Bio-Inspired Techniques for Resources State Prediction in Large Scale Distributed Systems

Andreea Visan, Mihai Istin, Florin Pop and Valentin Cristea
Additional contact information
Andreea Visan: University Politehnica of Bucharest, Romania
Mihai Istin: University Politehnica of Bucharest, Romania
Florin Pop: University Politehnica of Bucharest, Romania
Valentin Cristea: University Politehnica of Bucharest, Romania

International Journal of Distributed Systems and Technologies (IJDST), 2011, vol. 2, issue 3, 1-18

Abstract: The state prediction of resources in large scale distributed systems represents an important aspect for resources allocations, systems evaluation, and autonomic control. The paper presents advanced techniques for resources state prediction in Large Scale Distributed Systems, which include techniques based on bio-inspired algorithms like neural network improved with genetic algorithms. The approach adopted in this paper consists of a new fitness function, having prediction error minimization as the main scope. The proposed prediction techniques are based on monitoring data, aggregated in a history database. The experimental scenarios consider the ALICE experiment, active at the CERN institute. Compared with classical predicted algorithms based on average or random methods, the authors obtain an improved prediction error of 73%. This improvement is important for functionalities and performance of resource management systems in large scale distributed systems in the case of remote control ore advance reservation and allocation.

Date: 2011
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 4018/jdst.2011070101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jdst00:v:2:y:2011:i:3:p:1-18

Access Statistics for this article

International Journal of Distributed Systems and Technologies (IJDST) is currently edited by Nik Bessis

More articles in International Journal of Distributed Systems and Technologies (IJDST) from IGI Global
Bibliographic data for series maintained by Journal Editor ().