由施巍松编著的《计算机系统研究基础》的目的是为致力于成为计算机系统领域研究人员的学生介绍相关的基础技术知识。在以操作系统、网络、数据库、计算机体系结构等领域为代表的计算机科学与工程的研究教育中，许多基本的概念，如设计原则、模块化、命名、抽象、并发、通信、容错性、安全性和原子性，都是共同的前沿主题。课程分为两个部分：一是介绍实用系统设计的基本原则，二是在系统设计中如何运用这些原则，比如命名、客户端/服务端、虚拟化以及可靠性。

自从计算机问世以来，计算机系统结构的研究重点发生了很多变化，这让一些希望从事这方面研究的新手觉得很难入门。作者施巍松根据多年从事研究和指导研究生的经验，把计算机系统研究中最常用的原理和关键技术汇集在一起。在《计算机系统研究基础》中的基本知识部分，作者描述了从事系统结构研究的基本要领，包括如何读、写、说，以及英文写作最常见的问题，并给出了12个最经典的设计原理和经验。在关键技术部分，作者从建模、设计、实现和性能评测方面选择了15个关键技术进行了详细的讨论和描述，每一个关键技术的题目都经过精心挑选，并且提供多个实例分析。《计算机系统研究基础》可供计算机系统结构初学者使用，也可供高年级本科生和研究生在学习有关课程时参考。

