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Modeling and Optimization of Parallel and Distributed Embedded Systems.

By: Contributor(s): Material type: TextTextSeries: IEEE Press SeriesPublisher: Newark : John Wiley & Sons, Incorporated, 2016Copyright date: ©2016Edition: 1st edDescription: 1 online resource (444 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781119086390
Subject(s): Genre/Form: Additional physical formats: Print version:: Modeling and Optimization of Parallel and Distributed Embedded SystemsDDC classification:
  • 004/.35
LOC classification:
  • QA76.58 -- .M86 2016eb
Online resources:
Contents:
Intro -- Title Page -- Copyright -- Dedication -- Table of Contents -- Preface -- About This Book -- Highlights -- Intended Audience -- Organization of the Book -- Acknowledgment -- Part One: Overview -- Chapter 1: Introduction -- 1.1 Embedded Systems Applications -- 1.2 Characteristics of Embedded Systems Applications -- 1.3 Embedded Systems-Hardware and Software -- 1.4 Modeling-An Integral Part of the Embedded Systems Design Flow -- 1.5 Optimization in Embedded Systems -- 1.6 Chapter Summary -- Chapter 2: Multicore-Based EWSNs-An Example of Parallel and Distributed Embedded Systems -- 2.1 Multicore Embedded Wireless Sensor Network Architecture -- 2.2 Multicore Embedded Sensor Node Architecture -- 2.3 Compute-Intensive Tasks Motivating the Emergence of MCEWSNs -- 2.4 MCEWSN Application Domains -- 2.5 Multicore Embedded Sensor Nodes -- 2.6 Research Challenges and Future Research Directions -- 2.7 Chapter Summary -- Part Two: Modeling -- Chapter 3: An Application Metrics Estimation Model for Embedded Wireless Sensor Networks -- 3.1 Application Metrics Estimation Model -- 3.2 Experimental Results -- 3.3 Chapter Summary -- Chapter 4: Modeling and Analysis of Fault Detection and Fault Tolerance in Embedded Wireless Sensor Networks -- 4.1 Related Work -- 4.2 Fault Diagnosis in WSNs -- 4.3 Distributed Fault Detection Algorithms -- 4.4 Fault-Tolerant Markov Models -- 4.5 Simulation of Distributed Fault Detection Algorithms -- 4.6 Numerical Results -- 4.7 Research Challenges and Future Research Directions -- 4.8 Chapter Summary -- Chapter 5: A Queueing Theoretic Approach for Performance Evaluation of Low-Power Multicore-Based Parallel Embedded Systems -- 5.1 Related Work -- 5.2 Queueing Network Modeling of Multicore Embedded Architectures -- 5.3 Queueing Network Model Validation -- 5.4 Queueing Theoretic Model Insights -- 5.5 Chapter Summary.
Part Three: Optimization -- Chapter 6: Optimization Approaches in Distributed Embedded Wireless Sensor Networks -- 6.1 Architecture-Level Optimizations -- 6.2 Sensor Node Component-Level Optimizations -- 6.3 Data Link-Level Medium Access Control Optimizations -- 6.4 Network-Level Data Dissemination and Routing Protocol Optimizations -- 6.5 Operating System-Level Optimizations -- 6.6 Dynamic Optimizations -- 6.7 Chapter Summary -- Chapter 7: High-Performance Energy-Efficient Multicore-Based Parallel Embedded Computing -- 7.1 Characteristics of Embedded Systems Applications -- 7.2 Architectural Approaches -- 7.3 Hardware-Assisted Middleware Approaches -- 7.4 Software Approaches -- 7.5 High-Performance Energy-Efficient Multicore Processors -- 7.6 Challenges and Future Research Directions -- 7.7 Chapter Summary -- Chapter 8: An MDP-Based Dynamic Optimization Methodology for Embedded Wireless Sensor Networks -- 8.1 Related Work -- 8.2 MDP-Based Tuning Overview -- 8.3 Application-Specific Embedded Sensor Node Tuning Formulation as an MDP -- 8.4 Implementation Guidelines and Complexity -- 8.5 Model Extensions -- 8.6 Numerical Results -- 8.7 Chapter Summary -- Chapter 9: Online Algorithms for Dynamic Optimization of Embedded Wireless Sensor Networks -- 9.1 Related Work -- 9.2 Dynamic Optimization Methodology -- 9.3 Experimental Results -- 9.4 Chapter Summary -- Chapter 10: A Lightweight Dynamic Optimization Methodology for Embedded Wireless Sensor Networks -- 10.1 Related Work -- 10.2 Dynamic Optimization Methodology -- 10.3 Algorithms for Dynamic Optimization Methodology -- 10.4 Experimental Results -- 10.5 Chapter Summary -- Chapter 11: Parallelized Benchmark-Driven Performance Evaluation of Symmetric Multiprocessors and Tiled Multicore Architectures for Parallel Embedded Systems -- 11.1 Related Work -- 11.2 Multicore Architectures and Benchmarks.
11.3 Parallel Computing Device Metrics -- 11.4 Results -- 11.5 Chapter Summary -- Chapter 12: High-Performance Optimizations on Tiled Manycore Embedded Systems: A Matrix Multiplication Case Study -- 12.1 Related Work -- 12.2 Tiled Manycore Architecture (TMA) Overview -- 12.3 Parallel Computing Metrics and Matrix Multiplication (MM) Case Study -- 12.4 Matrix Multiplication Algorithms' Code Snippets for Tilera's TILEPro64 -- 12.5 Performance Optimization on a Manycore Architecture -- 12.6 Results -- 12.7 Chapter Summary -- Chapter 13: Conclusions -- References -- Index -- End User License Agreement.
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Intro -- Title Page -- Copyright -- Dedication -- Table of Contents -- Preface -- About This Book -- Highlights -- Intended Audience -- Organization of the Book -- Acknowledgment -- Part One: Overview -- Chapter 1: Introduction -- 1.1 Embedded Systems Applications -- 1.2 Characteristics of Embedded Systems Applications -- 1.3 Embedded Systems-Hardware and Software -- 1.4 Modeling-An Integral Part of the Embedded Systems Design Flow -- 1.5 Optimization in Embedded Systems -- 1.6 Chapter Summary -- Chapter 2: Multicore-Based EWSNs-An Example of Parallel and Distributed Embedded Systems -- 2.1 Multicore Embedded Wireless Sensor Network Architecture -- 2.2 Multicore Embedded Sensor Node Architecture -- 2.3 Compute-Intensive Tasks Motivating the Emergence of MCEWSNs -- 2.4 MCEWSN Application Domains -- 2.5 Multicore Embedded Sensor Nodes -- 2.6 Research Challenges and Future Research Directions -- 2.7 Chapter Summary -- Part Two: Modeling -- Chapter 3: An Application Metrics Estimation Model for Embedded Wireless Sensor Networks -- 3.1 Application Metrics Estimation Model -- 3.2 Experimental Results -- 3.3 Chapter Summary -- Chapter 4: Modeling and Analysis of Fault Detection and Fault Tolerance in Embedded Wireless Sensor Networks -- 4.1 Related Work -- 4.2 Fault Diagnosis in WSNs -- 4.3 Distributed Fault Detection Algorithms -- 4.4 Fault-Tolerant Markov Models -- 4.5 Simulation of Distributed Fault Detection Algorithms -- 4.6 Numerical Results -- 4.7 Research Challenges and Future Research Directions -- 4.8 Chapter Summary -- Chapter 5: A Queueing Theoretic Approach for Performance Evaluation of Low-Power Multicore-Based Parallel Embedded Systems -- 5.1 Related Work -- 5.2 Queueing Network Modeling of Multicore Embedded Architectures -- 5.3 Queueing Network Model Validation -- 5.4 Queueing Theoretic Model Insights -- 5.5 Chapter Summary.

