Advances in Visible Light Communication are enabling novel Internet of Things applications. Going forward, we expect that LED-to-Camera links will enable a wide range of body-centric computing applications. Up until now, most LED-to-Camera studies have been following a deploy-and-test approach instead of a principled methodology. This ad-hoc design raises up two problems. First, we cannot compare fairly the various methods proposed in the literature because they use different types of LEDs and cameras. Second, and perhaps more importantly, we cannot identify the fundamental opportunities and limits of these novel links. To overcome these challenges, we propose a simple analytical model that estimates the range and data rate of LED-to-camera links prior to deployment. The model is built from first principles and requires only a limited set of parameters. To validate the accuracy of our model, we consider the two main transmission modes used in the literature: binary transmission and communication based on the rolling shutter effect. Our experimental evaluation confirms the predictions of the analytical model.

Traditionally, link quality estimation (LQE) has been viewed as an a priori step in sensor network routing protocols because it filters out unreliable links before data transmission. Recent results, however, show that protocols can perform well without a priori LQE. Because getting rid of LQE seems rather counter-intuitive, the aim of this work is to look deeper into the behavior of LQE-free protocols. Our results, based on one of the state-of-the-art LQE-free protocols, show two interesting insights. First, LQE-free protocols manage to choose links that are slightly better than the ones obtained with a priori LQE methods. Second, in traditional protocols, the effort needed to identify good links accounts, on average, for roughly half of the energy consumption of nodes, depending on the nodes' active period and on the inter-packet interval. By eliminating this overhead, LQE-free protocols can save a significant amount of energy compared to standard approaches.

Planetary surface exploration is an appealing application of wireless sensor networks that has been investigated in recent years by the space community, including the European Space Agency. The idea is to deploy a number of self-organizing sensor nodes forming a wireless networked architecture to provide a distributed instrument for the study and exploration of a planetary body. To explore this concept, ESA has funded the research project RF Wireless for Planetary Exploration (RF-WIPE), carried out by GMV, SUPSI and UPM. The purpose of RF-WIPE was to simulate and prototype a wireless sensor network in order to assess the potential and limitations of the technology for the purposes of planetary exploration. In this paper, we illustrate the results of the work carried out within the context of RF-WIPE. Two test case scenarios have been investigated: a distributed sensor network-based instrument and networked planetary surface exploration. Each scenario is related to a particular network configuration. For such configurations, energy models and communication protocols have been developed, simulated, and validated both on laboratory tests and with outdoor field tests. Additionally, node deployment was investigated, and a deployment system based on a mobile robotics platform has been designed and tested.

Asynchronous low-power listening techniques reduce the energy footprint of radio communication by enforcing link layer duty cycling. At the same time, these techniques make broadcast traffic significantly more expensive than unicast traffic. Because broadcast is a key network primitive and is widely used in various protocols, recently several techniques have been proposed to reduce the amount of broadcast activity by merging broadcasts from different protocols. In this paper we focus on collection protocols and investigate the more extreme approach of eliminating broadcast completely. To this end, we design, implement and, evaluate a Broadcast-Free Collection Protocol, BFC. We derive firstorder models to quantify the costs of broadcasts, and evaluate the performance of BFC on a public testbed. Compared to the Collection Tree Protocol, the de facto standard for data collection, BFC achieves double-digit percentage improvements on the duty cycles. The specific benefits to individual nodes depend on the relative cost of unicast activity; we show that the nodes that benefit the most are the sink's neighbors, which are crucial for network lifetime extension. Eliminating broadcast also brings several other advantages, including extra flexibility with link layer calibrations and energy savings in the presence of poor connectivity.

Empirical studies on link blacklisting show that the delivery rate is sensitive to the calibration of the blacklisting threshold. If the calibration is too restrictive (the threshold is too high), all neighbors get blacklisted. On the other hand, if the calibration is too loose (the threshold is too low), unreliable links get selected. This paper investigates blacklisting analytically. We derive a model that accounts for the joint effect of the wireless channel (signal strength variance and coherence time) and the network (node density). The model, validated empirically with mote-class hardware, shows that blacklisting does not help if the wireless channel is stable or if the network is relatively sparse. In fact, blacklisting is most beneficial when the network is relatively dense and the channel is unstable with long coherence times.