StabTrust—A Stable and Centralized Trust-Based Clustering Mechanism for IoT Enabled Vehicular Ad-Hoc Networks

Vehicular Ad-hoc Network (VANET) is a modern era of dynamic information distribution among societies. VANET provides an extensive diversity of applications in various domains, such as Intelligent Transport System (ITS) and other road safety applications. VANET supports direct communications between vehicles and infrastructure. These direct communications cause bandwidth problems, high power consumption, and other similar issues. To overcome these challenges, clustering methods have been proposed to limit the communication of vehicles with the infrastructure. In clustering, vehicles are grouped together to formulate a cluster based on certain rules. Every cluster consists of a limited number of vehicles/nodes and a cluster head (CH). However, the significant challenge for clustering is to preserve the stability of clusters. Furthermore, a secure mechanism is required to recognize malicious and compromised nodes to overcome the risk of invalid information sharing. In the proposed approach, we address these challenges using components of trust. A trust-based clustering mechanism allows clusters to determine a trustworthy CH. The novel features incorporated in the proposed algorithm includes trust-based CH selection that comprises of knowledge, reputation, and experience of a node. Also, a backup head is determined by analyzing the trust of every node in a cluster. The major significance of using trust in clustering is the identification of malicious and compromised nodes. The recognition of these nodes helps to eliminate the risk of invalid information. We have also evaluated the proposed mechanism with the existing approaches and the results illustrate that the mechanism is able to provide security and improve the stability by increasing the lifetime of CHs and by decreasing the computation overhead of the CH re-selection. The StabTrust also successfully identifies malicious and compromised vehicles and provides robust security against several potential attacks.

[1]  Zhen Wang,et al.  Improved Clustering Algorithm Based on AOW Clustering Algorithm , 2019, 2019 7th International Conference on Information, Communication and Networks (ICICN).

[2]  Waleed Ejaz,et al.  Unmanned Aerial Vehicles enabled IoT Platform for Disaster Management , 2019, Energies.

[3]  Sherali Zeadally,et al.  Data analytics for Cooperative Intelligent Transport Systems , 2019, Veh. Commun..

[4]  Baohua Huang,et al.  A Center-Based Secure and Stable Clustering Algorithm for VANETs on Highways , 2019, Wirel. Commun. Mob. Comput..

[5]  Mohsen Guizani,et al.  PUC: Packet Update Caching for energy efficient IoT-based Information-Centric Networking , 2020, Future Gener. Comput. Syst..

[6]  Fattehallah Ghadi,et al.  Efficient dissemination based on passive approach and dynamic clustering for VANET , 2018 .

[7]  Luciano Bononi,et al.  Design and performance evaluation of cross layered MAC and clustering solutions for wireless ad hoc networks , 2006, Perform. Evaluation.

[8]  Mohsen Guizani,et al.  RobustTrust – A Pro-Privacy Robust Distributed Trust Management Mechanism for Internet of Things , 2019, IEEE Access.

[9]  Rakesh Kumar,et al.  A Multi-metric-Based Algorithm for Cluster Head Selection in Multi-hop Ad Hoc Network , 2018 .

[10]  Kin K. Leung,et al.  Stable Clustering for Ad-Hoc Vehicle Networking , 2017, 2017 IEEE Wireless Communications and Networking Conference (WCNC).

[11]  T. Mamatha.  An Efficient Cluster based Routing Protocol using Hybrid FCM-Q LEACH for Vehicular Ad Hoc Networks , 2019 .

[12]  Punam Bedi,et al.  Use of Big Data technology in Vehicular Ad-hoc Networks , 2014, 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[13]  Mohsen Guizani,et al.  Caching in Information-Centric Networking: Strategies, Challenges, and Future Research Directions , 2018, IEEE Communications Surveys & Tutorials.

[14]  Devesh Shukla,et al.  Performance Evaluation of IEEE 802.11p Physical Layer for Efficient Vehicular Communication , 2020 .

[15]  Md. Kamrul Hasan,et al.  Routing Protocol Selection for Intelligent Transport System (ITS) of VANET in High Mobility Areas of Bangladesh , 2018, IJCCI.

[16]  A. V. Sutagundar,et al.  Agent based dynamic clustering for hybrid VANET (ADCHV) , 2016, 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT).

[17]  Rasmeet S. Bali,et al.  A Hybrid Backbone Based Clustering Algorithm for Vehicular Ad-Hoc Networks☆ , 2015 .

