The lossy nature of wireless communication leads to many challenges while designing multihop networks. As an integral part of reliable communication in wireless networks, effective link estimation is essential for routing protocols. Recent studies have shown that link reliability-based metrics like ETX have better performance than traditional metrics such as hop count or latency. Usually, such metrics employ techniques like blacklisting, involving thresholds during the link estimation process. In this paper, we conduct a detailed performance analysis of three commonly used link-quality metrics in wireless sensor networks: ETX, 4Bit, and RNP. We study the interplay between these metrics and CTP, a tree-based routing protocol provided by TinyOS. The objectives of our experiment are two fold. First, by applying different link-quality metrics to the same routing protocol, we provide extensive evaluation on ETX, 4Bit and RNP with insights on their performance under different criteria. Second, we study the impact of the presence or absence of a blacklisting policy when using these link quality estimation metrics. As to our knowledge, this paper is the first to compare the performance between these link quality based metrics with networks of different qualities under realistic conditions.

The ease of deploying wireless camera sensor nodes has grown with the reduction of manufacturing costs of low power, high resolution cameras. Although current wireless sensor network platforms have limited on-board resources for solving highly complex computer vision problems, we show that by splitting the processing costs between the sensor node and a powerful backend, we can achieve better classification results. Using such a distributed processing approach, we balance the computational and communication costs for achieving better detection performance while improving the system lifetime.