uwe ;

Badia, Rosa M. ;

Bubak, Marian ;

Danelutto, Marco ;

Dustdar, Schahram ;

Gagliardi, Fabrizio ;

Geiger, Alfred ;

Hluchy, Ladislav ;

Kranzlmueller, Dieter ;

Laure, Erwin ;

Priol, Thierry ;

Reinefeld, Alexander ;

Resch, Michael ;

Reuter, Andreas ;

Rienhoff, Otto ;

Rueter, Thomas ;

Sloot, Peter ;

Talia, Domenico ;

Ullmann, Klaus ;

Yahyapour, Ramin ;

von Voigt, Gabriele .

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2010, 26 (08) :1104-1115

[18] A rotary chaotic PSO algorithm for trustworthy scheduling of a grid workflow [J].

Tao, Qian ;

Chang, Hui-You ;

Yi, Yang ;

Gu, Chun-qin ;

Li, Wen-jie .

COMPUTERS & OPERATIONS RESEARCH, 2011, 38 (05) :824-836

[19] A heuristic-based hybrid genetic-variable neighborhood search algorithm for task scheduling in heterogeneous multiprocessor system [J].

Wen, Yun ;

Xu, Hua ;

Yang, Jiadong .

INFORMATION SCIENCES, 2011, 181 (03) :567-581

[20] Task scheduling using Bayesian optimization algorithm for heterogeneous computing environments [J].

Yang, Jiadong ;

Xu, Hua ;

Pan, Li ;

Jia, Peifa ;

Long, Fei ;

Jie, Ming .

APPLIED SOFT COMPUTING, 2011, 11 (04) :3297-3310