# Analysis of the Most Relevant Factors for Routing in Internet of Space Things Networks
## 1 Introduction
The performance of a MANET is highly dependent on factors such as the routing strategy followed, node mobility, energy constraints, radio channel characteristics, and multiple access mechanisms and physical layer used in the transceiver. Of these factors, as explored in [30; 31; 32], the routing strategy is of the utmost importance in MANET deployments, and its performance is closely related to the particular characteristics of the deployment scenario. For instance, a routing protocol for flying ad hoc networks (FANETs) where the nodes are drones should consider energy limitations [33; 34; 35; 36]. In contrast, in vehicular ad hoc networks (VANETs) where the nodes are cars, energy limitations are not necessarily a critical issue [37; 38; 39]. Furthermore, node mobility also has an impact on the routing strategy performance. For example, in [40], the authors compared the performance offered by the two main routing approaches in MANET, i.e., reactive and proactive routing, for different node speeds in smart city environments. They found that for this scenario, there are differences in the performance offered by proactive and reactive routing depending on the mobility (high or low) of the nodes. As previously mentioned, one of the main paradigms proposed for IoST networking involves the formation of ad hoc inter-satellite networks, [41; 42]. Previously, [PERSON]. [43; 44] explored the use of MANET protocols for the formation of ad hoc IoT networks. Although these works have shown the feasibility of using MANET protocols to form IoST networks, they did not study the differences in the performance offered by the main routing strategies in MANETs, namely reactive and proactive routing. Studying these differences is important for the development of new routing protocols for emerging ad hoc networking scenarios such as ad hoc IoST networking. This is because most MANET (including VANET and FANET) protocols have been developed considering as a starting point the adoption of: a reactive routing approach [45; 46]; a proactive routing approach [30; 47]; or some combination of both routing approaches (e.g., see [48]). Thus, by studying the performance differences and constraints observed and when a proactive (of which optimized link state routing (OLSR) is the base example) or a reactive (of which ad hoc on-demand distance vector (AODV) is the base example) routing approach is used in an ad hoc IoST network, a performance baseline can be provided for the design and development of new ad hoc IoT protocols. To the best of our knowledge, this study hasnot been previously addressed in the literature. Thus, two of the main contributions of our paper are: performing a comparative analysis of proactive and reactive routing in ad hoc IoT networking; and the identification of critical factors that affect the performance of the routing task in ad hoc IoT networks. Among the parameters commonly considered when evaluating the performance of routing algorithms are those related to node density and the freshness of control information [49]. These parameters can affect the routing protocol performance in different ways depending on the particular routing strategy adopted (e.g., proactive, reactive, or hybrid). For instance, work done in [50] shows that tuning the freshness control parameters of the base proactive routing protocol, OLSR, improves its routing performance in VANET scenarios compared to the baseline configuration set. In this sense, different configuration sets and the interaction between parameters make challenging the task of identifying, isolating, and analyzing the impact of each parameter on the performance of different routing strategies for ad hoc IoT networking. To be able to study routing performance in ad hoc IoT networks, a proper simulation testbed must be developed to recreate networking conditions found in space scenarios. Additionally, an adequate analysis methodology must be used to identify the critical factors for route discovery and maintenance in ad hoc IoT networks.