[18]  Soumya Xavier,et al.  A New Scalable Hybrid Routing Protocol for VANETs , 2014 .

[19]  Hang Su,et al.  Clustering-Based Multichannel MAC Protocols for QoS Provisionings Over Vehicular Ad Hoc Networks , 2007, IEEE Transactions on Vehicular Technology.

[20]  Bernard Ženko,et al.  Learning Predictive Clustering Rules , 2005, Informatica.

[21]  Syed Hassan Ahmed,et al.  Vehicular content centric network (VCCN): a survey and research challenges , 2015, SAC.

[22]  Ikram Ud Din,et al.  A popularity based caching strategy for the future Internet , 2016, 2016 ITU Kaleidoscope: ICTs for a Sustainable World (ITU WT).

[23]  Mohsen Guizani,et al.  A review of information centric network-based internet of things: communication architectures, design issues, and research opportunities , 2018, Multimedia Tools and Applications.

[24]  Sheng-Shih Wang,et al.  PassCAR: A passive clustering aided routing protocol for vehicular ad hoc networks , 2013, Comput. Commun..

[25]  M. A. Wong,et al.  A Hybrid Clustering Method for Identifying High-Density Clusters , 1982 .

[26]  Ioannis Baraklianos,et al.  Urban travel behaviour and household income in times of economic crisis: Challenges and perspectives for sustainable mobility , 2017, Transport Policy.

[27]  Byung-Seo Kim,et al.  The Internet of Things: A Review of Enabled Technologies and Future Challenges , 2019, IEEE Access.

[28]  Melbourne Barton,et al.  Efficient flooding with passive clustering-an overhead-free selective forward mechanism for ad hoc/sensor networks , 2003 .

[29]  Luca Delgrossi,et al.  IEEE 802.11p: Towards an International Standard for Wireless Access in Vehicular Environments , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.

[30]  Emmanuel S. Pilli,et al.  A framework to manage Trust in Internet of Things , 2016, 2016 International Conference on Emerging Trends in Communication Technologies (ETCT).

[31]  Geoffrey Ye Li,et al.  Vehicular Communications: A Network Layer Perspective , 2017, IEEE Transactions on Vehicular Technology.

[32]  Suzi Iryanti Fadilah,et al.  The modified safe clustering algorithm for vehicular ad hoc networks , 2017, 2017 IEEE 15th Student Conference on Research and Development (SCOReD).

[33]  Haleem Farman,et al.  Designing a Smart Transportation System: An Internet of Things and Big Data Approach , 2019, IEEE Wireless Communications.

[34]  Joel J. P. C. Rodrigues,et al.  Energy and performance aware fog computing: A case of DVFS and green renewable energy , 2019, Future Gener. Comput. Syst..

[35]  Wei Ni,et al.  An Evolutionary Game Theoretic Approach for Stable and Optimized Clustering in VANETs , 2018, IEEE Transactions on Vehicular Technology.

[36]  Raj Jain,et al.  A Survey of Protocols and Standards for Internet of Things , 2017, ArXiv.

[37]  Byung-Seo Kim,et al.  Information-Centric Network-Based Vehicular Communications: Overview and Research Opportunities , 2018, Sensors.

[38]  Abdelfettah Belghith,et al.  Cluster Connectivity Assurance Metrics in Vehicular ad hoc Networks , 2015, ANT/SEIT.

[39]  Feng Xia,et al.  Adaptive Beaconing Approaches for Vehicular Ad Hoc Networks: A Survey , 2016, IEEE Systems Journal.

[40]  Eswaran Perumal,et al.  Mobility and QoS Analysis in VANET Using NMP with Salp Optimization Models , 2020 .

[41]  Stephan Olariu,et al.  TDMA cluster-based MAC for VANETs (TC-MAC) , 2012, 2012 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM).

[42]  Sanjay Silakari,et al.  A Survey of all Existing Clustering Protocols in VANETS but Main Emphasis of Survey Laid on Currently using Protocol i. e TCDGP , 2015 .

[43]  Mohsen Guizani,et al.  Machine learning in the Internet of Things: Designed techniques for smart cities , 2019, Future Gener. Comput. Syst..

[44]  Antonios Argyriou,et al.  Estimating the Relative Speed of RF Jammers in VANETs , 2019, Secur. Commun. Networks.

[45]  Haleem Farman,et al.  Toward Integrating Vehicular Clouds with IoT for Smart City Services , 2019, IEEE Network.

