Nature-Inspired Algorithms Applied to an Efficient and Self-adaptive Resources Selection Model for Grid Applications

Botón-Fernández, María; Prieto‐Castrillo, Francisco; Vega‐Rodríguez, Miguel A.

doi:10.1007/978-3-642-33860-1_8

Cited by 3 publications

(1 citation statement)

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“…A cellular Automata (CA) is a mathematical model for a complex system which evolves in discrete steps [9]. It is suitable for modelling cloud scheduling system which can be described as a massive collection of resources that interact locally with each other [4]. In this paper, we represent the cloud scheduling system behaviour as a cellular automaton, specifically as a one-dimension cellular automata network.…”

Section: Introductionmentioning

confidence: 99%

A Cost-Efficient and Reliable Resource Allocation Model Based on Cellular Automaton Entropy for Cloud Project Scheduling

Chen¹,

Wang²,

Helian³

2013

IJACSA

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Abstract-Resource allocation optimization is a typical cloud project scheduling problem: a problem that limits a cloud system's ability to execute and deliver a project as originally planned. The entropy, as a measure of the degree of disorder in a system, is an indicator of a system's tendency to progress out of order and into a chaotic condition, and it can thus serve to measure a cloud system's reliability for project scheduling. In this paper, cellular automaton is used for modeling the complex cloud project scheduling system. Additionally, a method is presented to analysis the reliability of cloud scheduling system by measuring the average resource entropy (ARE). Furthermore, a new cost-efficient and reliable resource allocation (CERRA) model is proposed based on cellular automaton entropy to aid decision maker for planning projects on the cloud. At last, the proposed model is designed using Matlab toolbox and simulated with three basic cloud scheduling algorithm, First Come First Served Algorithm (FCFS), Min-Min Algorithm and Max-Min Algorithm. The simulation results show that the proposed model can lead to achieve a cost-efficient and reliable resource allocation strategy for running projects on the cloud environment.

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Section: Introductionmentioning

confidence: 99%