**2. Multi-hop strategies**

Using the physical layer of LoRa, the payload of the data packet can be used to implement different protocols used by mobile wireless sensor networks (WMSNs). This allows the approach of tree or mesh topologies using these protocols. Keep in mind that, in the case of this chapter, mobile nodes can act as repeaters and end nodes in all cases and that they can appear and disappear from the network at any time. For this reason, the most appropriate protocols are the proactive ones that require the routing table to be constantly updated. Another important dilemma, in these cases, is the parameter used to choose the appropriate route to the destination. On the one hand, minimizing the Time on Air (ToA) of the data packets may be a priority to minimize system latency, or depending on the type of data, the rate of packets received can be used. As is known, in the case of LoRa, several communication parameters can be varied such as the bit rate (BR), the spreading factor (SF), or the transmitted power (Pt). The main challenge is that the system adjusts to the requirements of latency, reliability, or QoS minimizing the energy consumption of the different nodes. For this, there are several works developed on different technologies.

**Figure 1** shows an example case of the compromise between the different priorities in a multi-hop topology in the case of LoRa technology. If the end node has direct access to the gateway in both cases if the RSSI route is taken as a parameter to choose the route, in case a) a better response will be obtained, and that route would *Hybrid Architectures to Improve Coverage in Remote Areas and Incorporate Long-Range LPWAN… DOI: http://dx.doi.org/10.5772/intechopen.113328*

**Figure 1.** *Two communication cases: a) using multi-hop, b) direct communication with the gateway.*

be chosen. The consequence is that it is not necessary to increase the transmission power or the SF achieving a better BR. However, the total ToA would be higher due to the processing of the intermediate nodes, and in addition, they are forced to consume more energy. In case b), it would probably be necessary to increase the transmit power or increase the SF to obtain an adequate Packet Error Rate (PER), although the TOF of the packets would be lower. It is, therefore, important to determine the priority of the parameters to be minimized when choosing the appropriate route depending on the type of data packets, the required latency, or the need to reduce consumption. For this reason, the knowledge of the nature of the entire network is needed and not just find the nearest neighbor. This knowledge must be constantly updated due to the presence of mobile nodes, which impose proactive protocols [3]. In [4], an assessment of the energy efficiency of the network is highlighted according to the network topology and the number of hops. For example, for a given LoRa transceiver, measurements of the energy consumed in a meshed network, such as the one shown in **Figure 2**, are obtained as a function of the range, the number of hops, and the distance between the repeater nodes. Where D is the end-to-end distance (i.e., between the sender and sink node), and d is the distance between each intermediate node.

#### **2.1 Routing protocols**

There are multiple routing protocols for the different mobile node network topologies deployed [5]. When selecting one of them for the case of LoRa technology, it is important to consider whether the rapid discovery of new routes or the number of total nodes in the network is critical. In the case of reactive protocols, such as Ad-hoc On-Demand Distance Vector Routing [6], the network is not saturated with route update packets, although in the case of the incorporation of mobile nodes, the use of

these protocols may not be the most appropriate, depending on the time they remain in the network. Others are based on clustering of nodes within the total network (clustering) for large networks, as is the case of LEACH [7], where all nodes can become the central node of a cluster with equal probability. It is a proactive protocol that can be mono-hop or multi-hop [8], both based on extending the life of the network. In the case of the mobile sink-based routing protocol (MSRP) [9], the life of the network is extended avoiding the effect that the nodes closest to the sink of each cluster transmit a greater number of data packets than those that are farther away. For this, the sink nodes become mobile nodes that collect information from several clusters of the total network.

A mixed solution for these mobile node networks, also based on node zone grouping, is the zone routing protocol (ZRP) [10], which groups nodes according to the number of hops required. It is based on the coexistence of two protocols: one intrazone of proactive type that allows the constant search of the neighboring nodes and another inter-zone of reactive type, thus avoiding the saturation of the network.

