Introduction of Computer System

A comprehensive introduction to reliability and availability modeling, analysis, and design at the system, hardware, and software levels Reliability of Computer Systems and Networks presents the fundamentals of reliability and availability analysis for various computer hardware, software, and networked systems. Reliability and availability as major objectives in system design are the focus. Various redundancy and fault-tolerant techniques, as well as error-correcting coding techniques are treated. The author proposes a high-level design approach based on apportioning the reliability and availability goals to subsystems and provides various techniques for achieving these subsystem goals. The next step is an efficient, exact optimization approach based on upper and lower bounds to minimize the number of feasible candidates. The most readily applied methods for analysis are utilized and design techniques are derived from basic principles. Analytical simplifications and approximations are developed to validate the results of computer models used for large-scale complex problems. Coverage includes: Coding and decoding schemes for error detection and correction including chip reliabilityComparison of the reliability and availability of parallel, standby, and majority voting architecturesFormulation, solution, and interpretation of Markov models for repairable systemsIntroduction and comparison of various RAID memory systemsThe architecture and fault-tolerant principles of TANDEM and STRATUS non-stop computer systemsPractical and tutorial examples and numerous practice problemsAppendices which cover the necessary background material on probability, reliability, andarchitecture Reliability of Computer Systems and Networks offers in-depth and up-to-date coverage of reliability and availability for students with a focus on important applications areas, computer systems, and networks.

Presenting a reference model architecture for the design of intelligent systems Engineering of Mind presents the foundations for a computational theory of intelligence. It discusses the main streams of investigation that will eventually converge in a scientific theory of mind and proposes an avenue of research that might best lead to the development of truly intelligent systems. This book presents a model of the brain as a hierarchy of massive parallel computational modules and data structures interconnected by information pathways. Using this as the basic model on which intelligent systems should be based, the authors propose a reference model architecture that accommodates concepts from artificial intelligence, control theory, image understanding, signal processing, and decision theory. Algorithms, procedures, and data embedded within this architecture would enable the analysis of situations, the formulation of plans, the choice of behaviors, and the computation of uncertainties. The computational power to implement the model can be achieved in practical systems in the foreseeable future through hierarchical and parallel distribution of computational tasks. The authors’ reference model architecture is expressed in terms of the Real-time Control System (RCS) that has been developed primarily at the National Institute of Standards and Technology. Suitable for engineers, computer scientists, researchers, and students, Engineering of Mind blends current theory and practice to achieve a coherent model for the design of intelligent systems.