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Low-Power Wide-Area Networks (LP-WANs) are seeing wide-spread deployments connecting millions of sensors, each powered by a ten-year AA battery to radio infrastructure, often miles away. By design, iteratively querying all sensors in an LP-WAN may take several hours or even days, given the stringent battery limits of client radios. This precludes obtaining even an approximate real-time view of sensed information across LP-WAN devices over a large area, say in the event of a disaster, fault or simply for diagnostics.This paper presents QuAiL 1 , a system that provides a coarse aggregate view of sensed data across LP-WAN devices over a wide- area within a time span of just one LP-WAN packet. QuAiL achieves this by coordinating multiple LP-WAN radios to transmit their information synchronously in time and frequency despite their power constraints. We design each client's transmission so that the base station can retrieve an approximate heatmap of sensed data by exploiting the spatial correlation of this data across clients. We further show how our system can be optimized for statistical and machine learning queries, all while maintaining the security and privacy of sensed data from individual clients. Our deployment over a 3 sq. km. LP-WAN deployment around CMU campus in Pittsburgh demonstrates a 4x faster information retrieval versus the state-of- the-art statistical methods to retrieve the spatial sensor heatmap at a desired resolution. 

Low-Power Wide Area Networks, such as LoRaWAN, are rapidly gaining popularity in the field of wireless sensing and actuation. While LoRaWan is heavily studied in applications and performance, the concept of time has rarely been characterized in such networks. Many applications will require synchronized local clocks with varying levels of precision in order to maintain consistency and coordination in the network. Traditional time synchronization protocols however do not fit LoRaWAN's delay-inherent, low duty cycle, network model and wide-area deployment topology. Meanwhile, relying on GPS for time is not an option for low-power applications. In this paper, we present LongShoT, a time synchronization scheme built on LoRaWan capable of synchronizing device clocks to within 10μs of a reference clock with a single network request. This is achieved by utilizing the deterministic properties of Lo-Ra Wan networks along with hardware- and MAC-level timestamping of packets. LongShoT was implemented on consumer off-the-shelf hardware and evaluated over physically distributed devices using GPS 1PPS as a reference. Our results show that LongShoT achieves an average synchronization error of less than 2μs and compensates oscillator drift to less than 0.1ppm with devices distributed within 4km of a gateway.