For the case of LoRaWAN systems, also based on grouping LoRaWAN nodes around a cluster gateway is the proposal in [11]. This paper proposes a star of stars architecture, where devices or end nodes are connected to one or more gateways using the physical layer of LoRa. Each end device transmitted data to the cluster gateway, and the cluster gateway concatenated data from all the devices in an array and transmitted it to the central gateway. The authors demonstrate that a better energy efficiency is achieved in this star of stars topology.

There are many other applications such as those of large farms, the monitoring of seismic movements, or networks of marine buoys with sensors, where the mobility of the nodes is reduced, although there is still the fact that there are nodes that fall due to lack of battery or new ones are incorporated. This chapter focuses primarily on these cases.

#### *Hybrid Architectures to Improve Coverage in Remote Areas and Incorporate Long-Range LPWAN… DOI: http://dx.doi.org/10.5772/intechopen.113328*

Optimized Link State Routing protocol (OLSR) [12] is a proactive protocol that adapts link state routing for use in mobile ad-hoc networks. It allows multipoint relays. Each node selects a set of its single-hop neighbors to act as relays this information is shared between nodes making this protocol well-suited to large and dense networks with random and sporadic traffic. Destination-sequenced distance vector routing protocol (DSDV) [13] incorporates a sequence number to their routing tables and only refreshes the routing tables when receiving a DSDV packet with a higher sequence number than the node already has. This makes this protocol suitable for fixed node networks or with low-mobility nodes. Another reactive protocol used in these kinds of networks and maybe the most appropriate for the case above explained is Ad-hoc On-Demand Distance Vector Routing (AODV) [14], where each node initializes the routing discovering through a route request packet answered by all network neighbors and during the network recognition process a reverse path is created. Dynamic source routing (DSR) supposes an evolution of this protocol, where a list of hops from source to destination is collected in the RREQ packet as it travels through the network. This list allows implementing a total cost parameter of the route if information about SF, BR, and power required is added. This could be a solution for the problem described in **Figure 1**.

An IoT-oriented protocol is Pv6 routing protocol for low power and Lossy Networks (RPL) proposed by The IETF routing over low-power and Lossy Networks working group [15] RPL]. RPL is a gradient routing technique [16] that considers a WSN as a direct acyclic graph (DAG) rooted at the sink. The goal of RPL is to minimize the costs to reach any sink (from any sensor) by means of an objective function. This function can be defined in many ways adapting it to the operating scenario. Some authors [17] have developed a LoRa network RPL based. In this case, the optimal per-link spreading factor (SF) is one of the RPL objective functions (OF0) in order to compute rank, using the selected LoRa SF as routing metric.

Other approaches try to minimize the energy consumption of the LoRa nodes in a multi-hope network by minimizing the distance to the best neighbor taking into account the node state (busy or free). This is the energy-efficient multi-hop communication solution (e2McH) proposed in [18]. A more complex solution to improve coverage an energy consumption is presented in [19], using variable neighborhood search (VNS) and a minimum-cost spanning tree algorithm employing LoRaWAN end nodes and LoRa nodes as repeaters. In this work, the initial solution approach to find the multi-hop route to the final gateway is based in the PRIM algorithm [20] to find minimal spanning tree, storing the values of SF, BW, and Pt for each node. After that, variable neighborhood search (VNS) is employed to change node characteristics. The authors propose a stochastic algorithm that changes neighborhood structures to find local minimal solutions using a function objective based in the energy per useful bit transmitted. This proposal is designed for a three-level network: Level 1: gateway, level 2: repeaters, and level 3: sensors.

In summary, all these works seek the choice of appropriate protocols to minimize, mainly, the energy consumed, and the Time on Air (ToA) parameters of the packets transmitted along multi-hop networks. Some proposals are based on the location of the nodes, and others are based on the suitability of the configurable parameters of the LoRa nodes (SF, Pt, or BW). In certain use cases, it is also possible to extend the network coverage by combining different wireless communication technologies depending on the environmental conditions. The latter gives greater flexibility to the design of the final network adding more dynamic adaptability to the environment. In the next section, different use cases that develop this type of strategy are presented.
