Design and Implementation of Adaptive MAC Framework for UAV Ad Hoc Networks

Due to the agility and low-cost, small Unmanned Aerial Vehicle (UAV) has recently captured great attention of academia and industry. However, since the capability limitation of single device, an ad hoc network formed by small UAVs is very promising. But compared to ordinary ad hoc networks, because of the unmanned characteristic and the diversity of missions, the protocols of UAV ad hoc networks require higher adaptive ability, i.e., the MAC protocol. In this paper, first, we verify that different MAC protocols have respective performance advantage under various network scenarios during the UAV reconnaissance mission. Then, we propose an adaptive MAC framework which allows multiple MAC protocols to switch mutually based on some kind of information you want. After that, in order to demonstrate this framework we design an adaptive MAC protocol called CT-MAC following the proposed framework. CT-MAC allows UAVs to switch between CSMA and TDMA based on their own positions when performing reconnaissance mission. Finally, we implement CT-MAC with Raspberry Pi and MDS Radio. The experiment results show that CT-MAC can always keep desirable performance compared to single MAC protocol through the fast and transparent MAC switching and the proposed adaptive MAC framework is feasible and effective.

[1]  Ilker Bekmezci,et al.  Flying Ad-Hoc Networks (FANETs): A survey , 2013, Ad Hoc Networks.

[2]  Saad Walid,et al.  Mobile Internet of Things: Can UAVs Provide an Energy-Efficient Mobile Architecture? , 2016 .

[3]  Dipankar Raychaudhuri,et al.  Global Control Plane Architecture for Cognitive Radio Networks , 2007, 2007 IEEE International Conference on Communications.

[4]  T. Weingart,et al.  MultiMAC - an adaptive MAC framework for dynamic radio networking , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[5]  Long To,et al.  Radar Cross Section measurements of small Unmanned Air Vehicle Systems in non-cooperative field environments , 2009, 2009 3rd European Conference on Antennas and Propagation.

[6]  Evsen Yanmaz,et al.  Survey on Unmanned Aerial Vehicle Networks for Civil Applications: A Communications Viewpoint , 2016, IEEE Communications Surveys & Tutorials.

[7]  Ian F. Akyildiz,et al.  BorderSense: Border patrol through advanced wireless sensor networks , 2011, Ad Hoc Networks.

[8]  Lei Tian,et al.  Development of a low-cost agricultural remote sensing system based on an autonomous unmanned aerial vehicle (UAV) , 2011 .

[9]  Injong Rhee,et al.  Z-MAC: a hybrid MAC for wireless sensor networks , 2005, SenSys '05.

[10]  Injong Rhee,et al.  DRAND: Distributed Randomized TDMA Scheduling for Wireless Ad Hoc Networks , 2006, IEEE Transactions on Mobile Computing.

[11]  P. B. Sujit,et al.  Search Strategies for Multiple UAV Search and Destroy Missions , 2011, J. Intell. Robotic Syst..

[12]  András Faragó,et al.  Meta-MAC protocols: automatic combination of MAC protocols to optimize performance for unknown conditions , 2000, IEEE Journal on Selected Areas in Communications.

[13]  Dipankar Raychaudhuri,et al.  MAC protocol adaptation in cognitive radio networks , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[14]  Erik G. Ström,et al.  Delay and interference comparison of CSMA and self-organizing TDMA when used in VANETs , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.

[15]  Carlos Eduardo Pereira,et al.  Cooperation among Wirelessly Connected Static and Mobile Sensor Nodes for Surveillance Applications , 2013, Sensors.

[16]  Mehdi Berenjkoub,et al.  An adaptive MAC protocol for wireless LANs , 2014, Journal of Communications and Networks.

[17]  Xiaolong Li,et al.  LA-MAC: A Load Adaptive MAC Protocol for MANETs , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.