Cluster Based Semantic Data Aggregation in VANETs

Recently, we are witnessing increased interest in the research of Vehicular Ad-hoc Networks (VANETs). Due to the peculiar characteristics of VANETs, such as high speed, the unstable communication link, and network partitioning, information transfer becomes inevitably challenging. The main communication challenges in vehicle to vehicle communication is scalability, predictability and reliability. With increasing number of vehicles in highway congestion scenarios, the congestion application need to disseminate large amount of information over multiple hops to the control center. This challenge can be solved by reducing the data load through clustering and data aggregation. In this paper, we propose cluster based semantic data aggregation (CBSDA) protocol that divide the road into different segments based on the cluster-ID and aggregate the data in each cluster. The aggregation scheme is a lossy aggregation with maximum precision. CBSDA scheme stores the data using a data structure that consists of super cluster, cluster and cluster member (CM) nodes. CBSDA is proposed to adaptively adjust the number of super cluster nodes. Moreover, the CBSDA scheme consists of weighted deviation scheme that decides which data to be fused for aggregation. Additionally, the aggregation level is controlled based on the density of vehicles and channel busy ratio (CBR). Simulation results show that the CBSDA using weighted deviation decision scheme is able to quickly reduce the channel congestion and improve the data precision even in congested traffic scenarios.

[1]  Ram Ramanathan,et al.  Hierarchically‐organized, multihop mobile wireless networks for quality‐of‐service support , 1998, Mob. Networks Appl..

[2]  Martin Mauve,et al.  Probabilistic aggregation for data dissemination in VANETs , 2007, VANET '07.

[3]  Kalman Graffi,et al.  Data aggregation in VANETs a generalized framework for channel load adaptive schemes , 2014, 39th Annual IEEE Conference on Local Computer Networks.

[4]  Weihua Zhuang,et al.  Modeling and Analysis for Emergency Messaging Delay in Vehicular Ad Hoc Networks , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[5]  Phone Lin,et al.  A Region-Based Clustering Mechanism for Channel Access in Vehicular Ad Hoc Networks , 2011, IEEE Journal on Selected Areas in Communications.

[6]  Liviu Iftode,et al.  TrafficView: traffic data dissemination using car-to-car communication , 2004, MOCO.

[7]  Chen Avin,et al.  Fast randomized algorithm for hierarchical clustering in Vehicular Ad-Hoc Networks , 2011, 2011 The 10th IFIP Annual Mediterranean Ad Hoc Networking Workshop.

[8]  Pramod K. Varshney,et al.  Data-aggregation techniques in sensor networks: a survey , 2006, IEEE Communications Surveys & Tutorials.

[9]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[10]  K. Ibrahim,et al.  CASCADE: Cluster-Based Accurate Syntactic Compression of Aggregated Data in VANETs , 2008, 2008 IEEE Globecom Workshops.

[11]  Divyakant Agrawal,et al.  Medians and beyond: new aggregation techniques for sensor networks , 2004, SenSys '04.

[12]  Lars Wischhof,et al.  Information dissemination in self-organizing intervehicle networks , 2005, IEEE Transactions on Intelligent Transportation Systems.

[13]  Abdelhakim Hafid,et al.  A new stability based clustering algorithm (SBCA) for VANETs , 2012, 37th Annual IEEE Conference on Local Computer Networks - Workshops.

[14]  Wai Chen,et al.  Ad hoc peer-to-peer network architecture for vehicle safety communications , 2005, IEEE Communications Magazine.

[15]  Xuemin Shen,et al.  DCS: An Efficient Distributed-Certificate-Service Scheme for Vehicular Networks , 2010, IEEE Transactions on Vehicular Technology.