Medium Access Control for Unmanned Aerial Vehicle Based Mission Critical Wireless Sensor Networks in 3D Monitoring Networks

The Internet of Things (IoT), which consists of a large number of small low-cost devices, has become a leading solution for smart cities, smart agriculture, smart buildings, smart grids, e-healthcare, etc. Integrating unmanned aerial vehicles (UAVs) with IoT can result in an airborne UAV-based IoT (UIoT) system and facilitate various value-added services from sky to ground. In addition to wireless sensors, various kinds of IoT devices are connected in UIoT, making the network more heterogeneous. In a UIoT system, for achieving high throughput in an energy-efficient manner, it is crucial to design an efficient medium access control (MAC) protocol because the MAC layer is responsible for coordinating access among the IoT devices in the shared wireless medium. Thus, various MAC protocols with different objectives have been reported for UIoT. However, to the best of the authors’ knowledge, no survey had been performed so far that dedicatedly covers MAC protocols for UIoT. Hence, in this study, state-of-the-art MAC protocols for UIoT are investigated. First, the communication architecture and important design considerations of MAC protocols for UIoT are examined. Subsequently, different MAC protocols for UIoT are classified, reviewed, and discussed with regard to the main ideas, innovative features, advantages, limitations, application domains, and potential future improvements. The reviewed MAC protocols are qualitatively compared with regard to various operational characteristics and system parameters. Additionally, important open research issues and challenges with recommended solutions are summarized and discussed.

Section: Design Considerations For Mac Protocols Of Uiotmentioning

confidence: 99%

Medium Access Control Protocols for the Internet of Things Based on Unmanned Aerial Vehicles: A Comparative Survey

Khisa

Moh

2020

“…A hybrid protocol that partially adopts the beacon-based IEEE 802.15.4 MAC DR/CDT mechanisms is proposed in [ 34 ]. Recently, MAC for UAV-based mission-critical WSNs is proposed in [ 35 ]. The authors have focused on designing MAC for efficient communication and coordination between UAVs employed in a mission.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient and Fast MAC Protocol in UAV-Aided Wireless Sensor Networks for Time-Critical Applications

Poudel

Moh

2020

Unmanned aerial vehicle (UAV)-aided wireless sensor networks (UWSNs) can be effectively used for time-critical sensing applications. UAVs can be used to collect the sensed data from sensors and transfer them to a base station. The real-time transfer of data is highly desired in the time-critical applications. However, the medium access control (MAC) protocols designed for UWSNs so far are primarily focused on the efficient use of UAVs to collect data in the sensing areas. In this paper, we propose an energy-efficient and fast MAC (EF-MAC) protocol in UWSNs for time-critical sensing applications. EF-MAC adopts carrier sense multiple access (CSMA) for the registration of sensor nodes with a UAV and time division multiple access (TDMA) with variable slot time for the transmission of collected data. The UAV is equipped with two transceivers to minimize both energy consumption and delay in air-to-ground communication. The energy consumption and delay are formally analyzed and the performance of EF-MAC is evaluated via extensive simulation. The simulation results show that the proposed EF-MAC outperforms the conventional MAC protocols in terms of energy efficiency and communication delay.

“…UAVs help in performing time-sensitive tasks [ 8 , 9 , 10 , 11 ], monitoring emergencies [ 12 ], saving energy of WSN [ 13 , 14 , 15 , 16 , 17 ], extending the lifetime of WSN network [ 14 , 18 ], connecting separate nodes and networks [ 12 , 19 ], and enabling data aggregation [ 17 , 20 ]. Measures such as optimizing the flight routes [ 9 , 12 , 14 , 15 , 16 , 19 ] and locations [ 15 , 19 , 21 ] of UAVs, designing clustering mechanisms [ 17 , 18 , 22 ], media access control mechanisms [ 10 , 18 , 23 , 24 ], and sleeping schedules of WSN [ 14 ] and the like have been adopted to achieve these targets. Assisting in locating the WSN nodes [ 25 , 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

WSN-Assisted UAV Trajectory Adjustment for Pesticide Drift Control

Tuan

Yang

et al. 2020

Unmanned Aerial Vehicles (UAVs) have been widely applied for pesticide spraying as they have high efficiency and operational flexibility. However, the pesticide droplet drift caused by wind may decrease the pesticide spraying efficiency and pollute the environment. A precision spraying system based on an airborne meteorological monitoring platform on manned agricultural aircrafts is not adaptable for. So far, there is no better solution for controlling droplet drift outside the target area caused by wind, especially by wind gusts. In this regard, a UAV trajectory adjustment system based on Wireless Sensor Network (WSN) for pesticide drift control was proposed in this research. By collecting data from ground WSN, the UAV utilizes the wind speed and wind direction as inputs to autonomously adjust its trajectory for keeping droplet deposition in the target spraying area. Two optimized algorithms, namely deep reinforcement learning and particle swarm optimization, were applied to generate the newly modified flight route. At the same time, a simplified pesticide droplet drift model that includes wind speed and wind direction as parameters was developed and adopted to simulate and compute the drift distance of pesticide droplets. Moreover, an LSTM-based wind speed prediction model and a RNN-based wind direction prediction model were established, so as to address the problem of missing the latest wind data caused by communication latency or a lack of connection with the ground nodes. Finally, experiments were carried out to test the communication latency between UAV and ground WSN, and to evaluate the proposed scheme with embedded Raspberry Pi boards in UAV for feasibility verification. Results show that the WSN-assisted UAV trajectory adjustment system is capable of providing a better performance of on-target droplet deposition for real time pesticide spraying with UAV.