# Multi-Agent Modeling and Jamming-Aware Routing Protocols for Movable-Jammer-Affected WSNs
## 2 Background and Related Work
### Jamming Attacks in WSNs  
Jamming attacks, refer to the intentional interference of the wireless communication channel in a WSN, which can disrupt the transmission of data between the nodes. Jamming attack is a major security threat to WSNs, which can significantly affect their reliability and performance. A number of studies have investigated the impact of jamming attacks on WSNs and proposed various solutions to mitigate their effects. Several studies have proposed different types of jamming attacks, such as constant jamming [21], deceptive jamming [22], random jamming [20], and reactive jamming [23], and evaluated their impact on WSN reliability. For instance, in [24; 25], the authors focus on the attacker's strategy. In the former paper, the authors optimize the best relay amplification matrix of WSNs and concluded that the network performance is influenced by the geometric shape of the nodes. In the latter paper, the authors consider the wireless relay network under a jamming attack, where the node's receiving power is limited. The author proposes a strategy to calculate the diagonal relay amplification matrix to minimize the mean square error between the transmitted signal and the received signal. Other studies analyze the detection and location of the jammer from the defender's perspective, providing the possibility of actively eliminating the jammer. [PERSON] et al. [26] introduced the JAM protocol, which detects and maps jammed areas in wireless sensor networks, treating the disturbed area as a single entity, instead of a set of disconnected links and congested nodes. The protocol uses unperturbed nodes around the disturbed node to collect and disseminate information about the affected area and employs a gradient-based algorithm to calculate the boundary of the disturbed region. [PERSON] et al. [27] proposed a method to localize single or multiple jammers by exploiting the neighbor changes caused by jamming. The authors analyzed the impact of different types of interference on the neighbor discovery process and neighbor table maintenance process and proposed an algorithm to estimate the jammer's position based on the neighbor change frequency and directional information. They also designed a distributed cooperation mechanism that allows nodes in the network to share and fuse their respective observed neighbor change information, thereby improving the positioning accuracy. [PERSON] et al. [28] systematically analyzed the impact of multiple overlapping or non-overlapping interference regions on network topology and connectivity, proposing a framework that can divide the network into different clusters and estimate multiple jammer positions. The framework utilizes two techniques: partitioning clusters based on minimum spanning trees (MST) and estimating locations based on maximum likelihood (ML). The framework can efficiently handle multiple overlapping or non-overlapping interference regions with low communication overhead and computational complexity. Another form of defense is to improve the network's robustness. [PERSON] et al. [29] proposed a cluster-based cooperative jamming (CB-CJ) scheme for improving security in wireless multi-hop networks. This scheme uses friendly nodes in the network as jammers to send artificial interference signals to enemy eavesdroppers, thereby reducing their signal-to-noise ratio and improving the confidentiality rate between legitimate communicators. This scheme adopts a method of selecting the optimal relay and jammer on demand and considers different security requirements and power constraints. [PERSON] et al. [30] analyzed various Denial-of-Service (DoS) attacks against sensor networks and their defense mechanisms. They pointed out that sensor networks are more vulnerable to DoS attacks than traditional networks due to their resource-constrained, distributed, and self-organizing characteristics. Using two examples of efficient sensor network protocols, they showed that designing with security in mind is the best way to ensure network availability.