# Predicting Topology Propagation Messages in Mobile Ad Hoc Networks: The Value of History
## 2 Related Work
Particularly, the OLSRp protocol was proposed to eliminate redundant control information, and thus, reduce CPU and energy consumption in MANETs. This prediction mechanism is based on the assumption that the last TP message sent by a node will probably be repeated during the next round of information delivery. Such a proposal has shown positive potential results in a simplified communication scenario, but its real capabilities need to be determined through more complex scenarios and real scenarios that consider the diversity of variables affecting the TP message exchange in MANETs. Concerning end-to-end/link quality prediction, there have been several authors that address this topic. Typically, quality tracking [16; 17; 18] has been applied to select links with higher quality, and thus maximize the message delivery rate and minimize traffic congestion. Recently, time-series analysis has been considered to estimate link quality (LQ) and end-to-end quality (EtEQ) in the routing layer, involving real-world wireless mesh community networks. For instance, [PERSON] et al. [19; 20; 21; 22] shown that time-series analysis can be used to improve the performance of the routing protocol, by providing information that allows making appropriate and timely decisions. This contributes to maximize the message delivery rate and minimize traffic congestion at both levels (i.e., LQ and EtEQ) with a small average mean absolute error. Additionally, [PERSON] et al. [23] identified several problems and limitations of the predictive models used in [20], through the use of batch machine learning algorithms. Similarly, [PERSON] and [PERSON] [24] provide an exhaustive study of the existingprediction methods to estimate link quality, considering online learning algorithms that increasingly update the network model. Concerning energy consumption, [PERSON] et al. (2020) proposed a new metric that evaluates the capacity of batteries to estimate the future lifetime of nodes in order to determine which nodes can be part of an active route. [PERSON] et al. (2020) dealt with mobile prediction to extend the lifetime of nodes in an energy-efficient way. Finally, [PERSON] et al. (2020) focused on managing the limited battery capacity of nodes in a wireless sensor networks. Such a work reviewed several techniques to address this issue, including some of them that applies a kind of prediction. Recently, cooperative network synchronization and cooperative network localization are becoming increasingly popular in wireless networks, as a way of improving the accuracy of clock synchronization and location information. For instance, [PERSON] et al. (2020) developed a framework that analyses the performance limits of cooperative network synchronization, as a way to address the drawbacks that introduce traditional synchronization techniques in wireless networks. [PERSON] et al. (2020) provided an overview of cooperative localization algorithms and applied them to ultrawide bandwidth wireless networks. Finally, [PERSON] et al. (2020) focused on passive localization of asynchronous receivers in wireless sensor networks. The history-based prediction mechanism proposed in this article can be easily adapted to fit with these techniques, and thus help predict synchronization and location information.