An Efficient Mobility Model for Improving Transmissions in Multi-UAVs Enabled WSNs

Abstract

Multi-Unmanned Aerial Vehicle (UAV) enabled Wireless Sensor Networks (WSNs) provide a wide range of applications, covering civilian and military expeditions along with geographical navigation, control, and reconnaissance. The coordinated networks formed between the UAVs and the WSNs help in enhancing the issues related to quality as well as coverage. The overall coverage issues result in starvation as an effect of long waiting time for the nodes, while forwarding the traffic. The coverage problem can be resolved by an intelligent choice of UAV way-points. Therefore, a specialized UAV mobility model is required which takes into account the topological structure as well as the importance of strategic locations to fix UAV way-points and decide the data transmission paradigm. To resolve this problem, a novel mobility model is proposed, which takes into account the attraction factor for setting up the way-points for UAV movements. The model is capable of deciding between the locations which result in more coverage, increased throughput with lesser number of UAVs employed, as justified by the simulation results and comparative evaluations.

Advances in Drone Communications, State-of-the-Art and Architectures

“…One such approach is discussed by Mohd. Abuzar Sayeed and Rajesh Kumar [3]. In their approach, the authors discussed the coverage issues in WSN-enabled UAV systems and argued that multiple UAVs can resolve the coverage problem through an efficient selection of the waypoints.…”

RSSGM: Recurrent Self-Similar Gauss–Markov Mobility Model

“…Several other studies have proposed mobility models for Unmanned Aerial Vehicles (UAVs) [31][32][33][34][35]. Li et al [31] took advantage of the temporal dependency of an Unmanned Aerial Vehicle (UAV).…”

“…The same authors extended their work to improve the coverage rate in reconnaissance operations by limiting the overlapping among UAVs and avoiding any simultaneous visits to the same zone [34]. Sayeed et al in [35] exploited the transmission density of nodes in a wireless sensor network to give a mobility model in which the UAV traversals are determined according to dynamic changes in the underlying network topology.…”

Efficient Deployment with Throughput Maximization for UAVs Communication Networks

“…Sayeed and Kumar [ 35 ] proposed an intelligent selection of waypoints based on attraction factor, for capacity enhancement in multi-UAV guided WSNs. The transmission density-based attraction factor is calculated to achieve maximum throughput and coverage with minimized aerial node deployment.…”