# Clustering-Based Energy-Efficient Self-Healing Strategy for WSNs under Jamming Attacks
## 2 Related Work
Using the packet data rate (PDR), round trip time (RTT), packet loss ratio, and RSS, the hyperbolic spider monkey optimization (HSMO) algorithm detects and eliminates the jammer node. However, the work does not consider a specific jamming strategy or model the jammer node. Therefore, the PHY parameters or channel models are inexistent owing to the focus of the work. Additionally, this work assumes that the edge and sub-edge nodes use a different frequency channel to communicate, which is no minor requirement. The cooperation scheme in the WSNs context is used primarily to improve energy efficiency [34; 35]. Cooperation schemes are based on the use of multi-hop communications. The evolution of these schemes has demonstrated the benefits of the selection of relays, which required considering the resources available by the nodes. In [34], the authors proposed a cooperative scheme in which the relays activate the receiving circuitry based on switching probability. Then, the ON-OFF probabilities were adjusted to reduce power consumption and maximize the effective information transmitted. This proposal was improved in [35] by considering the use of multiple antennas in the sensor nodes, as well as power control. However, neither proposal considers how to keep the network running during a jamming attack. On the other hand, the relationship that has been established today between WSNs and unmanned aerial vehicles (UAVs) is undeniable [36; 37; 38]. In [36], a comprehensive review is provided of the main applications of WSNs, UAVs, and monitoring technologies. The mobile sink-based solutions have triggered the investigation of UAVs as data mules. In [37], the authors addressed the problem of optimizing the UAV path through all the sensor nodes distributed over a large agricultural area to reduce its flight time and increase the nodes' lifetime. In addition, the authors proposed an efficient algorithm for discovering and reconfiguring the activation time of the nodes. Meanwhile, in [38], an energy-efficient and fast data collection scheme was designed in UAV-aided WSNs for hilly areas with the help of a UAV as a data mule. The authors applied a modified tabu search algorithm to optimize the UAV position to collect data from a group of nodes and the traveling salesman problem to achieve fast data collection. We consider the crucial role of UAVs in smart outdoor applications such as agriculture, transportation, health, and public safety. Therefore, the parameters determined in this work consider the possibility of using UAVs to perform determined functions. However, we wish to emphasize that the assistance of WSNs by UAVs does not guarantee the operation of the network against jamming attacks, as shown in [39; 40]. In [39], the authors propose an anti-jamming scheme for collecting data in the presence of jamming attacks. A clustering approach is used to minimize the points that UAVs visit and guarantee that the message transmitted from the cluster heads reaches the UAV. The probabilistic channel model presented and the constraints imposed on the UAV and devices suggest that the jamming attack can be a constant type. The results show that the proposed approach surpasses the optimal solution, min k-means and genetic algorithm, and genetic algorithm without clustering. Nevertheless, the work does not consider the link communication between the CH and the clustered nodes. Therefore, clustering strategies such as cooperation or power allocation are not considered. Moreover, the energy efficiency of the information transmitted is not part of the study. On the other hand, in [40], a similar approach to improve the data collection and trajectory of the UAV on the network is employed. Jamming is considered, but from the defensive side as a countermeasure. Meanwhile, from the attacker's side, only eavesdropping is used. Consequently, the jamming attacks in network communications are not part of the study.