Artificial Life Techniques for Load Balancing in Computational Grids
(2007) In Journal of Computer and System Sciences 73(8). p.1176-1190- Abstract
- Load balancing is a very important and complex problem in computational grids. A computational grid differs from traditional high performance computing systems in the heterogeneity of the computing nodes and communication links, as well as background workloads that may be present in the computing nodes. There is a need to develop algorithms that could capture this complexity yet can be easily implemented and used to solve a wide range of load balancing scenarios. Artificial life techniques have been used to solve a wide range of complex problems in recent times. The power of these techniques stems from their capability in searching large search spaces, which arise in many combinatorial optimization problems, very efficiently. This paper... (More)
- Load balancing is a very important and complex problem in computational grids. A computational grid differs from traditional high performance computing systems in the heterogeneity of the computing nodes and communication links, as well as background workloads that may be present in the computing nodes. There is a need to develop algorithms that could capture this complexity yet can be easily implemented and used to solve a wide range of load balancing scenarios. Artificial life techniques have been used to solve a wide range of complex problems in recent times. The power of these techniques stems from their capability in searching large search spaces, which arise in many combinatorial optimization problems, very efficiently. This paper studies several well-known artificial life techniques to gauge their suitability for solving grid load balancing problems. Due to their popularity and robustness, a genetic algorithm (GA) and tabu search (TS) are used to solve the grid load balancing problem. The effectiveness of each algorithm is shown for a number of test problems, especially when prediction information is not fully accurate. Performance comparisons with Min–min, Max–min, and Sufferage are also discussed. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3173118
- author
- Subrataa, R. ; Zomaya, A. and Landfeldt, Björn LU
- publishing date
- 2007
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Computer and System Sciences
- volume
- 73
- issue
- 8
- pages
- 1176 - 1190
- publisher
- Elsevier
- external identifiers
-
- scopus:34948846654
- ISSN
- 0022-0000
- DOI
- 10.1016/j.jcss.2007.02.006
- language
- English
- LU publication?
- no
- id
- 94fc11d2-b847-4108-a6e6-45d3b257adee (old id 3173118)
- date added to LUP
- 2016-04-01 15:22:51
- date last changed
- 2022-01-28 05:05:09
@article{94fc11d2-b847-4108-a6e6-45d3b257adee,
abstract = {{Load balancing is a very important and complex problem in computational grids. A computational grid differs from traditional high performance computing systems in the heterogeneity of the computing nodes and communication links, as well as background workloads that may be present in the computing nodes. There is a need to develop algorithms that could capture this complexity yet can be easily implemented and used to solve a wide range of load balancing scenarios. Artificial life techniques have been used to solve a wide range of complex problems in recent times. The power of these techniques stems from their capability in searching large search spaces, which arise in many combinatorial optimization problems, very efficiently. This paper studies several well-known artificial life techniques to gauge their suitability for solving grid load balancing problems. Due to their popularity and robustness, a genetic algorithm (GA) and tabu search (TS) are used to solve the grid load balancing problem. The effectiveness of each algorithm is shown for a number of test problems, especially when prediction information is not fully accurate. Performance comparisons with Min–min, Max–min, and Sufferage are also discussed.}},
author = {{Subrataa, R. and Zomaya, A. and Landfeldt, Björn}},
issn = {{0022-0000}},
language = {{eng}},
number = {{8}},
pages = {{1176--1190}},
publisher = {{Elsevier}},
series = {{Journal of Computer and System Sciences}},
title = {{Artificial Life Techniques for Load Balancing in Computational Grids}},
url = {{http://dx.doi.org/10.1016/j.jcss.2007.02.006}},
doi = {{10.1016/j.jcss.2007.02.006}},
volume = {{73}},
year = {{2007}},
}