Comparison of Multi Criteria Decision Making Algorithms for Ranking Cloud Renderfarm Services

TL;DR

This paper compares and ranks three cloud renderfarm services using AHP and SAW multi-criteria decision making algorithms based on five QoS attributes, demonstrating similar rankings across different simulations.

Contribution

It applies and compares AHP and SAW algorithms for ranking cloud renderfarm services based on multiple QoS criteria, providing insights into their performance consistency.

Findings

AHP and SAW algorithms produced similar rankings across all simulations.

The ranking was consistent despite varying attribute weights.

Both methods effectively evaluated cloud renderfarm services.

Abstract

Cloud services that provide a complete environment for the animators to render their files using the resources in the cloud are called Cloud Renderfarm Services. The objective of this work is to rank and compare the performance of these services using two popular Multi Criteria Decision Making (MCDM) Algorithms namely the Analytical Hierarchical Processing (AHP) and SAW (Simple Additive Weighting) methods. The performance of three real time cloud renderfarm services are ranked and compared based on five Quality of Service (QoS) attributes that are important to these services namely the Render Node Cost, File Upload Time, Availability, Elasticity and Service Response Time. The performance of these cloud renderfarm services are ranked in four different simulations by varying the weights assigned for each QoS attribute and the ranking obtained are compared. The results show that AHP and SAW assigned similar ranks to all three cloud renderfarm services for all simulations.