Vehicular Wireless Sensor Research Articles

SDAA: Secure Data Aggregation and Authentication Using Multiple Sinks in Cluster-Based Underwater Vehicular Wireless Sensor Network.

Security is one of the major concerns while designing robust protocols for underwater sensor networks (UWSNs). The underwater sensor node (USN) is an example of medium access control (MAC) that should control underwater UWSN, and underwater vehicles (UV) combined. Therefore, our proposed method, in this research, investigates UWSN combined with UV optimized as an underwater vehicular wireless network (UVWSN) that can completely detect malicious node attacks (MNA) from the network. Thus, MNA that engages the USN channel and launches MNA is resolved by our proposed protocol through SDAA (secure data aggregation and authentication) protocol deployed in UVWSN. SDAA protocol plays a significant role in secure data communication, as the cluster-based network design (CBND) network organization creates a concise, stable, and energy-efficient network. This paper introduces SDAA optimized network known as UVWSN. In this proposed SDAA protocol, the cluster head (CH) is authenticated through the gateway (GW) and the base station (BS) to guarantee that a legitimate USN oversees all clusters deployed in the UVWSN are securely established for providing trustworthiness/privacy. Furthermore, the communicated data in the UVWSN network guarantee that data transmission is secure due to the optimized SDAA models in the network. Thus, the USNs deployed in the UVWSN are securely confirmed to maintain secure data communication in CBND for energy efficiency. The proposed method is implemented and validated on the UVWSN for measuring reliability, delay, and energy efficiency in the network. The proposed method is utilized for monitoring scenarios for inspecting vehicles or ship structures in the ocean. Based on the testing results, the proposed SDAA protocol methods improve energy efficiency and reduce network delay compared to other standard secure MAC methods.

Fog Computing for Detecting Vehicular Congestion, an Internet of Vehicles Based Approach: A Review

Vehicular congestion is directly impacting the efficiency of the transport sector. A wireless sensor network for vehicular clients is used in Internet of Vehicles based solutions for traffic management applications. It was found that vehicular congestion detection by using Internet of Vehicles based connected vehicles technology are practically feasible for congestion handling. It was found that by using Fog Computing based principles in the vehicular wireless sensor network, communication in the system can be improved to support larger number of nodes without impacting performance. In this paper, connected vehicles technology based vehicular congestion identification techniques are studied. Computing paradigms that can be used for the vehicular network are studied to develop a practically feasible vehicular congestion detection system that performs accurately for a large coverage area and multiple scenarios. The designed system is expected to detect congestion to meet traffic management goals that are of primary importance in intelligent transportation systems.

An effective data fusion-based routing algorithm with time synchronization support for vehicular wireless sensor networks

In the field of vehicular wireless sensor networks-based structural health monitoring, the structural damage identification is achieved by two structural features, namely natural frequencies and mode shapes. The kind of data fusion-based routing algorithm in specific applications needs to meet time synchronization requirements and meet certain constraints, such as the single-hop communication between cluster head node and each node in cluster, the overlap between different clusters and so on. To meet the special constraints for data fusion-based routing algorithm in structural health monitoring, this paper proposed a new method based on an improved flooding time synchronization protocol, which is called time synchronization and enhanced greedy algorithm based on D(v) (TSDEGA) routing algorithm. The TSDEGA method can achieve the minimum connected cover by node’s own degree D(v), and it can also meet the structural health monitoring routing constraints. The simulation experiments show that TSDEGA has better energy resistance and longer network lifetime, and it is superior to the traditional greedy algorithms. The proposed algorithm can effectively eliminate interference of outliers and improve the accuracy in order to meet time synchronization requirements in structural health monitoring applications.

Measuring air quality in city areas by vehicular wireless sensor networks

This paper considers a micro-climate monitoring scenario, which usually requires deploying a large number of sensor nodes to capture environmental information. By exploiting vehicular sensor networks ( VSNs), it is possible to equip fewer nodes on cars to achieve fine-grained monitoring. Specifically, when a car is moving, it could conduct measurements at different locations, thus collecting lots of sensing data. To achieve this goal, this paper proposes a VSN architecture to collect and measure air quality for micro-climate monitoring in city areas, where nodes’ mobility may be uncontrollable (such as taxis). In the proposed VSN architecture, we address two network-related issues: (1) how to adaptively adjust the reporting rates of mobile nodes to satisfy a target monitoring quality with less communication overhead and (2) how to exploit opportunistic communications to reduce message transmissions. We propose algorithms to solve these two issues and verify their performances by simulations. In addition, we also develop a ZigBee-based prototype to monitor the concentration of carbon dioxide (CO 2) gas in city areas.