# MPH-M, AODV-M and DSR-M Performance Evaluation under Jamming Attacks
## 7 Conclusions  
In this paper, we have proposed a new mechanism for mitigation of jamming attacks, which is comprised of two phases: firstly the detection of the attack, and secondly the reaction of the network for adaptation of the routes avoiding those nodes nearby to the attack. For the detection, the method relies on an anomaly model, we have shown that the chosen variables of the model (CSMA retries, retransmissions, and energy) are suitable for building a jamming detector, where the metrics are combined under a majority voting rule, however some differences arise when the routing protocols are contrasted, MPH-M reaches higher efficiency in detection than DSR-M and AODV-M. The detection capabilities of the proposed method for MPH-M may stem from the behavior of the metrics, which jointly deliver a higher reliable decision since the deviations from the normal conditions are larger for the MPH-M protocol under jamming when compared to DSR-M and AODV-M. The analysis carried out in the rest of the paper show that in general MPH-M receives more benefits from the mitigation scheme than DSR-M and AODV-M. For instance, the node energy for MPH-M is 138.13% better than AODV-M and 126.07% better than DSR-M. The other metrics considered in this work also show a remarkably higher performance for MPH-M: delay end-to-end, overhead and retransmissions. For CSMA retries the differences are lower among the three protocols, but again MPH-M has a better performance. Furthermore, if we compare the results of the modified protocols with the performance of the original versions, we can observe that in general there is an increase in the performance, thus the network presents a mitigation of the jamming attack when the proposed method is integrated. In this work, we compare the performance of our routing protocol, MPH, with two protocols widely known in the literature of WSNs: AODV and DSR. We made some modifications to these protocols in order to get a better detection mechanism. However, at present, there are other protocols in sensor networks, such as Routing Protocol for Low Power and Lossy Networks [30] and the modification of OSLR (Optimized Link State Routing) protocol made by [31], that we are going to work in the near future. Figure 19: Resilience results for AODV, DSR and MPH and for AODV-M, DSR-M and MPH-M.  
RPL is a proactive distance-vector routing protocol. This protocol is energy efficient in multipoint-to-point traffic scenarios, however, it presents inefficient performance in point-to-multipoint and point-to-point communications. Its main objective is the wireless networks of many nodes with limited resources and is managed by one or a few node collectors. It will be interesting, as a future work, to compare our MPH protocol with RPL. In the modification of OSLR, the authors already made a performance analysis, but it is different to the performance analysis we made; therefore, it is not easy to compare. For example, the number of nodes is different, in our work we use 49 and they use 20; they use different topologies and our work is based on grid topology; they test with deceptive and random jamming and we use reactive jamming; they parametrize the jamming length, period and starting time and ours is fix; they limit their study mainly to MAC layer and we extend our study to MAC and Routing layer; the authors analyze the network performance in terms of communication and energy degradation and we use the energy consumption per node and the network as a whole, and we use more performance metrics such as retransmissions, overhead, affected nodes, and so on. Finally, we stress the network by increasing the traffic rate and the noise in the environment. [PERSON] developed the detection algorithm, built the simulator, prepared and executed the simulations, interpreted and analyzed the results and drafted the manuscript. [PERSON] supervised the research methodology and the approach of this work, he was a main contributor to the development of the MPH protocol and analyzed the anomaly model proposed in this paper.