The design space of probing algorithms for network-performance measurement

We present a framework for the design and analysis of probing methods to monitor network performance, an important technique for collecting measurements in tasks such as fault detection. We use this framework to study the interaction among numerous, possibly conflicting, optimization goals in the design of a probing algorithm. We present a rigorous definition of a probing-algorithm design problem that can apply broadly to network-measurement scenarios. We also present several metrics relevant to the analysis of probing algorithms, including probing frequency and network coverage, communication and computational overhead, and the amount of algorithm state required. We show inherent tradeoffs among optimization goals and give hardness results for achieving some combinations of optimization goals. We also consider the possibility of developing approximation algorithms for achieving some of the goals and describe a randomized approach as an alternative, evaluating it using our framework. Our work aids future development of low-overhead probing techniques and introduces principles from IP-based networking to theoretically grounded approaches for concurrent path-selection problems.