ZTE Communications

Vehicular Networks

Jiannong Cao

2014, 12(1): 1-2.

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Yuanguo Bi, Hangguan Shan, Xuemin (Sherman) Shen, Hai Zhao

2014, 12(1): 3-10. doi:10.3969/j.issn.1673-5188.2014.01.001

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Vehicle to Infrastructure (V2I) communications aim to provide mobile users on the road low-cost Internet and driver safety services. However, to meet Quality of Service (QoS) requirements of various applications and efficiently utilize limited wireless channel resources, the transport layer protocol has to perform effective rate control in low channel quality and frequent changing topology communication environment. In this paper, we propose a novel rate-control scheme in infrastructure based vehicular networks that avoids congestion and starvation and promotes fairness in end-to-end V2I communications. In vehicular networks, a bottleneck roadside unit (RSU) keeps track of its buffer size, aggregate incoming rate, and link throughput, and appropriately allocates bandwidth to traversing flows. With feedback information from the RSU, source nodes dynamically adjust their sending rates to avoid buffer overflow or starvation at the bottleneck RSU. Simulation results show that the proposed scheme can reduce not only packet losses owing to buffer overflow but also buffer starvation time, which improves the utilization efficiency of wireless channel resource.

Advanced Leader Election for Virtual Traffic Lights

Florian Hagenauer, Patrick Baldemaier, Falko Dressler, Christoph Sommer

2014, 12(1): 11-16. doi:10.3969/j.issn.1673-5188.2014.01.002

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We examine the network performance of algorithms for self-organized traffic management. In particular, we focus on wireless networking between cars. One of many technologies that make road traffic safer and more efficient is the Virtual Traffic Light (VTL) system, which is able to coordinate the traffic flow at intersections without the need for physical lights. VTL takes a leading vehicle at an intersection and uses it to control the traffic lights. We developed algorithms for leader election and traffic light computation in realistic vehicular networking scenarios. Our key contribution is the extension of this algorithm to support arbitrary intersection layouts. We investigated the proposal in synthetic and realistic scenarios. The results show that, overall, VTLs use network resources efficiently and positively influences driving experience. It performs better than stationary traffic lights for a low to medium network load. We also identify potential optimizations to deal with high network load and to improve fairness.

Trajectory-Based Data Forwarding Schemes for Vehicular Networks

Jaehoon (Paul) Jeong, Tian He, David H.C.Du

2014, 12(1): 17-25. doi:10.3969/j.issn.1673-5188.2014.01.003

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This paper explains trajectory-based data forwarding schemes for multihop data delivery in vehicular networks where the trajectory is the GPS navigation path for driving in a road network. Nowadays, GPS-based navigation is popular with drivers either for efficient driving in unfamiliar road networks or for a better route, even in familiar road networks with heavy traffic. In this paper, we describe how to take advantage of vehicle trajectories in order to design data-forwarding schemes for information exchange in vehicular networks. The design of data-forwarding schemes takes into account not only the macro-scoped mobility of vehicular traffic statistics in road networks, but also the micro-scoped mobility of individual vehicle trajectories. This paper addresses the importance of vehicle trajectory in the design of multihop vehicle-to-infrastructure, infrastructure-to-vehicle, and vehicle-to-vehicle data forwarding schemes. First, we explain the modeling of packet delivery delay and vehicle travel delay in both a road segment and an end-to-end path in a road network. Second, we describe a state-of-the-art data forwarding scheme using vehicular traffic statistics for the estimation of the end-to-end delivery delay as a forwarding metric. Last, we describe two data forwarding schemes based on both vehicle trajectory and vehicular traffic statistics in a privacy-preserving manner.

Unveiling the Challenges in Improving Data Availability in Vehicular Networks with Network Coding

Zhenni Feng, Yanmin Zhu, Qian Zhang, Min Gao

2014, 12(1): 26-32. doi:10.3969/j.issn.1673-5188.2014.01.004

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Retrieving data from mobile source vehicles is a crucial routine operation for a wide spectrum of vehicular network applications, including road surface monitoring and sharing. Network coding has been widely exploited and is an effective technique for diffusing information over a network. The use of network coding to improve data availability in vehicular networks is explored in this paper. With random linear network codes, simple replication is avoided, and instead, a node forwards a coded block that is a random combination of all data received by the node. We use a network-coding-based approach to improve data availability in vehicular networks. To determine the feasibility of this approach, we conducted an empirical study with extensive simulations based on two real vehicular GPS traces, both of which contain records from thousands of vehicles over more than a year. We observed that, despite significant improvement in data availability, there is a serious issue with linear correlation between the received codes. This reduces the data-retrieval success rate. By analyzing the real vehicular traces, we discovered that there is a strong community structure within a real vehicular network. We verify that such a structure contributes to the issue of linear dependence. Then, we point out opportunities to improve the network-coding-based approach by developing community-aware code-distribution techniques.

