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IoT is rapidly growing from small-scale apps to large-scale apps. Small-scale apps employ short-range radios like Zigbee,BLE while large-scale apps employ long-range radios like LoRa,NB-IoT. The other upcoming category of apps like P2P energy-trade in smart homes are termed mesoscale IoT apps. There are no specialized radios for these apps. They either use short/long-range radios. To close this gap, we explored mesoscale apps using the COTS IoT radios available. Our qualitative analysis identifies Zigbee and LoRa as potential candidates. Our quantitative analysis on single and multi-hop topologies showed that Zigbee and LoRa achieve competitive throughput at a distance of 500-1200m from the gateway. A fundamental finding of these analyses is that a multi-radio system that can efficiently switch between Zigbee and LoRa performs better than the single-radio systems. However, instantaneously selecting and switching to a high-throughput radio during transmission is not trivial because of the erratic link quality dynamics. To address this issue, we developed MARS, that uses path quality metrics to instantaneously select the high-throughput radio during transmission. However, realizing MARS on resource-constrained end devices entails the challenge of obtaining instantaneous path-quality metrics. Traditional path quality estimation is not instantaneous due to propagation and queuing delays. We overcome this challenge by showing that collecting local path metrics as input to our decision trees provides sufficient information to instantaneously identify the high-throughput radio. The radio selector of MARS is powered by TAO-CART trees. The evaluation of MARS on a large-scale mesh topology at two different locations shows that MARS can efficiently identify and switch to the high-throughput radio during transmission, leading to an average throughput gain of 48.2% and 49.79% over its competitors.

Wireless networks have been widely deployed for many Internet-of-Things (IoT) applications, like smart cities and precision agriculture. Low Power Wide Area Networking (LPWAN) is an emerging IoT networking paradigm to meet three key requirements of IoT applications, i.e., low cost, large scale deployment and high energy efficiency. Among all available LPWAN technologies, LoRa networking has attracted much attention from both academia and industry, since it specifies an open standard and allows us to build autonomous LPWAN networks without any third-party infrastructure. Many LoRa networks have been developed recently, e.g., managing solar plants in Carson City, Nevada, USA and power monitoring in Lyon and Grenoble, France. However, there are still many research challenges to develop practical LoRa networks, e.g., link coordination, resource allocation, reliable transmissions and security. This article provides a comprehensive survey on LoRa networks, including the technical challenges of deploying LoRa networks and recent solutions. Based on our detailed analysis of current solutions, some open issues of LoRa networking are discussed. The goal of this survey paper is to inspire more works on improving the performance of LoRa networks and enabling more practical deployments.

Recent studies exploited external periodic synchronous signals to synchronize a pair of network nodes to address a threat of delaying the communications between the nodes. However, the sensing-based synchronization may yield faults due to nonmalicious signal and sensor noises. This paper considers a system of N nodes that will fuse their peer-to-peer synchronization results to correct the faults. Our analysis gives the lower bound of the number of faults that the system can tolerate when N is up to 12. If the number of faults is no greater than the lower bound, the faults can be identified and corrected. We also prove that the system cannot tolerate more than N-2 faults. Our results can guide the design of resilient sensing-based clock synchronization systems.