A network measurement architecture for adaptive applications

摘要

The quality of network connectivity between a pair of Internet hosts can vary greatly. Adaptive applications can cope with these differences in connectivity by choosing alternate representations of objects or streams or by downloading the objects from alternate locations. In order to effectively adapt, applications must discover the condition of the network before communicating with distant hosts. Unfortunately, the ability to predict or report the quality of connectivity is missing in today's suite of Internet services. To address this limitation, we have developed SPAND (shared passive network performance discovery), a system that facilitates the development of adaptive network applications. In each domain, applications make passive application specific measurements of the network and store them in a local centralized repository of network performance information. Other applications may retrieve this information from the repository and use the shared experiences of all hosts in a domain to predict future performance. In this way, applications can make informed decisions about adaptation choices as they communicate with distant hosts. In this paper, we describe and evaluate the SPAND architecture and implementation. We show how the architecture makes it easy to integrate new applications into our system and how the architecture has been used with specifics types of data transport. Finally, we describe LookingGlass, a WWW mirror site selection tool that uses SPAND. LookingGlass meets the conflicting goals of collecting passive network performance measurements and maintaining good client response times. In addition, LookingGlass's server selection algorithms based on application level measurements perform much better than techniques that rely on geographic location or route metrics.