Networking-GPS: Cooperative Vehicle Localization Using Commodity GPS in Urban Area

Chisheng Zhang, Jiannong Cao, Gang Yao

2014, 12(1): 33-39. doi:10.3939/j.issn.1673-5188.2014.01.005

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A challenging issue in intelligent transportation systems (ITS) is to accurately locate moving vehicles in urban area. Considerable efforts have been made to improve the localization accuracy of standalone GPS receivers. However, through empirical study, we found that the latitude and longitude values generated by GPS receivers fluctuate significantly because of the multipath effect in urban areas. The relative distances between neighboring vehicles with similar GPS signal data in terms of satellite sets and signal strength are much more stable in such a scenario. In this paper, we propose a cooperative localization algorithm, Networking-GPS, to improve the accuracy of location information for vehicular networks in urban area using commodity GPS receivers. First, atom redundantly rigid graphs of vehicles are constructed according to the similarity of neighboring GPS data. Then, through rigidity expansion, local accuracy can enforce global accuracy. Extensive simulations based on the real road network and trace data of vehicle mobility demonstrate that Networking-GPS can improve the accuracy of the entire system.

Anatomy of Connected Cars

Mario Gerla, Giovanni Pau, Rita Tse

2014, 12(1): 40-45. doi:10.3969/j.issn.1673-5188.2014.01.006

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The National Highway Traffic Safety Administration in the US and the European Commission are drafting a regulatory framework that will make the goal of connected vehicles possible by 2020. Control, embedded systems, and communication technologies have developed over the past 10 plus years and are approaching maturity. These will spark a revolution in how we approach driving. Cars will no longer need human drivers; they will be connected and exchange information about navigation, road hazards, traffic conditions, and safety. Travelers will be connected more than ever. Today’s car will become tomorrow’s office and the act of driving will become a leisure activity rather than a necessity. The emerging Internet of Vehicle enables application scenarios unimaginable just few years ago. The main challenges are Internet access spectrum scarcity, mobility, intermittent connectivity and scalability. In this article, we discuss the evolution from intelligent vehicle grid to autonomous, internet-connected vehicles and vehicular cloud.

Mobile Internet WebRTC and Related Technologies

Zhenjiang Dong, Congbing Li, Wei Wang, Da Lyu

2014, 12(1): 46-51. doi:10.3939/j.issn.1673-5188.2014.01.007

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This paper describes an improved design for WebRTC technology. With this design, WebRTC communication at client side, server side, and between these two sides is improved. HTML5 WebSocket, media negotiation and synthesis, network address translator (NAT)/firewall traversal, Session Initiation Protocol (SIP) signaling interaction, and P2P communication security are all used in this improved design. This solution solves cross- browser running problem of WebRTC applications, reduces reliance on client- side processing capability, and reduces bandwidth consumption. With this design, WebRTC also become more scalable.

Design and Implementation of a Distributed Complex-Event Processing Engine

Ping Lu, Yuming Qian, Kezhi Zhu

2014, 12(1): 52-56. doi:10.3969/j.issn.1673-5188.2014.01.008

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A high- performance, distributed, complex- event processing engine with improved scalability is proposed. In this new engine, the stateless processing node is combined with distributed storage so that scale and performance can be linearly expanded. This design prevents single node failure and makes the system highly reliable.

A User-Recommendation Method Based on Social Media

Hong Chen, Shengmei Luo, Lei Hu, Xiuwen Wang

2014, 12(1): 57-61. doi:10.3939/j.issn.1673-5188.2014.01.009

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User - analysis techniques are mainly used to recommend friends and information. This paper discusses the data characteristics of microblog users and describes a multidimensional user recommendation algorithm that takes into account microblog length, relativity between microblog and users, and familiarity between users. The experimental results show that this multidimensional algorithm is more accurate than a traditional recommendation algorithm.

The whole issue of ZTE Communications March 2014, Vol. 12 No. 1

2014, 12(1): 0.

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