Soft Computing Methods for System Dependability

311 Pages·2019·11.001 MB·English

by  Mohamed Arezki Mellal

Soft Computing Methods
for System Dependability
Mohamed Arezki Mellal
M’Hamed Bougara University, Algeria
A volume in the Advances in
Systems Analysis, Software
Engineering, and High Performance
Computing (ASASEHPC) Book Series
Published in the United States of America by
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Library of Congress Cataloging-in-Publication Data
Names: Mellal, Mohamed Arezki, editor.
Title: Soft computing methods for system dependability / Mohamed Arezki
Mellal, editor.
Description: Hershey, PA : Engineering Science Reference, 2020. | Includes
bibliographical references. | Summary: “”This book explores the
development and applications of soft computing methods in solving system
dependability problems”--Provided by publisher”-- Provided by publisher.

Identifiers: LCCN 2019032915 (print) | LCCN 2019032916 (ebook) | ISBN
9781799817185 (h/c) | ISBN 9781799817192 (s/c) | ISBN 9781799817208
(eISBN)
Subjects: LCSH: Reliability (Engineering) | Soft computing.
Classification: LCC TA169 .S655 2020 (print) | LCC TA169 (ebook) | DDC
620/.00452028563--dc23
LC record available at https://lccn.loc.gov/2019032915
LC ebook record available at https://lccn.loc.gov/2019032916

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To my parents and my wife.
Editorial Advisory Board
Sameer Al-Dahidi, German Jordanian University, Jordan
Harish Garg, Thapar Institute of Engineering and Technology (Deemed), India
Edward J. Williams, University of Michigan, Dearborn, USA
List of Reviewers
Anu Aggarwal, University of Delhi, India
Nabanita Banerjee, Techno India, India
Houda Daoud, University of Sfax, Tunisia
Santosh Kumar Das, Indian Institute of Technology, India
Mohammad A. Gharaibeh, Hashemite University, Jordan
Razib Hayat Khan, American International University, Bangladesh
Hakduran Koc, University of Houston, Clear Lake, USA
Dalila Laouej, University of Sfax, Tunisia
Yiliu Liu, Norwegian University of Science and Technology, Norway
Seyedali Mirjalili, Torrens University Australia, Australia
Suchismita Satapathy, KIIT University, India
Liudong Xing, University of Massachusetts, Dartmouth, USA
Table of Contents
Foreword.............................................................................................................xiv
Preface..................................................................................................................xv
Chapter 1
Software.Release.Planning.Using.Grey.Wolf.Optimizer........................................1
Vibha Verma, University of Delhi, India
Neha Neha, University of Delhi, India
Anu G. Aggarwal, University of Delhi, India
Chapter 2
Modified.Multi-Grey.Wolf.Pack.for.Vital.Sign-Based.Disease.Identification.....45
Nabanita Banerjee, Techno Main Salt Lake, Kolkata, India
Sumitra Mukhopadhyay, Institute of Radio Physics and Electronics,
University of Calcutta, India
Chapter 3
Analog.Integrated.Circuit.Optimization:.A.0.22µw.Bulk-Driven.Telescopic.
OTA.Optimization.Using.PSO.Program.for.Low.Power.Biomedical.Devices.....95
Houda Daoud, ENIS, University of Sfax, Tunisia
Dalila Laouej, ENIS, University of Sfax, Tunisia
Jihene Mallek, ENIS, University of Sfax, Tunisia
Mourad Loulou, ENIS, University of Sfax, Tunisia
Chapter 4
Enhancing.System.Reliability.Through.Targeting.Fault.Propagation.Scope......131
Hakduran Koc, University of Houston, Clear Lake, USA
Oommen Mathews, University of Houston, Clear Lake, USA

