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Item type:Publication, Access status: with files , AHOI: Inexpensive, low-power communication and localization for underwater sensor networks and μAUVs(Association for Computing Machinery (ACM), 2020-01); ; The recent development of small, cheap AUVs enables a plethora of underwater near- and inshore applications. Among these are monitoring of wind parks, detection of pollution sources, water-quality inspection, and the support of divers during disaster management. These tasks profit from online reporting, control, and AUV swarm interaction; yet they require underwater communication. Unfortunately, commercial devices are prohibitively expensive and typically closed-source, hampering their application in affordable products and research. Therefore, we developed the open-source1 ahoi acoustic modem. It is (i) small enough to be carried by micro AUVs, (ii) consumes little enough energy to not diminish operation times of its host, (iii) comes at an attractive unit cost below $600, (iv) can reliably communicate at distances of 150 m and more, and (v) supports ranging without additional hardware. Due to its modular build, the modem can be customized and is suitable as research platform to analyze, e.g., MAC and routing protocols. We conducted extensive real-world studies and present results of communication range, packet reception rate, ranging accuracy, and efficient and reliable self-localization. Finally, we draw conclusions regarding acoustic communication, ranging, and localization with inexpensive and low-power devices that go beyond a particular device. Our study, hence, encompasses general insights, observations, and recommendations.Publicationtype: Journal ArticleScopus© Citations 47 225 1448 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Whisper: Fast flooding for low-powerwireless networks(Association for Computing Machinery (ACM), 2019-10-01); 20 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , IdealVolting: reliable undervolting on Wireless Sensor NodesThe energy consumption of Wireless Sensor Networks (WSNs) correlates with the voltage level at which the nodes are powered-a lowered voltage leads to a prolonged lifetime of nodes and networks. Operating nodes at voltage levels below the recommendation-so-called undervolting-saves energy but is accompanied by an increased risk of failures. In this article, we show that a WSN can still work reliably, even if the voltage recommendations are violated. We show that there is a correlation between temperature and error-proneness at the same voltage level and that ideal voltage levels depend on environmental conditions. Especially in outdoor deployments, temperatures fluctuate often and heavily. Additionally, we show that these ideal voltage levels are different for each individual node. To deal with these individual variations and varying temperatures, we present a supervised learning strategy that is able to keep the nodes in uncritical states even if environmental conditions are constantly and heavily changing while saving as much energy as possible by constantly adapting the voltage level of these nodes to an individually ideal level. All measurements were performed on sensor node prototypes that are also presented in this article. In detailed evaluations, it is shown (i) that a single node will never run in the same unsafe state twice, (ii) that only five known bias points are needed to predict nearly all temperature dependencies for an individual node, and, thus, (iii) that a system of undervolted nodes can be as reliable as a conventionally powered network while prolonging the lifetime by more than 40%.Publicationtype: Journal Article43 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Perpetual data collection with energy-harvesting sensor networks(2014-08-08); ; ; 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.Publicationtype: Journal Article31 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Opportunistic routing in low duty-cycle wireless sensor networks(Association for Computing Machinery (ACM), 2014); ; Johansson, MikaelOpportunistic 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.Publicationtype: Journal Article3