AIDCFeb 24, 2021

A CP-Net based Qualitative Composition Approach for an IaaS Provider

arXiv:2102.12221v112 citations
Originality Synthesis-oriented
AI Analysis

This work addresses a domain-specific problem for IaaS providers in cloud computing, but it appears incremental as it builds on existing CP-Net methods.

The paper tackles the problem of selecting an optimal set of consumers for an IaaS provider using qualitative preferences, proposing a CP-Net based composition approach with greedy and heuristic methods that reduce search space, and experimental results demonstrate feasibility.

We propose a novel CP-Net based composition approach to qualitatively select an optimal set of consumers for an IaaS provider. The IaaS provider's and consumers' qualitative preferences are captured using CP-Nets. We propose a CP-Net composability model using the semantic congruence property of a qualitative composition. A greedy-based and a heuristic-based consumer selection approaches are proposed that effectively reduce the search space of candidate consumers in the composition. Experimental results prove the feasibility of the proposed composition approach.

Foundations

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