Chapter 5
Soft.Computing.Methods.for.Measuring.Sustainability.in.the.Agriculture.
Sector:.ISM.Method.to.Develop.Barriers.of.Agri-Sustainability.in.India..........161
Suchismita Satapathy, KIIT University, India
Chapter 6
A.Hybrid.Analysis.Method.for.Train.Driver.Errors.in.Railway.Systems...........176
Mohammed Manar Rekabi, Norwegian University of Science and
Technology, Norway
Yiliu Liu, Norwegian University of Science and Technology, Norway
Chapter 7
Performability.Modeling.of.Distributed.Systems.and.Its.Formal.Methods.
Representation.....................................................................................................203
Razib Hayat Khan, American International University-Bangladesh,
Bangladesh, Dhaka
Chapter 8
Sample.Size.Equation.of.Mechanical.System.for.Parametric.Accelerated.Life.
Testing.................................................................................................................234
Seongwoo Woo, Ababa Science and Technology University, Ethiopia
Chapter 9
Risk.Factor.in.Agricultural.Sector:.Prioritizing.Indian.Agricultural.Risk.
Factor.by.MAUT.Method...................................................................................249
Suchismita Satapathy, KIIT University, India
Compilation of References...............................................................................264
About the Contributors....................................................................................288
Index...................................................................................................................292
Detailed Table of Contents
Foreword.............................................................................................................xiv
Preface..................................................................................................................xv
Chapter 1
Software.Release.Planning.Using.Grey.Wolf.Optimizer........................................1
Vibha Verma, University of Delhi, India
Neha Neha, University of Delhi, India
Anu G. Aggarwal, University of Delhi, India
This.chapter.presents.the.application.of.grey.wolf.optimizer.in.software.release.
planning.considering.warranty.based.on.the.proposed.mathematical.model.that.
measures.reliability.growth.of.software.systems..Hence,.optimal.release.and.warranty.
time.is.determined.while.minimizing.the.overall.software.development.cost..The.
software.cost.model.is.based.on.failure.phenomenon.modelled.by.incorporating.fault.
removal.efficiency,.fault.reduction.factor,.and.error.generation..The.model.has.been.
validated.on.the.fault.dataset.of.ERP.systems..Sensitivity.analysis.has.been.carried.
out.to.study.the.discrete.changes.in.the.cost.parameter.due.to.changes.in.optimal.
solution..The.work.significantly.contributes.to.the.literature.by.fulfilling.gaps.of.
reliability.growth.models,.release.problems.considering.warranty,.and.efficient.
ways.for.solving.optimization.problems..Further,.the.grey.wolf.optimizer.result.has.
been.compared.with.genetic.algorithm.and.particle.swarm.optimization.techniques.
Chapter 2
Modified.Multi-Grey.Wolf.Pack.for.Vital.Sign-Based.Disease.Identification.....45
Nabanita Banerjee, Techno Main Salt Lake, Kolkata, India
Sumitra Mukhopadhyay, Institute of Radio Physics and Electronics,
University of Calcutta, India
Noninvasive.process.of.vital.sign.identification.and.design.of.low-cost.decision-
making.system.for.the.betterment.of.rural.health.care.support.is.a.prime.facet.of.
research..The.identification.of.bio-signals.from.different.sensors,.noise.removal,.signal.

processing,.and.decision.making.requires.the.use.of.sophisticated.expert.system..
In.this.chapter,.the.authors.propose.a.modified.multi.grey.wolf.pack.optimization.
technique.(MMGWO).for.better.generalization.and.diversification..The.basic.model.
has.been.modified.using.net.energy.gain.of.the.individual.wolf.in.the.process.of.
hunting..Here.multiple.packs.of.wolves.are.considered.with.simultaneous.sharing.and.
conflict.among.them..The.performance.of.the.proposed.technique.is.tested.on.23.well.
known.classical.benchmark.functions,.CEC.2014.benchmark.problem.set.along.with.
classical.real-life.applications..The.experimental.results.and.related.analysis.show.
that.the.proposed.MMGWO.is.significantly.superior.to.other.existing.techniques.
Chapter 3
Analog.Integrated.Circuit.Optimization:.A.0.22µw.Bulk-Driven.Telescopic.
OTA.Optimization.Using.PSO.Program.for.Low.Power.Biomedical.Devices.....95
Houda Daoud, ENIS, University of Sfax, Tunisia
Dalila Laouej, ENIS, University of Sfax, Tunisia
Jihene Mallek, ENIS, University of Sfax, Tunisia
Mourad Loulou, ENIS, University of Sfax, Tunisia
This.chapter.presents.a.novel.telescopic.operational.transconductance.amplifier.
(OTA).using.the.bulk-driven.MOS.technique..This.circuit.is.optimized.for.ultra-
low.power.applications.such.as.biomedical.devices..The.proposed.the.bulk-driven.
fully.differential.telescopic.OTA.with.very.low.threshold.voltages.is.designed.under.
±0.9V.supply.voltage..Thanks.to.the.particle.swarm.optimization.(PSO).algorithm,.
the.circuit.achieves.high.performances..The.OTA.simulation.results.present.a.DC.
gain.of.63.6dB,.a.GBW.of.2.8MHz,.a.phase.margin.(PM).of.55.8degrees.and.an.
input.referred.noise.of.265.3nV/√Hz.for.a.low.bias.current.of.52nA.
Chapter 4
Enhancing.System.Reliability.Through.Targeting.Fault.Propagation.Scope......131
Hakduran Koc, University of Houston, Clear Lake, USA
Oommen Mathews, University of Houston, Clear Lake, USA
The.unprecedented.scaling.of.embedded.devices.and.its.undesirable.consequences.
leading.to.stochastic.fault.occurrences.make.reliability.a.critical.design.and.
optimization.metric..In.this.chapter,.in.order.to.improve.reliability.of.multi-core.
embedded.systems,.a.task.recomputation-based.approach.is.presented..Given.a.task.
graph.representation.of.the.application,.the.proposed.technique.targets.at.the.tasks.
whose.failures.cause.more.significant.effect.on.overall.system.reliability..The.results.
of.the.tasks.with.larger.fault.propagation.scope.are.recomputed.during.the.idle.times.
of.the.available.processors.without.incurring.any.performance.or.power.overhead..
The.technique.incorporates.the.fault.propagation.scope.of.each.task.and.its.degree.of.
criticality.into.the.scheduling.algorithm.and.maximizes.the.usage.of.the.processing.
elements..The.experimental.evaluation.demonstrates.the.viability.of.the.proposed.
approach.and.generates.more.efficient.results.under.different.latency.constraints.