Protocols and applications in wireless mesh networks often optimize their performance by measuring the quality of wireless links. However, measuring and characterizing link-quality is a challenging task due to the nature of wireless channel and device-specific properties of radios. The paper proposes two aspects of link-quality measurement and estimation in realistic networks that benefit higher-layer protocols. First, we analyze the statistical properties of link-quality metrics, such as received signal strength and packet error rates, in an indoor IEEE 802.11 mesh network. We show that the statistical distribution and memory properties vary across different links, but are predictable. The next contribution of the paper is a real-time measurement framework that enables higher-level protocols in wireless mesh networks. We discuss the architectural requirements and our implementation experiences of a measurement framework. In addition, we provide three concrete applications that use the measured link-quality and statistical inference to better adapt their behavior.
