Optimizing communication and computation for multi-UAV information gathering applications

Typical mobile agent networks, such as multi-UAV systems, are constrained by limited resources: energy, computing power, memory and communication bandwidth. In particular, limited energy affects system performance directly, such as system lifetime. Moreover, it has been demonstrated experimentally in the wireless sensor network literature that the total energy consumption is often dominated by the communication cost, i.e. the computational and the sensing energy are small compared to the communication energy consumption. For this reason, the lifetime of the network can be extended significantly by minimizing the communication distance as well as the amount of communication data, at the expense of increasing computational cost. In this work, we aim at attaining an optimal trade-off between the communication and the computational energy. Specifically, we propose a mixed-integer optimization formulation for a multihop hierarchical clustering-based self-organizing UAV network incorporating data aggregation, to obtain an energy-efficient information routing scheme. The proposed framework is tested on two applications, namely target tracking and area mapping. Based on simulation results, our method can significantly save energy compared to a baseline strategy, where there is no data aggregation and clustering scheme

Architecture and Methods for Innovative Heterogeneous Wireless Sensor Network Applications

Nowadays wireless sensor netwoks (WSN) technology, wireless communications and digital electronics have made it realistic to produce a large scale miniaturized devices integrating sensing, processing and communication capabilities. The focus of this paper is to present an innovative mobile platform for heterogeneous sensor networks, combined with adaptive methods to optimize the communication architecture for novel potential applications in multimedia and entertainment. In fact, in the near future, some of the applications foreseen for WSNs will employ multi-platform systems with a high number of different devices, which may be completely different in nature, size, computational and energy capabilities, etc. Nowadays, in addition, data collection could be performed by UAV platforms which can be a sink for ground sensors layer, acting essentially as a mobile gateway. In order to maximize the system performances and the network lifespan, the authors propose a recently developed hybrid technique based on evolutionary algorithms. The goal of this procedure is to optimize the communication energy consumption in WSN by selecting the optimal multi-hop routing schemes, with a suitable hybridization of different routing criteria. The proposed approach can be potentially extended and applied to ongoing research projects focused on UAV-based sensing with WSN augmentation and real-time processing for immersive media experiences

3D UAV Trajectory and Communication Design for Simultaneous Uplink and Downlink Transmission

In this paper, we investigate the unmanned aerial vehicle (UAV)-Aided simultaneous uplink and downlink transmission networks, where one UAV acting as a disseminator is connected to multiple access points (AP), and the other UAV acting as a base station (BS) collects data from numerous sensor nodes (SNs). The goal of this paper is to maximize the system throughput by jointly optimizing the 3D UAV trajectory, communication scheduling, and UAV-AP/SN transmit power. We first consider a special case where the UAV-BS and UAV-AP trajectories are pre-determined. Although the resulting problem is an integer and non-convex optimization problem, a globally optimal solution is obtained by applying the polyblock outer approximation (POA) method based on the problem's hidden monotonic structure. Subsequently, for the general case considering the 3D UAV trajectory optimization, an efficient iterative algorithm is proposed to alternately optimize the divided sub-problems based on the successive convex approximation (SCA) technique. Numerical results demonstrate that the proposed design is able to achieve significant system throughput gain over the benchmarks. In addition, the SCA-based method can achieve nearly the same performance as the POA-based method with much lower computational complexity