Abstract

With the new advancements in flight control and integrated circuit (IC) technology, unmanned aerial vehicles (UAVs) have been widely used in various applications. One of the typical application scenarios is data collection for large-scale and remote sensor devices in the Internet of things (IoT). However, due to the characteristics of massive connections, access collisions in the MAC layer lead to high power consumption for both sensor devices and UAVs, and low efficiency for the data collection. In this paper, a dynamic speed control algorithm for UAVs (DSC-UAV) is proposed to maximize the data collection efficiency, while alleviating the access congestion for the UAV-based base stations. With a cellular network considered for support of the communication between sensor devices and drones, the connection establishment process was analyzed and modeled in detail. In addition, the data collection efficiency is also defined and derived. Based on the analytical models, optimal speed under different sensor device densities is obtained and verified. UAVs can dynamically adjust the speed according to the sensor device density under their coverages to keep high data collection efficiency. Finally, simulation results are also conducted to verify the accuracy of the proposed analytical models and show that the DSC-UAV outperforms others with the highest data collection efficiency, while maintaining a high successful access probability, low average access delay, low block probability, and low collision probability.

Highlights

  • After several years’ development, Internet of Things (IoT) has been becoming ubiquitous in our daily lives

  • We model random access procedure (RAP) for collection establishments in terms of the successful access probability, Ps, the average access delay, Tdelay, and data collection efficiency, U

  • The DSC scheme of unmanned aerial vehicles (UAVs) for data collection is verified, which can adaptively adjust the speed according to different amounts of access attempts from sensor devices under the UAVs’

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Summary

Introduction

After several years’ development, Internet of Things (IoT) has been becoming ubiquitous in our daily lives. It is more efficient to use mobile balloons or satellites to provide temporary communication links for flexible mobility These solutions are always limited by an ultra-high cost, a complicated deployment, weather conditions, and so on. Fixed-wing UAVs can move with a high speed and can carry heavy payloads They can be equipped with a greater battery supply for a longer flight time. Data communication between sensor devices and UAVs can be supported by WLAN (IEEE 802.11 series), ZigBee, Bluetooth Low Energy (BLE), cellular networks, and so on. Due to the strong communication links and flexible mobility, UAVs can move toward potential ground users and collect the sensed data with a low power consumption, reducing the energy consumptions of sensor devices. A cost-effective and energy-efficient solution is urgently needed for UAVs to efficiently complete data collection from tens of thousands of sensor devices

Related Work
System Model
Definition of Data Collection Efficiency
Random Access Procedure under a Cellular Network
Modeling of Connection Establishments
Dynamic Speed Control for UAVs
Results from computer computing
Simulations
Conclusions

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