Lina Zhu

Geographic routing protocol for vehicular ad hoc networks in city scenarios: a proposal and analysis

The characteristics of vehicular ad hoc networks VANETs make the design of routing protocol a great challenge. In this paper, we propose a vehicle density and load aware routing protocol for VANETs called VDLA. VDLA adopts sequential selection of junctions to construct the route. The selection is based on the real-time vehicle density, the traffic load, and the distance to the destination. The network information is collected by a decentralized mechanism. Through factoring in these metrics, the packets are avoided being sent to roads where network is disconnected, and the network load is balanced to mitigate network congestion. The intermediate junctions are selected before the packet reaches a junction to reduce the unnecessary hops. Our study also investigates the impact of the high mobility of the nodes. An analytical framework is proposed to analyze the mobility. Based on the analysis, the traditional Hello scheme is enhanced to improve the accuracy of the neighbor table. In the simulation, we compare VDLA with greedy perimeter coordinator routing and GpsrJ+, which are geographic routings protocols proposed for VANETs. The results validate the superiority of VDLA in terms of end-to-end delay and packet delivery rate. And the superiority holds in different scenarios. Copyright

On Stochastic Analysis of Greedy Routing in Vehicular Networks

Even the greedy routing is widely used in wireless networks, its theoretical study is still limited in vehicle environments. In this paper, we theoretically analyze the performance of the greedy routing under three typical vehicle scenarios, i.e., the single-lane road, the multilane road, and the multilevel road. We first propose the analytical model by analyzing characteristics of traffic environments, which contain the width and multilevel features of roads. Specifically, we prove that the road-width is ignorable under certain conditions, whereas the data measured in an outdoor experiment reveal that the multilevel feature is non-ignorable because its existence dramatically degrades the transmission range. Based on the model, we analyze the routing length of the greedy routing for all scenarios in the following three aspects. 1) We derive the distribution function for the first one-hop progress. 2) We prove that routing increments are history-dependent and give one sufficient condition that ensures these increments are approximately i.i.d. 3) We calculate the routing length described by the h-hop coverage and hop count using the renewal theory. Finally, simulations are conducted to verify the accuracy of our analysis.

A self-adaptive and link-aware beaconless forwarding protocol for VANETs

With the development of networks, Vehicular Ad-hoc Networks (VANETs) which act as the emerging application enhance the potential power of networks on the traffic safety and the entertainment. However, the high mobility and the dynamic nature of VANETs lead to the unreliable link which causes unreachable transmission and degrades the performance of the routing protocol in terms of the quality of experience (QoE). To provide a reliable routing for the data transmission, a self-adaptive and link-aware beaconless forwarding (SLBF) protocol is proposed. Based on the receiver based forwarding (RBF) scheme, SLBF designs a self-adaptive forwarding zone which is used to make the candidate nodes accurate. Furthermore, it proposes a comprehensive algorithm to calculate the waiting time by taking the greedy strategy, link quality, and the traffic load into account. With the NS-2 simulator, the performance of SLBF is demonstrated. The results show that the SLBF makes a great improvement in the delivery ratio, the end-to-end delay, and the average hops.

On Resource Management in Vehicular Ad Hoc Networks: A Fuzzy Optimization Scheme

Resource management is a crucial task in vehicular ad hoc networks (VANETs) due to the existence of various resources, such as text, audio and video. However, the highly dynamic network feature and the limited memory of the local server pose challenges to resource management, which not only lead to the failure of resource presentations to users, but the transmission of the invalid fragment data would also result in the significant waste of precious bandwidth and memory. To address the issue, our paper proposes a Fuzzy Logic based Resource Management scheme (FLRM) under fog computing platform in VANETs. In the scheme, we first gather and record the request time and download time for each resource by the designed Vehicle to Infrastructure (V2I) communication mode. Depending on the above information, we define a survival time for each stored resource by the proposed fuzzy logic based popularity evaluation algorithm. Motivated by the defined survival time, the local server can update the resource list in real time. In the end, we conduct simulations to verify the performance of FLRM. Results demonstrate that the proposed scheme performs well in terms of throughput, which increases the user experience with fresh resources.

Finding the shortest path in huge data traffic networks: A hybrid speed model

The shortest path problem has become an important issue in the increasingly complex road networks nowadays, especially for these applications which are strict with high timeliness. However, searching the shortest path is difficult as road traffic flows are time-varying. An important issue in searching the shortest path is how to obtain the time expired on each segment at the given time. To this purpose, we propose a hybrid speed model to calculate the travel time in this paper, which considers the difference between the speed in congested and uncongested road networks. And analysis of speed in both conditions are given, respectively. Subsequently, a metric is also proposed to distinguish between congested and uncongested networks. Our work also utilizes the huge traffic data to reflect and analyze the real scenario. Compared to the previous work, this paper considers a more complex urban traffic scenario and some verifications are made with our data. Finally, a numerical study is carried out in the urban road network in Kaohsiung, Taiwan. The results show the hybrid speed model can give travel time prediction in an accurate way and can provide useful information for road designers.

