The knowledge of bandwidth in communication networks can be useful in various applications. Some popular examples are validation of service level agreements, traffic engineering and capacity planning support, detection of congested or underutilized links, optimization of network route selection, dynamic server selection for downloads and visualizing network topologies, to name just a few. Following these various motivations, a variety of bandwidth estimation techniques and tools have been proposed in the last decade and still, several new ones are currently being introduced. They all show a wide spectrum of different assumptions, characteristics, advantages and limitations. In this paper, the bandwidth estimation literature is reviewed, with focus on introducing four specific bandwidth-related metrics including capacity, available bandwidth, achievable throughput and bulk transfer capacity (BTC); describing the main characteristics, strengths and weaknesses of major bandwidth estimation techniques as well as classifying the respective tool implementations. Also, the fundamental challenges, practical issues and difficulties faced by designing and implementing bandwidth estimation techniques are addressed.

For many different applications, current information about the bandwidth-related metrics of the utilized connection is very useful as they directly impact the performance of throughput sensitive applications such as streaming servers, IPTV and VoIP applications. In literature, several tools have been proposed to estimate major bandwidth-related metrics such as capacity, available bandwidth and achievable throughput. The vast majority of these tools fall into one of Packet Pair (PP), Variable Packet Size (VPS), Self-Loading of Periodic Streams (SLoPS) or Throughput approaches. In this study, seven popular bandwidth estimation tools including nettimer, pathrate, pathchar, pchar, clink, pathload and iperf belonging to these four well-known estimation techniques are presented and experimentally evaluated in a controlled testbed environment. Differently from the rest of studies in literature, all tools have been uniformly classified and evaluated according to an objective and sophisticated classification and evaluation scheme. The performance comparison of the tools incorporates not only the estimation accuracy but also the probing time and overhead caused.