A Disaster Management Specific Mobility Model for Flying Ad-hoc Network

The extended Mobile Ad-hoc Network architecture is a paramount research domain due to a wide enhancement of smart phone and open source Unmanned Aerial Vehicle UAV technology. The novelty of the current work is to design a disaster aware mobility modeling for a Flying Ad-hoc network infrastructure, where the UAV group is considered as nodes of such ecosystem. This can perform a collaborative task of a message relay, where the mobility modeling under a "Post Disaster" is the main subject of interest, which is proposed with a multi-UAV prototype test bed. The impact of various parameters like UAV node attitude, geometric dilution precision of satellite, Global Positioning System visibility, and real life atmospheric upon the mobility model is analyzed. The results are mapped with the realistic disaster situation. A cluster based mobility model using the map oriented navigation of nodes is emulated with the prototype test bed.

[1]  Bernhard Rinner,et al.  Networked UAVs as aerial sensor network for disaster management applications , 2010, Elektrotech. Informationstechnik.

[2]  Yan Ma,et al.  The Analysis of Positioning Performance and DOP Value Based on BDS/GPS Integrated Navigation Satellite System , 2014 .

[3]  Ozgur Koray Sahingoz,et al.  Networking Models in Flying Ad-Hoc Networks (FANETs): Concepts and Challenges , 2014, J. Intell. Robotic Syst..

[4]  Eduardo Cerqueira,et al.  A Comparative Analysis of Beaconless Opportunistic Routing Protocols for Video Dissemination over Flying Ad-Hoc Networks , 2014, NEW2AN.

[5]  Arun K. Majumdar,et al.  Free-space Optical (FSO) Platforms: Unmanned Aerial Vehicle (UAV) and Mobile , 2015 .

[6]  David Hyunchul Shim,et al.  RRT-based path planning for fixed-wing UAVs with arrival time and approach direction constraints , 2014, 2014 International Conference on Unmanned Aircraft Systems (ICUAS).

[7]  Yogesh Kumar Dwivedi,et al.  Handbook of Research on Contemporary Theoretical Models in Information Systems , 2009 .

[8]  Maxim Likhachev,et al.  Path planning for non-circular micro aerial vehicles in constrained environments , 2013, 2013 IEEE International Conference on Robotics and Automation.

[9]  Vincent Roberge,et al.  Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time UAV Path Planning , 2013, IEEE Transactions on Industrial Informatics.

[10]  Evangelos Mitsakis,et al.  Combination of Macroscopic and Microscopic Transport Simulation Models: Use Case in Cyprus , 2014 .

[11]  H Shen,et al.  Fault tolerant attitude control for small unmanned aircraft systems equipped with an airflow sensor array , 2014, Bioinspiration & biomimetics.

[12]  Sajal K. Das,et al.  Traffic-Aware Dynamic Routing to Alleviate Congestion in Wireless Sensor Networks , 2011, IEEE Transactions on Parallel and Distributed Systems.

[13]  Muhannad Al-Omari,et al.  A Cascaded Approach for Quadrotor's Attitude Estimation , 2014 .

[14]  Bangnan Xu,et al.  Performance analysis of temporally ordered routing algorithm based on IEEE 802.11a , 2005, 2005 IEEE 61st Vehicular Technology Conference.

[15]  Bharat K. Bhargava,et al.  A simulation study of ad hoc networking of UAVs with opportunistic resource utilization networks , 2014, J. Netw. Comput. Appl..

[16]  Ian Postlethwaite,et al.  A Probabilistically Robust Path Planning Algorithm for UAVs Using Rapidly-Exploring Random Trees , 2013, J. Intell. Robotic Syst..

[17]  Yasser Albagory,et al.  Innovative Large Scale Wireless Sensor Network Architecture Using Satellites and High-Altitude Platforms , 2014 .

[18]  Mario Gerla,et al.  Survey of Routing Protocols in Vehicular Ad Hoc Networks , 2010 .

