SoLVE: A Localization System Framework for VANets using the Cloud and Fog Computing

Usually, vehicles are equipped with Global Positioning System (GPS), which can provide its position estimation. However, GPS can become erroneous or unavailable in cases of some indoor scenarios, such as tunnels and dense urban areas where there is no straight visibility to satellites. In Vehicular Ad Hoc Networks (VANets), some critical applications such as Driverless Vehicles and Blind Crossing require a precise localization system. In this work, we proposed a new localization system framework for VANets using the Cloud and Fog Computing paradigm. Our framework, called SoLVE (acronym of three keywords: System, Localization, and VANets), takes advantage of both Fog Computing and the location awareness of the RoadSide Units (RSUs) and Smart Traffic Lights (STL) in order to provide a precise estimate the position of vehicles within a Fog Network. Fogs can be as many as needed to cover the entire area of the localization system. Some of framework challenges, and implementations are discussed. Also, some use cases are described as well future research directions are highlighted.

[1]  Victor C. M. Leung,et al.  On Developing Smart Transportation Applications in Fog Computing Paradigm , 2016, DIVANet@MSWiM.

[2]  Wei Xiong,et al.  Vehicle node localization without GPS in VANET , 2014, 2014 International Conference on Connected Vehicles and Expo (ICCVE).

[3]  Ivan Stojmenovic,et al.  The Fog computing paradigm: Scenarios and security issues , 2014, 2014 Federated Conference on Computer Science and Information Systems.

[4]  Yacine Ghamri-Doudane,et al.  Software defined networking-based vehicular Adhoc Network with Fog Computing , 2015, 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM).

[5]  Silviu-Andrei Lazar,et al.  Future Vehicular networks: What control technologies? , 2016, 2016 International Conference on Communications (COMM).

[6]  Hannes Hartenstein,et al.  A tutorial survey on vehicular ad hoc networks , 2008, IEEE Communications Magazine.

[7]  Victor I. Chang,et al.  Computationally efficient privacy preserving anonymous mutual and batch authentication schemes for vehicular ad hoc networks , 2018, Future Gener. Comput. Syst..

[8]  Oliver W. W. Yang,et al.  Location Prediction of Vehicles in VANETs Using A Kalman Filter , 2015, Wirel. Pers. Commun..

[9]  Éfren Lopes Souza,et al.  On the performance of localization prediction methods for vehicular Ad Hoc Networks , 2015, 2015 IEEE Symposium on Computers and Communication (ISCC).

[10]  Azzedine Boukerche,et al.  Trust based security enhancements for vehicular ad hocnetworks , 2014, DIVANet '14.

[11]  Khalil El-Khatib,et al.  Paving the way for Intelligent Transport Systems (ITS): Privacy Implications of Vehicle Infotainment and Telematics Systems , 2016, DIVANet@MSWiM.

[12]  Deepak Gupta,et al.  On the hybrid augmentation of inter-vehicular communication assisted localization using previous path detection , 2015, 2015 IEEE International Advance Computing Conference (IACC).

[13]  Jalel Ben-Othman,et al.  Solution of detecting jamming attacks in vehicle ad hoc networks , 2013, MSWiM.

[14]  Gongjun Yan,et al.  The Next Paradigm Shift: From Vehicular Networks to Vehicular Clouds , 2013, Mobile Ad Hoc Networking.

[15]  Mohsen Guizani,et al.  RSU cloud and its resource management in support of enhanced vehicular applications , 2014, 2014 IEEE Globecom Workshops (GC Wkshps).

[16]  Sherali Zeadally,et al.  VANET-cloud: a generic cloud computing model for vehicular Ad Hoc networks , 2015, IEEE Wireless Communications.

[17]  Raja Lavanya,et al.  Fog Computing and Its Role in the Internet of Things , 2019, Advances in Computer and Electrical Engineering.

[18]  Azzedine Boukerche,et al.  Vehicular Ad Hoc Networks: A New Challenge for Localization-Based Systems , 2008, Comput. Commun..

[19]  Tetsutaro Uehara,et al.  Fog Computing: Issues and Challenges in Security and Forensics , 2015, 2015 IEEE 39th Annual Computer Software and Applications Conference.

[20]  Sateesh Addepalli,et al.  Fog computing and its role in the internet of things , 2012, MCC '12.

[21]  Luiz Fernando Bittencourt,et al.  Towards Virtual Machine Migration in Fog Computing , 2015, 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC).

[22]  Nasreddine Lagraa.  Localization technique in VANets using Clustering (LVC) , 2010 .

[23]  Silvia Giordano,et al.  The Next Paradigm Shift: From Vehicular Networks to Vehicular Clouds , 2013 .

[24]  Azzedine Boukerche,et al.  Improving Neighbor Localization in Vehicular Ad Hoc Networks to Avoid Overhead from Periodic Messages , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[25]  Jian Shen,et al.  Secure intelligent traffic light control using fog computing , 2018, Future Gener. Comput. Syst..

[26]  Fakhri Karray,et al.  Vehicle localization in VANETs using data fusion and V2V communication , 2012, DIVANet@MSWiM.

[27]  Yu Wang,et al.  Routing in vehicular ad hoc networks: A survey , 2007, IEEE Vehicular Technology Magazine.

[28]  Eduardo F. Nakamura,et al.  Information fusion for wireless sensor networks: Methods, models, and classifications , 2007, CSUR.

[29]  Kang Kai,et al.  Fog computing for vehicular Ad-hoc networks: paradigms, scenarios, and issues , 2016 .

[30]  Choong Seon Hong,et al.  A shared parking model in vehicular network using fog and cloud environment , 2015, 2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS).

[31]  S. Yousefi,et al.  Vehicular Ad Hoc Networks (VANETs): Challenges and Perspectives , 2006, 2006 6th International Conference on ITS Telecommunications.