Part Three: Optimization -- Chapter 6: Optimization Approaches in Distributed Embedded Wireless Sensor Networks -- 6.1 Architecture-Level Optimizations -- 6.2 Sensor Node Component-Level Optimizations -- 6.3 Data Link-Level Medium Access Control Optimizations -- 6.4 Network-Level Data Dissemination and Routing Protocol Optimizations -- 6.5 Operating System-Level Optimizations -- 6.6 Dynamic Optimizations -- 6.7 Chapter Summary -- Chapter 7: High-Performance Energy-Efficient Multicore-Based Parallel Embedded Computing -- 7.1 Characteristics of Embedded Systems Applications -- 7.2 Architectural Approaches -- 7.3 Hardware-Assisted Middleware Approaches -- 7.4 Software Approaches -- 7.5 High-Performance Energy-Efficient Multicore Processors -- 7.6 Challenges and Future Research Directions -- 7.7 Chapter Summary -- Chapter 8: An MDP-Based Dynamic Optimization Methodology for Embedded Wireless Sensor Networks -- 8.1 Related Work -- 8.2 MDP-Based Tuning Overview -- 8.3 Application-Specific Embedded Sensor Node Tuning Formulation as an MDP -- 8.4 Implementation Guidelines and Complexity -- 8.5 Model Extensions -- 8.6 Numerical Results -- 8.7 Chapter Summary -- Chapter 9: Online Algorithms for Dynamic Optimization of Embedded Wireless Sensor Networks -- 9.1 Related Work -- 9.2 Dynamic Optimization Methodology -- 9.3 Experimental Results -- 9.4 Chapter Summary -- Chapter 10: A Lightweight Dynamic Optimization Methodology for Embedded Wireless Sensor Networks -- 10.1 Related Work -- 10.2 Dynamic Optimization Methodology -- 10.3 Algorithms for Dynamic Optimization Methodology -- 10.4 Experimental Results -- 10.5 Chapter Summary -- Chapter 11: Parallelized Benchmark-Driven Performance Evaluation of Symmetric Multiprocessors and Tiled Multicore Architectures for Parallel Embedded Systems -- 11.1 Related Work -- 11.2 Multicore Architectures and Benchmarks.

11.3 Parallel Computing Device Metrics -- 11.4 Results -- 11.5 Chapter Summary -- Chapter 12: High-Performance Optimizations on Tiled Manycore Embedded Systems: A Matrix Multiplication Case Study -- 12.1 Related Work -- 12.2 Tiled Manycore Architecture (TMA) Overview -- 12.3 Parallel Computing Metrics and Matrix Multiplication (MM) Case Study -- 12.4 Matrix Multiplication Algorithms' Code Snippets for Tilera's TILEPro64 -- 12.5 Performance Optimization on a Manycore Architecture -- 12.6 Results -- 12.7 Chapter Summary -- Chapter 13: Conclusions -- References -- Index -- End User License Agreement.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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