Part Ⅰ General

 1 Elements

1.1 Top Systems Conferences/Journals

1.2 How to Read a Research Paper

1.3 How to Write a Research Paper

 1.3.1 Abstract

 1.3.2 Introduction

 1.3.3 Background Information/Problem Statement

 1.3.4 Your Approach

 1.3.5 Implementation

 1.3.6 Performance Evaluation

 1.3.7 Related Work

 1.3.8 Conclusions

 1.3.9 Acknowledgement

 1.3.10 References

 1.3.11 Most Common Mistakes in Paper Writing

1.4 How to Give a Presentation

 1.4.1 General Approach

 1.4.2 Understanding the Paper

 1.4.3 Adapting the Paper for Presentation

 1.4.4 Slides

 1.4.5 The Dry-Run

 1.4.6 To Memorize or not to Memorize?

 1.4.7 You Are on the Stage

 1.4.8 Interacting with the Audience and Dealing with Questions

1.5 Final Words: On Being a Scientist

References

 2 Rules of Thumb

2.1 Rules of Thumb

2.2 Further Readings

References

Part Ⅱ Design

 3 Bloom Filters

3.1 Introduction

3.2 Standard Bloom Filters

 3.2.1 Basic Idea of Bloom Filters

 3.2.2 False Positive Rate Estimation

 3.2.3 Optimal Number of Hash Functions

 3.2.4 Another Method of Implementing

3.3 Counting Bloom Filters

3.4 Compressed Bloom Filters

3.5 D-left Counting Bloom Filters

 3.5.1 D-left Hashing

 3.5.2 D-left Counting Bloom Filters

 3.5.3 Performance

3.6 Spectral Bloom Filters

 3.6.1 Basic Principle of SBF

 3.6.2  SBF Frequency Query Optimization

3.7 Dynamic Counting Bloom Filters

3.8 Case Studies

 3.8.1 Case Study 1: Summary Cache

 3.8.2 Case Study 2: IP Traceback

3.9 Conclusion

References

 4 Distributed Hash Tables

4.1 Introduction

4.2 An Overview of DHT

4.3 The Overlay Network of DHT

4.4 Chord: An Implementation of DHT

 4.4.1 Topology of Chord

 4.4.2 Key Lookup in Chord

 4.4.3 Dynamic Updates and Failure Recovery

4.5 Case Study 1: Cooperative Domain Name System （CoDoNS）

 4.5.1 Background and Motivation

 4.5.2 Overview of the System

 4.5.3 DHT in CoDoNS

 4.5.4 Evaluation

4.6 Case Study 2: Cooperative File System （CFS）

 4.6.1 Background and Motivation

 4.6.2 Overview of the System

 4.6.3 DHT in CFS

 4.6.4 Evaluation

References

 5 Locality Sensitive Hashing

5.1 Introduction

 5.1.1 Basic Idea of LSH

 5.1.2 The Origin of LSH

5.2 Overview

 5.2.1 The Definition

 5.2.2 Properties of LSH

 5.2.3 Several LSH Families

 5.2.4 Approximate Nearest Neighbor

5.3 Case Study 1: Large-Scale Sequence Comparison

 5.3.1 Theory

 5.3.2 Algorithm Complexity

 5.3.3 Implementation Details

 5.3.4 Results

5.4 Case Study 2: Image Retrieval

 5.4.1 Motivation

 5.4.2 The Problems of Existing Approaches

 5.4.3 The System

 5.4.4 Results

References

 6 XOR Operations

6.1 Introduction

6.2 XOR Operation

 6.2.1 Truth Table

 6.2.2 Set Diagrams

6.3 XOR Properties

6.4 Compress with XOR

 6.4.1 Case Study 1: XOR-linked list

 6.4.2 Case Study 2: XOR swap algorithm

6.5 Fault Tolerance

 6.5.1 Case Study 3: Hamming （7,4） code

 6.5.2 Hamming Codes with Additional Parity

 6.5.3 Case Study 4: RAID

6.6 Case Study 5: Feistel Cipher

6.7 Case Study 6: Kademlia

 6.7.1 XOR Metric in Kademlia

 6.7.2 Routing Table in Kademlia

 6.7.3 Kademlia Protocol

6.8 Conclusion

References

 7 Adaptation

7.1 Introduction

7.2 How Adaptation Works and Key Issues

 7.2.1 How Does Adaptation Work?

 7.2.2 Classification of Adaptation

7.3 Case Studies

 7.3.1 Case Study 1：Adaption in Internet Routing System

 7.3.2 Case Study 2：Adaptive Self-Configuration for Sensor Networks

References

 8 Optimistic Replication

8.1 Introduction

8.2 Topic Description

 8.2.1 Design Considerations

 8.2.2 Techniques and Algorithms

8.3 Case Studies

 8.3.1 Case Study 1： The Notes System

 8.3.2 Case Study 2：The Bayou system

References

 9 Reputation and Trust

9.1 Introduction

9.2 Reputation Systems：Challenges and Models

 9.2.1 Challenges

 9.2.2 Reputation Models

 9.2.3 Threat Model

9.3 Comparison of Representative Work

9.4 Case Studies

 9.4.1 Case Study 1：EigenTrust

 9.4.2 Case Study 2：HOURS

