# Design and Analysis of Adaptive Hierarchical Low-Power Long-Range Networks
## 1 Introduction, Related Work and Our Approach  
A plethora of small-factor devices with networking, computation and sensing capabilities are embedded in the physical world and interconnect it with the digital world of the Internet, creating the \"Internet of Things\" (IoT). Such networked devices are continuously deployed to accomodate the needs of different application domains, and, as a result, they have already surpassed the number of computers and mobile phones operated by humans. All these devices connected to the Internet enable an entirely new type of application and services that clearly affect all aspects of business and living. One fundamental aspect of IoT is the networking technologies that allow the communication between the embedded devices and the Internet cloud services. For this reason, all the efforts up untilnow focused predominantly on wireless low-power transmission technologies such as IEEE 802.15.4 (ZigBee, Z-Wave) and IEEE 802.15.11 (Bluetooth, BLE) [1]. These technologies provide reasonably high bit rate exchanges over a short range. Due to this low-power and short-range mode of operation, deploying a large-sized network requires the use of communication protocols that deliver messages based on a multi-path approach [2]. Such a multi-path approach provides certain benefits, such as the capability to overcome communication obstacles [3, 4], and the overall improvement of security of the network [5]. Experimentation over real-world wireless sensor networks has highlighted the difficulties and limitations of the multi-hop short-range paradigm [6]. In order to overcome these technical difficulties, several alternative solutions have been proposed, for example, by varying the transmission range of the nodes [4], providing hierarchical network structures [7] or even employing mobile nodes to facilitate network management [8]. Despite all these efforts, the reduced transmission range creates several difficulties that are difficult to overcome. As a result, real-world deployments need to use a combination of networking technologies in order to deliver urban-scale coverage in the context of smart city services [9, 10]. Recently, a new approach has been proposed that exploits sub-GHz communication, which allows for transmitting over longer distances, and very low data transmission rates, which allow for reducing significantly power consumption [11]. This approach of network has been titled Low-Power Wide Area Networks (LPWANs) as exposed to short-range high-frequency communication. Low-frequency signals are not as attenuated by thick walls or multi-path propagation as high-frequency signals contributing in this way to robustness and reliability of the signal [12]. In LPWAN, the embedded devices are connected to Concentrators (also called a _collector_ or _concentrator_) that are located several kilometres away. Evidently, LPWANs provide multiple benefits for IoT deployments, providing _higher autonomy_ due to the reduced energy consumption, and _decrease deployment costs_ as a small number of concentrators is required [12]. LPWAN uses proprietary modulation techniques that are derivatives of the Chirp Spread Spectrum (CSS) and operate in the sub-GHz bands. It allows end-nodes to communicate independently and asynchronously, similarly to an ALOHA-protocol. As a result, an LPWAN concentrator can receive data on the same channel from multiple IoT devices at the same time if the bit rates are different. This increases the capacity of nodes in a LPWAN. However, due to restrictions of the low duty cycle regulations in the unlicensed sub-GHz bands, LPWAN creates asymmetric situations where concentrators that are connected to a large number of IoT devices will be able to send downstream messages (i.e., messages arriving from the network servers to the IoT devices) less frequently to each node than a concentrator handling fewer IoT devices. Existing designs foresee both IoT devices and concentrators to transmit only 1% of the time to achieve low power consumption and high deployment numbers.