From measures to conclusions using Analytic Hierarchy Process in dependability benchmarkind

Abstract

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Dependability benchmarks are aimed at comparing and selecting alternatives in application domains where faulty conditions are present. However, despite its importance and intrinsic complexity, a rigorous decision process has not been defined yet. As a result, benchmark conclusions may vary from one evaluator to another, and often, that process is vague and hard to follow, or even nonexistent. This situation affects the repeatability and reproducibility of that analysis process, making difficult the cross-comparison of results between works. To mitigate these problems, this paper proposes the integration of the analytic hierarchy process (AHP), a widely used multicriteria decision-making technique, within dependability benchmarks. In addition, an assisted pairwise comparison approach is proposed to automate those aspects of AHP that rely on judgmental comparisons, thus granting consistent, repeatable, and reproducible conclusions. Results from a dependability benchmark for wireless sensor networks are used to illustrate and validate the proposed approach.This work was supported in part by the Spanish Project ARENES under Grant TIN2012-38308-C02-01 and in part by the Programa de Ayudas de Investigacion y Desarrollo through the Universitat Politecnica de Valencia, Valencia, Spain. The Associate Editor coordinating the review process was Dr. Dario Petri.Martínez Raga, M.; Andrés Martínez, DD.; Ruiz García, JC.; Friginal López, J. (2014). From measures to conclusions using Analytic Hierarchy Process in dependability benchmarkind. IEEE Transactions on Instrumentation and Measurement. 63(11):2548-2556. https://doi.org/10.1109/TIM.2014.2348632S25482556631