9.5 Conclusion

References

 10 Moving Average

10.1 Introduction

10.2 Topic Description

 10.2.1 Simple Moving Average

 10.2.2 Cumulative Moving Average

 10.2.3 Weighted Moving Average

 10.2.4 Exponential Weighted Moving Average

10.3 Case Study 1：Attacks Detection

 10.3.1 Introduction of Denial of Service Attack

 10.3.2 Anomalies Detection

 10.3.3 SYN Flooding Detection

 10.3.4 Other Methods

10.4 Case Study 2：Machine Monitoring Technique

10.5 Case Study 3：Data Cleaning in Wireless Sensor Networks

10.6 Conclusion

References

 11 Machine Learning

11.1 Machine Learning Concepts

 11.1.1 Concepts and History

11.2 Introduction of Machine Learning

 11.2.1 A Typical Machine Learning Problem

 11.2.2 Machine Learning in Computer Systems Research

11.3 Machine Learning Techniques

 11.3.1 Category

 11.3.2 Machine Learning Techniques and Algorithms

11.4 Case Studies

 11.4.1 Case Study 1：Large-Scale System Problem Detection

 11.4.2 Case Study 2：Snitch

11.5 Conclusion

References

Part Ⅲ Implementation

 12 Asynchronous I/O

12.1 Motivation

12.2 I/O Multiplexing

12.3 Asynchronous I/O

 12.3.1 Linux Asynchronous I/O

 12.3.2 Windows Overlapped I/O

12.4 Conclusion

References

 13 Multithreading

13.1 Background

13.2 The Concept of Thread

13.3 Hardware Support for Multithreading

 13.3.1 Block Multithreading

 13.3.2 Interleaved Multithreading

 13.3.3 Simultaneous Multithreading

13.4 Multithreading Programming

 13.4.1 POSIX Threads （Pthreads）

 13.4.2 JAVA Threads

 13.4.3 WIN32 Threads

 13.4.4 Common APIs

13.5 Multithreading Synchronization

 13.5.1 Multithreading Synchronization Problems

 13.5.2 Mutual Exclusion

 13.5.3 Solutions of Mutual Exclusion

 13.5.4 Mutual Exclusion Cases

13.6 Case Studies

13.7 Conclusion

References

 14 Virtualization

14.1 Virtualization Definitions

14.2 A Brief History of Virtualization

 14.2.1 The Mainframe Virtualization

 14.2.2 The x86 Virtualization

14.3 Why Virtualization?

14.4 Virtualizatiofi Capabilities

14.5 The Benefits of Virtualization

 14.5.1 Increasing Utilization

 14.5.2 Reducing Cost

 14.5.3 Isolation

 14.5.4 Improving Application Development Process

 14.5.5 Business Continuity

 14.5.6 1Vlanageability, Scalability and Flexibility

14.6 Types of Virtualization

14.7 Virtualization Vendors and Products

14.8 Case Studies

 14.8.1 Case Study 1：JVM

 14.8.2 Case Study 2：VirtualPower

14.9 Issues of Virtualization

 14.9.1 Issues of Adopting Virtualization

 14.9.2 Issues of Providing Virtualization

References

Part Ⅳ Evaluation

 15 Queueing Theory

15.1 Introduction

 15.1.1 Queueing Models

15.2 Fundamental Concepts

 15.2.1 Useful Probability Distributions

 15.2.2 Markov Chain

15.3 Queueing Systems

 15.3.1 Markovian Queues

 15.3.2 Non-Markovian Queues

15.4 Queueing Networks

15.5 Case Studies

 15.5.1 Case Study 1：Telephone Systems

 15.5.2 Case Study 2：A Barber Shop

References

 16 Black Box Testing

16.1 Introduction

16.2 Black Box Testing Techniques

 16.2.1 Equivalence Partitioning

 16.2.2 Boundary Value Analysis

 16.2.3 Decision Table Testing

 16.2.4 Pairwise Testing

 16.2.5 State Transition Tables

 16.2.6 Use Case Testing

16.3 Other Methods of Software Testing

16.4 Case Studies

 16.4.1 Case Study 1：Web Services

 16.4.2 Case Study 2：MobileTest

References

 17 Goodness-of-Fit

17.1 Introduction

17.2 General Topics in Goodness-of-Fit

 17.2.1 Hypothesis Testing

 17.2.2 Definition

 17.2.3 Common Problems in Goodness-of-Fit Tests

 17.2.4 Quantitative Goodness-of-fit Techniques

17.3 Chi-Square Test

 17.3.1 Meaning of the Chi-Square Test

 17.3.2 Definition of Chi-Square

17.4 Kolmogorov-Smirnov test

 17.4.1 How Does K-S Test Work?

 17.4.2 Comparison of Chi-Square and Kolmogorov-Smirnov Tests

17.5 Case Studies

 17.5.1 Case Study 1：Object Characteristics of Dynamic Web Content

 17.5.2 Case Study 2：Failures in High-Performance Computing Systems

References

Index