Various security threats and corresponding countermeasures has been a major concern of the maintainers of multi-hop wireless networks (MHWNs) in recent years. This is accompanied with background advances in wireless link bandwidth and rapid growth deployment of wireless network. As one of the main security threats MHWN faces, jamming attack has attracted much attention since it is easy to launch and can cause severe damages to the network. Accurate jammer localization plays an essential role in applying various anti-jamming countermeasures and it has been a hot topic in recent years. This survey overviews the major recent works done in the field of jammer localization for MHWN. The major contribution of this paper is to present all the typical jammer localization schemes in a single literature along with comprehensive performance comparison by simulation with respect to time complexity, location accuracy, and communication overhead in various MHWN deployment environments. Besides, directions for future research are outlined. We hope this survey can provide insight into different research directions to improve jammer localization accuracy for future developments.

Unmanned Aerial Vehicles (UAVs) are considered a promising solution for carrying communications and computational facilities to increase the flexibility of cloud-to-thing continuum, where short-range and long-range wireless links are adopted to connect mobile devices to the fog node and the fog node to the remote data center, respectively. Most existing UAV-involved resource allocation algorithms focus mainly on the radio resource allocation problem, and much less attention has been paid to the allocation of computational resources. Moreover, the dynamic arrival of tasks and the queueing delay at each computation entity is usually neglected. In this paper, a joint optimization problem is formulated that takes the weighted sum of energy consumption and delay experienced by tasks as the objective function. Processing frequencies and transmission powers of mobile devices and the fog node are the decision variables in the problem. To solve this problem, three decision-making algorithms are presented. The first one is used to decide the UAV’s position. The processing frequency, transmission power, and task assignment results at mobile devices are determined by the second algorithm. The last one is adopted by the fog node to optimize its processing frequency and transmission power. A series of simulation experiments are conducted to evaluate the effectiveness of the proposed algorithms. Compared with the random task assignment scheme with fixed parameters, the combination of our three algorithms always perform much better for a wide range of parameter settings.

Multihop Wireless Networks (MHWNs) can be easily attacked by the jammer for their shared nature and open access to the wireless medium. The jamming attack may prevent the normal communication through occupying the same wireless channel of legal nodes. It is critical to locate the jammer accurately, which may provide necessary message for the implementation of antijamming mechanisms. However, current range-free methods are sensitive to the distribution of nodes and parameters of the jammer. In order to improve the localization accuracy, this article proposes a jammer localization method based on Gravitational Search Algorithm (GSA), which is a heuristic optimization evolutionary algorithm based on Newton’s law of universal gravitation and mass interactions. At first, the initial particles are selected randomly from the jammed area. Then, the fitness function is designed based on range-free method. At each iteration, the mass and position of the particles are updated. Finally, the position of particle with the maximum mass is considered as the estimated jammer’s position. A series of simulations are conducted to evaluate our proposed algorithms and the simulation results show that the GSA-based localization algorithm outperforms many state-of-the-art algorithms.

Multi‐hop wireless network (MHWN) can be easily attacked by jammers for its shared nature and open access to the wireless medium. Jamming attack may pose a significant threat to MHWN by occupying wireless channel used by legitimate users. A number of anti‐jamming countermeasures have been put forward to eliminate the impact of communication disruption caused by jamming attacks. As an important building block of anti‐jamming strategies, jammer localisation attracts much attention in recent years and several algorithms have been presented. However, how to locate multiple co‐existing jammers receives little attention, and the efficiency and accuracy of the existing methods are still unsatisfactory. In this study, the authors focus on the localisation of sequential opening multi‐jammers and put forward the multi‐jammers localisation algorithm based on time series analysis (MLTSA) algorithm. The main process of MLTSA consists of four steps: detection of jamming attack, collection of received jamming signal strength, anomaly detection and separation of nodes, the existence determination and localisation of jammers. Finally, a series of simulation experiments are conducted to evaluate the correctness and effectiveness of the proposed algorithm. Experimental results show that the localisation accuracies of MLTSA are better than those of several state‐of‐the‐art solutions.