[19]  Nilmani Verma,et al.  Path planning for unmanned aerial vehicle based on genetic algorithm & artificial neural network in 3D , 2014, 2014 International Conference on Data Mining and Intelligent Computing (ICDMIC).

[20]  Md. Abu Naser Bikas,et al.  VANET Routing Protocols: Pros and Cons , 2011, ArXiv.

[21]  Sujoy Saha,et al.  Post Disaster Management Using Delay Tolerant Network , 2011 .

[22]  Philip E. Ross Open-source drones for fun and profit , 2014, IEEE Spectrum.

[23]  Daniel J. Pack,et al.  Optimal path planning of a target-following fixed-wing UAV using sequential decision processes , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[24]  Ilker Bekmezci,et al.  Connected multi UAV task planning for Flying Ad Hoc Networks , 2014, 2014 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom).

[25]  Simin Nadjm-Tehrani,et al.  Mobility Models for UAV Group Reconnaissance Applications , 2006, 2006 International Conference on Wireless and Mobile Communications (ICWMC'06).

[26]  Swarna Ravindra Babu,et al.  Investigation of GDOP for Precise user Position Computation with all Satellites in view and Optimum four Satellite Configurations , 2009 .

[27]  Xiao-lu Ren,et al.  Robust -Stability Controller Design for a Ducted Fan Unmanned Aerial Vehicle , 2014 .

[28]  Liang Sun,et al.  Distributed Probabilistic Search and Tracking of Agile Mobile Ground Targets Using a Network of Unmanned Aerial Vehicles , 2014, Human Behavior Understanding in Networked Sensing.

[29]  Michael A. Goodrich,et al.  Hierarchical Heuristic Search Using a Gaussian Mixture Model for UAV Coverage Planning , 2014, IEEE Transactions on Cybernetics.

[30]  V Krishnaveni,et al.  Dynamic Reliable Multipath Routing Protocol for MANET , 2014 .

[31]  Carol J. Friedland,et al.  High Resolution Imagery Collection Utilizing Unmanned Aerial Vehicles (UAVs) for Post-Disaster Studies , 2012 .

[32]  Paolo Gasti,et al.  Privacy-preserving distance computation and proximity testing on earth, done right , 2014, AsiaCCS.

[33]  Norbert Pfeifer,et al.  Accuracy analysis of direct georeferenced UAV images utilising low-cost navigation sensors , 2014 .

[34]  Md. Shahid Akhter,et al.  Power Aware Dynamic Source Routing Protocol To Increase Lifetime Of Mobile Ad Hoc Networks , 2013 .

[35]  Ana Maria Ramalho Correia Knowledge and Technology Adoption, Diffusion and Transfer: International Perspectives , 2013 .

[36]  Bahram Alidaee,et al.  Position Unmanned Aerial Vehicles in the Mobile Ad Hoc Network , 2014, J. Intell. Robotic Syst..

[37]  Kevin Curran,et al.  A Survey of Geographical Routing in Wireless Ad-Hoc Networks , 2013, IEEE Communications Surveys & Tutorials.

[38]  Seunghong Hong,et al.  Processing of GPS Data with Difference HDOP in Guide Robot for the Visually Impaired , 2007 .

[39]  Salah M. El-Sayed,et al.  Increasing The Performance Of Mobile Smartphones Using Partition And Migration Of Mobile Applications To Cloud Computing , 2014 .

[40]  Karthikeyan Umapathy,et al.  Language-Action Perspective (LAP) , 2009 .

[41]  Ashutosh Srivastava,et al.  Modelling mobility in emergency scenario for MANET applications , 2014, 2014 Recent Advances in Engineering and Computational Sciences (RAECS).

[42]  Sangkyung Sung,et al.  GNSS integration with vision-based navigation for low GNSS visibility conditions , 2013, GPS Solutions.

[43]  Inayat Ali Shah,et al.  An Efficient and Generic Algorithm for Matrix Inversion , 2010, Int. J. Technol. Diffusion.