[46]  Josephina Antoniou.  Using Game Theory to Characterize Trade-Offs Between Cloud Providers and Service Providers for Health Monitoring Services , 2020 .

[47]  Qian Ren,et al.  An Energy-Efficient Cluster Head Selection Scheme for Energy-Harvesting Wireless Sensor Networks , 2019, Sensors.

[48]  Richard Chbeir,et al.  A scalable data dissemination protocol based on vehicles trajectories analysis , 2018, Ad Hoc Networks.

[49]  Muhammad Khurram Khan,et al.  Cross-layer design and optimization techniques in wireless multimedia sensor networks for smart cities , 2019, Comput. Sci. Inf. Syst..

[50]  Byung-Seo Kim,et al.  Trust Management Techniques for the Internet of Things: A Survey , 2019, IEEE Access.

[51]  Lei Liu,et al.  A data dissemination scheme based on clustering and probabilistic broadcasting in VANETs , 2018, Veh. Commun..

[52]  Elisa Bertino,et al.  Protecting the 4G and 5G Cellular Paging Protocols against Security and Privacy Attacks , 2020, Proc. Priv. Enhancing Technol..

[53]  T. Menakadevi,et al.  Dynamic Clustering Mechanism to Avoid Congestion Control in Vehicular Ad Hoc Networks Based on Node Density , 2019, Wirel. Pers. Commun..

[54]  Amarsinh Vidhate,et al.  An agglomerative approach to elect the cluster head in VANET , 2016, 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES).

[55]  Joel J. P. C. Rodrigues,et al.  Clustering in vehicular ad hoc networks: Taxonomy, challenges and solutions , 2014, Veh. Commun..

[56]  Arif Ridho Lubis,et al.  Optimization of distance formula in K-Nearest Neighbor method , 2020 .

[57]  Mohinder S. Grewal,et al.  Global Navigation Satellite Systems, Inertial Navigation, and Integration , 2013 .

[58]  Z Li,et al.  KERNEL CLUSTERING ALGORITHM , 2002 .

[59]  Zibouda Aliouat,et al.  A review of routing protocols in internet of vehicles and their challenges , 2019, Sensor Review.

[60]  Mohsen Guizani,et al.  Integrating Fog Computing with VANETs: A Consumer Perspective , 2019, IEEE Communications Standards Magazine.

[61]  Lei Guo,et al.  Mobile Edge Computing-Enabled Internet of Vehicles: Toward Energy-Efficient Scheduling , 2019, IEEE Network.

[62]  Mohammad Reza Jabbarpour Sattari,et al.  Could-based vehicular networks: a taxonomy, survey, and conceptual hybrid architecture , 2017, Wireless Networks.

[63]  Daniel Liberzon,et al.  Almost Lyapunov functions for nonlinear systems , 2018, Autom..

[64]  Maqbool Hussain,et al.  Moth Flame Clustering Algorithm for Internet of Vehicle (MFCA-IoV) , 2019, IEEE Access.

[65]  Luciano Bononi,et al.  Intrusion detection for secure clustering and routing in Mobile Multi-hop Wireless Networks , 2007, International Journal of Information Security.

[66]  Andras Varga,et al.  A Practical Introduction to the OMNeT++ Simulation Framework , 2019, Recent Advances in Network Simulation.

[67]  Jagruti Sahoo,et al.  BAHG: Back-Bone-Assisted Hop Greedy Routing for VANET's City Environments , 2013, IEEE Transactions on Intelligent Transportation Systems.

[68]  Nadra Guizani,et al.  Secret Sharing-Based Energy-Aware and Multi-Hop Routing Protocol for IoT Based WSNs , 2019, IEEE Access.

[69]  Muhammad Khurram Khan,et al.  Multi‐tier authentication schemes for fog computing: Architecture, security perspective, and challenges , 2019, Int. J. Commun. Syst..

[70]  Shahnewaz Hasanat-E-Rabbi,et al.  ROAD TRAFFIC ACCIDENT: A LEADING CAUSE OF THE GLOBAL BURDEN OF PUBLIC HEALTH INJURIES AND FATALITIES , 2007 .

[71]  Mohsen Guizani,et al.  HoliTrust-A Holistic Cross-Domain Trust Management Mechanism for Service-Centric Internet of Things , 2019, IEEE Access.

[72]  Jianhui Wu,et al.  Study of multiple moving targets’ detection in fisheye video based on the moving blob model , 2018, Multimedia Tools and Applications.