A Multi-Layer Feedback System Approach to Resilient Connectivity of Remotely Deployed Mobile Internet of Things

Enabling the Internet of Things in remote environments without traditional communication infrastructure requires a multi-layer network architecture. Devices in the overlay network such as unmanned aerial vehicles (UAVs) are required to provide coverage to underlay devices as well as remain connected to other overlay devices to exploit device-to-device (D2D) communication. The coordination, planning, and design of such overlay networks constrained by the underlay devices is a challenging problem. Existing frameworks for placement of UAVs do not consider the lack of backhaul connectivity and the need for D2D communication. Furthermore, they ignore the dynamical aspects of connectivity in such networks which presents additional challenges. For instance, the connectivity of devices can be affected by changes in the network, e.g., the mobility of underlay devices or unavailability of overlay devices due to failure or adversarial attacks. To this end, this work proposes a feedback based adaptive, self-configurable, and resilient framework for the overlay network that cognitively adapts to the changes in the network to provide reliable connectivity between spatially dispersed smart devices. Results show that the proposed framework requires significantly lower number of aerial base stations to provide higher coverage and connectivity to remotely deployed mobile devices as compared to existing approaches.

[1]  Richard M. Murray,et al.  Flocking with obstacle avoidance: cooperation with limited communication in mobile networks , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[2]  P. Pardalos,et al.  The p-Median Problem , 2013 .

[3]  Mac Schwager,et al.  Robust Adaptive Coverage Control for Robotic Sensor Networks , 2017, IEEE Transactions on Control of Network Systems.

[4]  Mohamed-Slim Alouini,et al.  A Stochastic Geometry Model for Multi-Hop Highway Vehicular Communication , 2016, IEEE Transactions on Wireless Communications.

[5]  Quanyan Zhu,et al.  Optimizing mission critical data dissemination in massive IoT networks , 2017, 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[6]  Yunhui Liu,et al.  Formation control of quadrotor UAVs without linear velocity measurements , 2017, 2017 18th International Conference on Advanced Robotics (ICAR).

[7]  Ismail Güvenç,et al.  UAV-Enabled Intelligent Transportation Systems for the Smart City: Applications and Challenges , 2017, IEEE Communications Magazine.

[8]  Kandeepan Sithamparanathan,et al.  Optimal LAP Altitude for Maximum Coverage , 2014, IEEE Wireless Communications Letters.

[9]  Walid Saad,et al.  Optimal transport theory for power-efficient deployment of unmanned aerial vehicles , 2016, 2016 IEEE International Conference on Communications (ICC).

[10]  Igor Bisio,et al.  Satellite Communications Supporting Internet of Remote Things , 2016, IEEE Internet of Things Journal.

[11]  Walid Saad,et al.  Efficient Deployment of Multiple Unmanned Aerial Vehicles for Optimal Wireless Coverage , 2016, IEEE Communications Letters.

[12]  S. P. Lloyd,et al.  Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.

[13]  Yaonan Wang,et al.  Collision-free consensus in multi-agent networks: A monotone systems perspective , 2016, Autom..

[14]  Quanyan Zhu,et al.  Cognitive Connectivity Resilience in Multi-Layer Remotely Deployed Mobile Internet of Things , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.

[15]  Mohammed Anbar,et al.  Internet of Things (IoT) communication protocols: Review , 2017, 2017 8th International Conference on Information Technology (ICIT).

[16]  Quanyan Zhu,et al.  Secure and reconfigurable network design for critical information dissemination in the Internet of battlefield things (IoBT) , 2017, 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[17]  Rui Zhang,et al.  Wireless communications with unmanned aerial vehicles: opportunities and challenges , 2016, IEEE Communications Magazine.

[18]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[19]  M. Zeeshan Shakir,et al.  A Novel Airborne Self-Organising Architecture for 5G+ Networks , 2017, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall).

[20]  Walid Saad,et al.  Mobile Unmanned Aerial Vehicles (UAVs) for Energy-Efficient Internet of Things Communications , 2017, IEEE Transactions on Wireless Communications.

[21]  Sherali Zeadally,et al.  Intelligent Device-to-Device Communication in the Internet of Things , 2016, IEEE Systems Journal.

[22]  Abbas Jamalipour,et al.  Modeling air-to-ground path loss for low altitude platforms in urban environments , 2014, 2014 IEEE Global Communications Conference.

[23]  Halim Yanikomeroglu,et al.  Backhaul-aware robust 3D drone placement in 5G+ wireless networks , 2017, 2017 IEEE International Conference on Communications Workshops (ICC Workshops).

[24]  John A. Stankovic,et al.  Research Directions for the Internet of Things , 2014, IEEE Internet of Things Journal.

[25]  Mohamed-Slim Alouini,et al.  Modeling Inter-Vehicle Communication in Multi-Lane Highways: A Stochastic Geometry Approach , 2015, 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall).

[26]  Quanyan Zhu,et al.  On the Secure and Reconfigurable Multi-Layer Network Design for Critical Information Dissemination in the Internet of Battlefield Things (IoBT) , 2018, IEEE Transactions on Wireless Communications.

[27]  Mohsen Guizani,et al.  Drone-Assisted Public Safety Networks: The Security Aspect , 2017, IEEE Communications Magazine.

[28]  Wael Guibène,et al.  An evaluation of low power wide area network technologies for the Internet of Things , 2016, 2016 International Wireless Communications and Mobile Computing Conference (IWCMC).

[29]  Halim Yanikomeroglu,et al.  Efficient 3-D placement of an aerial base station in next generation cellular networks , 2016, 2016 IEEE International Conference on Communications (ICC).

[30]  Quanyan Zhu,et al.  Resilient and decentralized control of multi-level cooperative mobile networks to maintain connectivity under adversarial environment , 2015, 2016 IEEE 55th Conference on Decision and Control (CDC).

[31]  Mazen O. Hasna,et al.  Association of networked flying platforms with small cells for network centric 5G+ C-RAN , 2017, 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[32]  Rui Zhang,et al.  Placement Optimization of UAV-Mounted Mobile Base Stations , 2016, IEEE Communications Letters.

[33]  Jianping Pan,et al.  Disaster Management and Response for Modern Cellular Networks Using Flow-Based Multi-Hop Device-to-Device Communications , 2016, 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall).

[34]  Mazen O. Hasna,et al.  A Distributed Approach for Networked Flying Platform Association with Small Cells in 5G+ Networks , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.