Zhengtao Xiang

A Cross-Layer AOMDV Routing Protocol for V2V Communication in Urban VANET

Vehicular Ad hoc Network (VANET) is a special class of wireless mobile communication network. For vehicle-to-vehicle (V2V) communication, suitable routing protocols are needed. A routing metric combining hop counts and retransmission counts at MAC layer is proposed with consideration of link quality and delay reduction. Based on the new routing metric, a cross-layer Ad hoc On-demand Multipath Distance Vector with retransmission counts metric (R-AOMDV) routing protocol is designed to make use of advantages of multi-path routing protocol, such as decrease of route discovery frequency. Compared with AOMDV with minimum hop-count metric, simulation results show that R-AOMDV achieves better performance with Pareto On/Off distribution traffic model in urban VANET, no matter in sparse or dense scenarios.

An adaptive cross-layer multi-path routing protocol for urban VANET

For vehicle-to-vehicle (V2V) communication, suitable routing protocols are needed. An adaptive cross-layer multi-path routing protocol, R-S-AOMDV, is proposed. The routing metric combines hop-count, link-quality and vehicle-motion information. To make use of advantages of multi-path routing protocol, such as decrease of route discovery frequency, the protocol is designed based on the improvement of AOMDV (Ad hoc On-demand Multipath Distance Vector) routing protocol. Compared with AOMDV with minimum hop-count metric, simulation results show that R-S-AOMDV achieves better performance, no matter in sparse or dense urban VANET (Vehicular Ad hoc NETwork).

Multi-Fractal Characteristics of Mobile Node's Traffic in Wireless Mesh Network with AODV and DSDV Routing Protocols

The analysis of traffic characteristics can be used for performance evaluation, design and implementation of routing protocols in WMNs (Wireless Mesh Networks). Higher bursty traffic will cause larger queue size, which means more dropping packets, and thus affects other metrics. Because burstiness can be modeled by multi-fractal characteristics effectively, multi-fractal characteristics of mobile node’s traffic in WMNs are analyzed with typical proactive and reactive routing protocols, which are DSDV (Destination Sequenced Distance Vector) and AODV (Ad hoc On-demand Distance Vector), respectively. Three types of traffic models are used to generate traffic at application level, which corresponding to open-loop and closed-loop scenarios. With different configurations, the probability distribution of inter-arrival time and multi-fractal characteristics of traffic at mobile node and gateway are analyzed with DSDV and AODV protocols. Results show that inter-arrival time with AODV and DSDV protocols possesses heavy-tailed property. And traffic with DSDV protocol exhibits more multi-fractal characteristics than that with AODV protocol, which can explain the higher routing performance of AODV.

Design and implementation of multi-source vehicular information monitoring system in real time

Vehicular applications are the bases of vehicle value-added services in the future, which depend on real-time access to multi-source vehicular information. In order to be applied to vehicles in use easily, the implementation of vehicular applications should avoid modifying vehicles and control the increase of wiring harness to decrease system complexity. A vehicular information real-time monitoring framework is proposed, which can collect, transfer and display vehicle driving information, such as velocity and trouble codes, and environment information, such as GPS and video around the car. A flexible and reliable communication protocol is designed to exchange multi-source information between modules in the framework. On-Board Diagnose (OBD) technology and wireless technology are used to collect vehicle driving information to avoid modifying vehicles, and to transfer information to control the increase of wiring harness, respectively. The prototype system is tested on a car, and the results show that the system can be used easily as a basis for future vehicular applications based on multi-source information fusion.

Predictability of Aggregated Traffic of Gateways in Wireless Mesh Network with AODV and DSDV Routing Protocols and RWP Mobility Model

When evaluating the performance of routing protocols in wireless mesh network (WMN), we need deeper analysis from the aspect of network traffic complexity to show how traffic characteristics are influenced by routing protocols and node mobility. The predictability of network traffic can be used as one metric of complexity and can be analyzed by multi-scale entropy (MSE) method. With 20 different random waypoint (RWP) mobility scenarios and with destination sequenced distance vector (DSDV), a typical proactive protocol, and Ad hoc on-demand distance vector (AODV), a typical reactive protocol, the predictabilities of aggregated traffic of gateway in WMN are analyzed using MSE method to show how different routing protocols bear different mobility scenarios. The MSE results show that the aggregated traffic of gateway with DSDV is more difficult to be predicted than that with AODV for different mobility scenarios. The maxspeed parameter of RWP dominates the traffic predictability for AODV. Both of the pause time and the maxspeed parameters, have great influence on the traffic predictability for DSDV. The reasons lie in the behaviors of routing protocols, i.e., AODV has up-to-date paths while DSDV does not.

