Opportunistic routing is widely known to have substantially better performance than unicast routing in wireless networks with lossy links. However, wireless sensor networks are usually duty cycled, that is, they frequently enter sleep states to ensure long network lifetime. This renders existing opportunistic routing schemes impractical, as they assume that nodes are always awake and can overhear other transmissions. In this article we introduce ORW, a practical opportunistic routing scheme for wireless sensor networks. ORW uses a novel opportunistic routing metric, EDC, that reflects the expected number of duty-cycled wakeups that are required to successfully deliver a packet from source to destination. We devise distributed algorithms that find the EDC-optimal forwarding and demonstrate using analytical performance models and simulations that EDC-based opportunistic routing results in significantly reduced delay and improved energy efficiency compared to traditional unicast routing. In addition, we evaluate the performance of ORW in both simulations and testbed-based experiments. Our results show that ORW reduces radio duty cycles on average by 50% (up to 90% on individual nodes) and delays by 30% to 90% when compared to the state-of-the-art.

A sustainable, uniform, and utility-maximizing operation of energy-harvesting sensor networks requires methods for aligning consumption with harvest. This article presents a lightweight algorithm for online load adaptation of energy-harvesting sensor nodes using supercapacitors as energy buffers. The algorithm capitalizes on the elementary relationship between state of charge and voltage that is characteristic for supercapacitors. It is particularly designed to handle the nonlinear system model, and it is lightweight enough to run on low-power sensor node hardware. We define two energy policies, evaluate their performance using real-world solar-harvesting traces, and analyze the influence of the supercapacitor's capacity and imprecisions in harvest forecasts. To show the practical merit of our algorithm, we devise a load adaptation scheme for multihop data collection sensor networks and run a 4-week field test. The results show that (i) choosing a duty cycle a priori is infeasible, (ii) our algorithm increases the achievable work load of a node when using forecasts, (iii) uniform and steady operation is achieved, and (iv) depletion can be prevented in most cases.

This article presentsWhisper, a fast and reliable protocol to flood small amounts of data into a multi-hop network. Whisper makes use of synchronous transmissions, a technique first introduced by the Glossy flooding protocol. In contrast to Glossy, Whisper does not let the radio switch from receive to transmit mode between messages. Instead, it makes nodes continuously transmit identical copies of the message and eliminates the gaps between subsequent transmissions. To this end, Whisper embeds the message to be flooded into a signaling packet that is composed of multiple packlets-where a packlet is a portion of the message payload that mimics the structure of an actual packet. A node must intercept only one of the packlets to detect that there is an ongoing transmission and that it should start forwarding the message. This allows Whisper to speed up the propagation of the flood and, thus, to reduce the overall radio-on time of the nodes. Our evaluation on the FlockLab testbed shows thatWhisper achieves comparable reliability but 2×lower radio-on time than Glossy. We further show that by embedding Whisper in an existing data collection application, we can more than double the lifetime of the network.