Book contents
- Frontmatter
- Contents
- Notation
- Introduction
- 1 Preliminaries
- 2 Fundamental Conditions for Additive Network Tomography
- 3 Monitor Placement for Additive Network Tomography
- 4 Measurement Path Construction for Additive Network Tomography
- 5 Fundamental Conditions for Boolean Network Tomography
- 6 Measurement Design for Boolean Network Tomography
- 7 Stochastic Network Tomography Using Unicast Measurements
- 8 Stochastic Network Tomography Using Multicast Measurements
- 9 Other Applications and Miscellaneous Techniques
- Appendix Datasets for Evaluations
- Index
6 - Measurement Design for Boolean Network Tomography
Published online by Cambridge University Press: 25 May 2021
- Frontmatter
- Contents
- Notation
- Introduction
- 1 Preliminaries
- 2 Fundamental Conditions for Additive Network Tomography
- 3 Monitor Placement for Additive Network Tomography
- 4 Measurement Path Construction for Additive Network Tomography
- 5 Fundamental Conditions for Boolean Network Tomography
- 6 Measurement Design for Boolean Network Tomography
- 7 Stochastic Network Tomography Using Unicast Measurements
- 8 Stochastic Network Tomography Using Multicast Measurements
- 9 Other Applications and Miscellaneous Techniques
- Appendix Datasets for Evaluations
- Index
Summary
Based on the identifiability measures for Boolean network tomography presented in Chapter 5, this chapter addresses the follow-up question of how to design the measurement system to optimize the identifiability measure of interest, with a focus on the placement of monitoring nodes.Depending on the mechanism to collect measurements, the problem is divided into (1) monitor placement, (2) beacon placement, and (3) monitoring-aware service placement, where the first approach requires monitoring nodes at both endpoints of each measurement path, the second approach requires a monitoring node only at one of the endpoints of each measurement path, and the third approach requires each measurement path to be the default routing path between a client and a server. As many of such problems are NP-hard, the focus is put on establishing the hardness of the optimal solution and developing polynomial-time suboptimal algorithms with performance guarantees. The chapter also covers a suite of path construction problems addressing how to construct or select measurement paths to optimize the tradeoff between identifiability and probing cost.
Keywords
- Type
- Chapter
- Information
- Network TomographyIdentifiability, Measurement Design, and Network State Inference, pp. 138 - 173Publisher: Cambridge University PressPrint publication year: 2021