A Reliable Beaconless Routing Protocol for VANETs

In Vehicular Ad hoc Networks (VANETs), video delivery is crucial to enhance the applications associated with safety, management and infotainment. However, the high mobility and dynamic nature of VANETs leads to unreliable links that pose a great challenge in protocol to support the high quality of experience (QoE) for video delivery. To provide an efficient protocol for VANETs, we propose a novel protocol called Reliable Beaconless Routing Protocol (RBRP) to perform receiver-based unicast forwarding without the help of beacons. In RBRP, we propose a self-adaptive forwarding zone to avoid the multipoint relay. And then the nodes compete for the forwarding right based on a comprehensive waiting time which considers the greedy strategy, the quality of link and the load of the node. To verify the performance of the RBRP, we compare it with the Greedy Perimeter Stateless Routing (GPSR) and the gossiping-based protocol by means of simulation with NS-2. Simulation results show that the RBRP improves the packet delivery ratio and reduces the end-to-end delay.

CFT: A Cluster-based File Transfer Scheme for highway VANETs

Effective file transfer between vehicles is fundamental to many emerging vehicular infotainment applications in the highway Vehicular Ad Hoc Networks (VANETs), such as content distribution and social networking. However, due to fast mobility, the connection between vehicles tends to be short-lived and lossy, which makes intact file transfer extremely challenging. To tackle this problem, we presents a novel Cluster-based File Transfer (CFT) scheme for highway VANETs in this paper. With CFT, when a vehicle requests a file, the transmission capacity between the resource vehicle and the destination vehicle is evaluated. If the requested file can be successfully transferred over the direct Vehicular-to-Vehicular (V2V) connection, the file transfer will be completed by the resource and the destination themselves. Otherwise, a cluster will be formed to help the file transfer. As a fully-distributed scheme that relies on the collaboration of cluster members, CFT does not require any assistance from roadside units or access points. Our experimental results indicate that CFT outperforms the existing file transfer schemes for highway VANETs.

A Hybrid Routing Protocol for 3-D Vehicular Ad Hoc Networks

In Vehicular Ad hoc NETworks (VANETs), traditional routing protocols are mainly based on planar scenarios. However, the actual application environments of VANETs are three-dimensional (3-D). For example, an important way to fully utilize the city space is the elevated overpass which is popular in most big cities. In this paper, we investigate the routing issues in 3-D scenarios of VANETs. We first analyze the characteristics of a 3-D city road network and present the key design points of 3-D routing protocols in VANETs. Afterward, we propose our hybrid improved 3-D scenario oriented routing (ITSR) which consists of two parts. The first is the routing strategy simple ITSR (S-ITSR) addressing the issue in the simple 3-D city scenario. In S-ITSR, we design intralayer greedy forwarding, interlayer greedy forwarding, and interlayer recovery strategy in combination with the degradation of the transmission range. The second is the routing strategy complex ITSR based on the complex 3-D city scenario. In this protocol, we introduce the concept of virtual neighbor node and the complete process of neighbor list considering the feature of the fluctuant transmission range. Finally, we conduct simulations to evaluate the network performance. Simulation results show that ITSR can achieve enhanced performance in terms of the packet delivery ratio, hop count, and end-to-end delay.

On dynamic video source decision in VANETs: an on-demand clustering approach

In vehicular ad hoc networks (VANETs), video communication makes a significant contribution to quality of experience (QoE) for people on the road. However, the selection of the video source is an impediment to video delivery due to the high mobility and dynamic topology of VANETs. An improper provider not only leads to frequent interruptions of communications, but the transmission of the invalid video fragments would also result in the waster of precious bandwidth. To address the issue, a novel video source decision scheme, named Cluster and Dynamic Overlay based video delivery over VANETs (CDOV), is proposed in this paper. By the on-demand clustering approach, nodes with the same video requirement/supply and moving features are clustered. Further, in a cluster, an overlay tree is constructed dynamically based on the relation between supply and demand, in which all requesters can find their greedy optimal source easily. In addition, the intracluster communication and head-RSU communication are designed for video streaming over this network structure. Using extensive simulations, the effectiveness of the proposed scheme is demonstrated. Compared with two existing works, the proposed solution is capable of obtaining lower startup latency and higher delivery ratio.

See the near future: A short-term predictive methodology to traffic load in ITS

The Intelligent Transportation System (ITS) targets to a coordinated traffic system by applying the advanced wireless communication technologies for road traffic scheduling. Towards an accurate road traffic control, the short-term traffic forecasting which predicts the road traffic at the particular site in a short period is often useful and important. In existing works, Seasonal Autoregressive Integrated Moving Average (SARIMA) model is a popular approach. The scheme however encounters two challenges: 1) the analysis on related data is insufficient whereas some important features of data may be neglected; and 2) with data presenting different features, it is unlikely to have one predictive model that can fit all situations. To tackle above issues, in this work, we develop a hybrid model to improve accuracy of SARIMA. In specific, we first explore the autocorrelation and distribution features existed in traffic flow to amend structure of the time series model. Based on the Gaussian distribution of traffic flow, a hybrid model with a Bayesian learning algorithm is developed which can effectively expand the application scenarios of SARIMA. We show the efficiency and accuracy of our proposal using both analysis and experimental studies. Using the real-world trace data, we show that the proposed predicting approach can achieve satisfactory performance in practice.