# Deep Validation of Spatial Temporal Features of Synthetic Mobility Models
## 4 The Proposed Metric: The Mobile Neighbors Range
This metric is inaccurate in the cases in which it is lower or higher than the number of neighbors of all mobile nodes at a given time instant. This feature makes this metric inaccurate in reflecting exact changes in neighbor variability. * The spatial node distribution must be validated at a concrete time instant because it cannot show all location changes over a continuous period. * The speed decay problem only produces speed variation per time instant without taking into consideration the exact spatial locations of nodes. Table 5 illustrates the comparative study of all the aforementioned properties that have been validated in this paper. We conclude that all the mobility metrics show complementary features that are aimed at accurately assessing mobility flaws and this finally allows the model flaws that have the greatest effect on the performance of the whole mobile network to be revealed. Choosing the wrong mobility model can have undesirable consequences due to the appearance of many network flaws. ## 6 Mobility Metrics and Resources Management Overview

Among the different resources whose usage must be optimized in WSNs, we can highlight energy consumption and bandwidth. Energy consumption is a critical parameter in mobile networks, where long battery life is required to guarantee operation, maintaining the performance and the QoS over an acceptable period of time. Bandwidth is another critical resource to be considered as most of the IoT devices (nodes) operate in the ISM band, interfering with each other and affecting both the performance and the QoS. In this paper, we have revisited a metric that has been used already, and a novel one is proposed. Density wave phenomenon represents the average number of neighbors that belong to each node that fluctuates during operation. Nodes located in specific zones of the considered area can have many more neighbors than others, and this fact can be taken into account to optimize the overall performance and resource optimization. The average neighbor percentage metric describes the cumulative percentage of the total number of neighboring nodes. The appropriate usage of energy and bandwidth resources could improve the results of this metric. In the novel approach introduced in this paper, the proposed node neighbor range metric reveals the imbalance of mobility models during the simulation. This concept can be linked with node clustering, which impacts the overall network performance, and with a node's battery life. The metric can be combined with resource allocation optimization techniques in order to reveal the inefficiencies in energy and bandwidth usage. In the next paragraphs, we introduce techniques that can be adopted to improve the network performance based on the metric results. Several works have been developed aiming at the optimization of network performance. Among the ideas to improve resource usage in the proposed metric, we can consider the results in [37], the authors of which proposed a multi-cluster, multi-hop packet radio network architecture for wireless adaptive mobile information systems, allowing spatial reuse of time slots and codes and guaranteeing bandwidth for real time traffic. In [38], the authors describe a self-organizing, multihop, mobile radio network that relies on a code division access scheme for multimedia support, which offers spatial reuse of the frequencies,bandwidth sharing, and robustness against topological changes caused by node motion, a case considered in this paper. The authors in [39] propose heuristic routing schemes for clustered multihop, mobile wireless networks that improve packet delay and consider the effect of channel fading. There are interesting results obtained by other researchers that could be applied to the proposed approach in order to improve network efficiency. In [40], the problem of interest, energy-aware and physically aware coalition formation, and resource management in smart IoT applications is studied.