[44]  Timothy X. Brown,et al.  Ad Hoc UAV Ground Network (AUGNet) , 2004 .

[45]  Li Kang,et al.  Attitude Heading Reference System Using MEMS Inertial Sensors with Dual-Axis Rotation , 2014, Sensors.

[46]  Dario Floreano,et al.  Dynamic Routing for Flying Ad Hoc Networks , 2014, IEEE Transactions on Vehicular Technology.

[47]  Ren-Hung Hwang,et al.  Open Source for Networking: Tools and Applications , 2014 .

[48]  Sidney Nascimento Givigi,et al.  Unmanned Aerial Vehicle formation flying using Linear Model Predictive Control , 2014, 2014 IEEE International Systems Conference Proceedings.

[49]  Marco Conti,et al.  Mesh networks: commodity multihop ad hoc networks , 2005, IEEE Communications Magazine.

[50]  Daewon Lee,et al.  Design and development of a free-floating hexrotor UAV for 6-DOF maneuvers , 2014, 2014 IEEE Aerospace Conference.

[51]  Jose A. Jiménez-Berni,et al.  A new era in remote sensing of crops with unmanned robots , 2008 .

[52]  Bin Zhang,et al.  Engineering Notes Probabilistic Weather Forecasting Analysis for Unmanned Aerial Vehicle Path Planning , 2014 .

[53]  Liren Zhang,et al.  Mobility analysis in vehicular ad hoc network (VANET) , 2013, J. Netw. Comput. Appl..

[54]  Thomas Weber,et al.  Post‐disaster Remote Sensing and Sampling via an Autonomous Helicopter , 2014, J. Field Robotics.

[55]  Changhao Piao,et al.  Study on Stable Estimation Method for Lead-acid Battery SOC by Extended Kalman Filter , 2014 .

[56]  Wahyu Kuntjoro,et al.  Advanced Autonomous Multirotor Response System , 2013 .

[57]  B. Mukherjee,et al.  Hybrid Wireless-Optical Broadband-Access Network (WOBAN): A Review of Relevant Challenges , 2007, Journal of Lightwave Technology.

[58]  Seid H. Pourtakdoust,et al.  Integrated motion planning and trajectory control system for unmanned air vehicles , 2013 .

[59]  Jamey D. Jacob,et al.  Modeling and Evaluation of a Spherical VTOL Aerial Vehicle with Ground Mobility , 2014 .

[60]  Stamatis Manesis,et al.  A Wireless Sensors and Controllers Network in automation a laboratory-scale implementation for students training , 2014, 22nd Mediterranean Conference on Control and Automation.

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

[62]  Thierry Peynot,et al.  Learned Stochastic Mobility Prediction for Planning with Control Uncertainty on Unstructured Terrain , 2014, J. Field Robotics.

[63]  Gurkan Tuna,et al.  Unmanned aerial vehicle-aided communications system for disaster recovery , 2014, J. Netw. Comput. Appl..

[64]  Ahmed Patel,et al.  VDTN-ToD: Routing Protocol VANET/DTN Based on Trend of Delivery , 2013, ICT 2013.

[65]  Pascual Campoy Cervera,et al.  An Approach Toward Visual Autonomous Ship Board Landing of a VTOL UAV , 2014, 2013 International Conference on Unmanned Aircraft Systems (ICUAS).

[66]  Reinhard German,et al.  Flying Ad-Hoc Network communication for detecting thermals: Feasibility and insights , 2013, Third International Conference on Innovative Computing Technology (INTECH 2013).

[67]  Dharma P. Agrawal,et al.  Linear wireless sensor networks: Classification and applications , 2011, J. Netw. Comput. Appl..

[68]  Kamran Mohseni,et al.  SensorFlock: an airborne wireless sensor network of micro-air vehicles , 2007, SenSys '07.

[69]  Thomas Kunz,et al.  An enhanced Gauss-Markov mobility model for simulations of unmanned aerial ad hoc networks , 2014, 2014 7th IFIP Wireless and Mobile Networking Conference (WMNC).