Experimental studies have demonstrated that the behavior of real links in low-power wireless networks (such as wireless sensor networks) deviates to a large extent from the ideal binary model used in several simulation studies. In particular, there is a large transitional region in wireless link quality that is characterized by significant levels of unreliability and asymmetry, significantly impacting the performance of higher-layer protocols. We provide a comprehensive analysis of the root causes of unreliability and asymmetry. In particular, we derive expressions for the distribution, expectation, and variance of the packet reception rate as a function of distance, as well as for the location and extent of the transitional region. These expressions incorporate important environmental and radio parameters such as the path loss exponent and shadowing variance of the channel, and the modulation, encoding, and hardware variance of the radios.

Recent experimental studies have shown that wireless links in real sensor networks can be extremely unreliable, deviating to a large extent from the idealized perfect-reception-within-range models used in common network simulation tools. Previously proposed geographic routing protocols commonly employ a maximum-distance greedy forwarding technique that works well in ideal conditions. However, such a forwarding technique performs poorly in realistic conditions as it tends to forward packets on lossy links. Based on a recently developed link loss model, we study the performance of a wide array of forwarding strategies, via analysis, extensive simulations and a set of experiments on motes. We find that the product of the packet reception rate and the distance improvement towards destination ( PRR × d ) is a highly suitable metric for geographic forwarding in realistic environments.

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A recent development in wireless communication is the use of optical shutters and smartphone cameras to create optical links solely from ambient light. At the transmitter, a liquid crystal display (LCD) modulates ambient light by changing its level of transparency. At the receiver, a smartphone camera decodes the optical pattern. This LCD-to-camera link requires low-power levels at the transmitter, and it is easy to deploy because it does not require modifying the existing lighting infrastructure. The system, however, provides a low data rate, of just a few tens of bps. This occurs because the LCDs used in the state-of-the-art are slow single-pixel transmitters. To overcome this limitation, we introduce a novel multi-pixel display. Our display is similar to a simple screen, but instead of using embedded LEDs to radiate information, it uses only the surrounding ambient light. We build a prototype, called SunBox, and evaluate it indoors and outdoors with both, artificial and natural ambient light. Our results show that SunBox can achieve a throughput between 2 kbps and 10 kbps using a low-end smartphone camera with just 30 FPS. To the best of our knowledge, this is the first screen-to-camera system that works solely with ambient light.

We explore a new alternative for drones to gather information from sensors. Instead of using the traditional radiofrequency spectrum, whose broadcast nature makes it more difficult to poll specific objects, we utilize the light spectrum. In our system, the drone carries a light, and flies to an area that it is interested in polling. Only the sensor (tag) under the coverage of the light sends data back by backscattering the impinging light waves. Enabling this system poses two challenges. First, a reliable modulation method with light is required. The method must overcome noise dynamics introduced by the drone (mechanical oscillations), the object (backscattering effects) and the environment (interference from ambient light). Second, to facilitate the deployment of tags in pervasive applications, the design of the tag should be battery-less and have a small surface area. These requirements limit the amount of power available for reception, transmission and sensing, since the energy harvested by solar cells is proportional to their surface area. Regarding the first challenge, we show that the amplitude-based modulation methods used in state-of-the-art studies do not work in our scenario, and investigate instead a frequency-based approach. For the second challenge, we optimize the computation, reception and transmission of the tag to create a battery-less design that operates with frequency-modulated signals generated from light. We build a prototype for the drone and the tag, and test them under different lighting scenarios: dark, indoors, and outdoors with sunlight. The results show that, under standard indoor lighting, our system can attain a polling range of 1.1 m with a data rate of 120 bps, while the tag operates with small solar cells and consumes less than 1 mW.