Predictability Analysis of Lithium-Ion Battery Remaining Useful Life with Multiscale Entropy

Lithium-ion battery Remaining Useful Life (RUL) estimation and prediction are very important in the fields of reliability, automatic test, power sources, and electric vehicles, etc. The performance of battery RUL estimation relies on the predictability. Multiscale entropy (MSE) can be used to analyze the predictability of time series across multiple time scales. MSE is used to analyze the predictability of lithium-ion battery RUL. Results show that the predictability of battery discharge voltage decreases along with time scale and discharge cycle, and when the cycle time exceeds certain value, the predictability of discharge voltage decreases sharply. As an input of RUL prediction, the predictability of discharge voltage influences the prediction performance of RUL. For better prediction of RUL, if the MSE of discharge voltage of certain cycle changes greatly, other models or different model parameters should be considered.

Effect Analysis of Early Warning for Abandoned Object on Highway Based on Internet-of-Vehicles CA Model

An early warning on the highway will effectively reduce traffic accidents. Considering the influence of an abandoned object on driving behavior, a Visual-based Asymmetric Two-lane Cellular Automata model with Abandoned Object (V-ATCA-AO) and an Internet-of-Vehicles-based Asymmetric Two-lane Cellular Automata model with Abandoned Object (IoV-ATCA-AO) are proposed. Based on the two models, two types of traffic accidents caused by an abandoned object are analyzed: rear-end collision caused by the abandoned object ahead and collision of the vehicle with the abandoned object. Simulation results show the following: the accidents occur when the road density is smaller, while the accidents will not occur when the density is larger. The results are different from the rear-end collision rate curve without abandoned object in a single lane. Compared with the visual-based avoidance pattern in V-ATCA-AO, the Internet-of-Vehicles-based avoidance pattern in IoV-ATCA-AO can create an early warning for the abandoned object and tell the vehicle to make an earlier lane change and decelerate in advance, thereby significantly reducing the accident rate. Spatiotemporal characteristics in front of the abandoned object directly affect the accident rate: the less the “stability” of a traffic jam in front of the abandoned object, the higher the accident rate.

A Cellular Automaton Traffic Model Considering the Influence of Driving State on Randomization

The cellular automaton (CA) traffic models are widely used to simulate the real traffic. Considering the influence of driving states on randomization, a cellular automaton model based on the NS model is proposed. In our new model, the randomization probability is different for different driving states, which is determined by the velocity changes after the step of deterministic deceleration. Simulation results show that the maximum flux of the new model is greater than that of the NS model, and the traffic evolution of the new model is more complex than that of the NS model.

The effects of advanced information feedback strategies in FI model

Advanced Traveler Information System provides travelers with real-time transportation information, which can satisfy the dynamic requirements of travelers and increase the ability of transportation infrastructure. Many information feedback strategies are proposed based on the real-time information of roads and vehicles. There are some typical information feedback strategies: Travel Time Feedback Strategy (TTFS), Mean Velocity Feedback Strategy (MVFS), and Congestion Coefficient Feedback Strategy (CCFS). However, all the above information strategies are used in NS model. The effects of the above information feedback strategies in other models have not been studied. The effects of the above information feedback strategies in FI model are validated in this paper. Results show that the above strategies are applicable to FI model.

Implementing Ad hoc On-demand Multipath Distance Vector routing protocol in Linux

Multi-path routing protocol attracts more and more attention because the routing performance can be improved by making use of advantages of multi-path routing protocol, such as fault-tolerant and load balance. To validate multi-path routing protocol in real environment, the Ad hoc On-demand Multipath Distance Vector (AOMDV) routing protocol is implemented in Linux based on AODV-UU. The functions of AOMDV protocol are implemented in user space, and the interaction with the kernel is implemented based on Netlink and Netfilter. Experimental results validate the implementation of AOMDV.