The surge in vehicular network research has led, over the last few years, to the proposal of countless network solutions specifically designed for vehicular environments. A vast majority of such solutions has been evaluated by means of simulation, since experimental and analytical approaches are often impractical and intractable, respectively. The reliability of the simulative evaluation is thus paramount to the performance analysis of vehicular networks, and the first distinctive feature that has to be properly accounted for is the mobility of vehicles, i.e., network nodes. Notwithstanding the improvements that vehicular mobility modeling has undergone over the last decade, no vehicular mobility dataset is publicly available today that captures both the macroscopic and microscopic dynamics of road traffic over a large urban region. In this paper, we present a realistic synthetic dataset, covering 24 hours of car traffic in a 400- ${\rm km}^{2}$ region around the city of Koln, in Germany. We describe the generation process and outline how the dataset improves the traces currently employed for the simulative evaluation of vehicular networks. We also show the potential impact that such a comprehensive mobility dataset has on the network protocol performance analysis, demonstrating how incomplete representations of vehicular mobility may result in over-optimistic network connectivity and protocol performance.

Generation and Analysis of a Large-Scale Urban Vehicular Mobility Dataset

Currently, vehicular sensor network (VSN) has been paid much attention for monitoring the physical world of urban areas. We have studied VSNs by utilizing about 4000 taxies and 1000 buses equipped with GPS-based mobile sensors in Shanghai to constitute a virtual vehicular sensor network. The communication-connection intermittence makes the routing issue nontrivial when delay-tolerant applications are deployed in VSNs. The existing DTN routing protocols can be categorized as "neighbor-oriented" and how to select a neighbor candidate was always neglected. In this paper, we present a new DTN routing protocol for Delay-Tolerant Vehicular Sensor Networks, Packet-Oriented Routing protocol (POR), which is designed to emphasize neighbor selection based on awareness of packets to be sent and in consideration of probability to complete transferring of these packets. Our results show that POR performs much better than the ordinary Epidemic routing, as well as other popular routing protocols applied in a similar setting.

DTN Routing in Vehicular Sensor Networks

WiFi-enabled buses and stops may form the backbone of a metropolitan delay-tolerant network, which exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real-time information. This paper studies the routing problem in such a network. Assuming that the bus schedule is known, we maximize the delivery probability by a given deadline for each packet. Our approach takes the randomness into account, which stems from road traffic conditions, passengers boarding and alighting, and other factors that affect bus mobility. In this sense, this paper is one of the first to tackle quasi-deterministic mobility scenarios. We propose a simple stochastic model for bus arrivals at stops, supported by a study of real-life traces collected in a large urban network. A succinct graph representation of this model allows us to devise an optimal (under our model) single-copy routing algorithm and then extend it to cases where several copies of the same data are permitted. Through an extensive simulation study, we compare the optimal routing algorithm with three other approaches: 1) minimizing the expected traversal time over our graph; 2) maximizing the delivery probability over an infinite time-horizon; and 3) a recently proposed heuristic based on bus frequencies. We show that our optimal algorithm shows the best performance, but it essentially reduces to minimizing the expected traversal time. When transmissions frequently fail (more than half of the times), the algorithm behaves similarly to a heuristic that maximizes the delivery probability over an infinite time horizon. For reliable transmissions and values of deadlines close to the expected delivery time, the multicopy extension requires only ten copies to almost reach the performance of the costly flooding approach.

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Timely Data Delivery in a Realistic Bus Network

Bus networks in cities have distinctive features such as wide coverage and fixed bus routes so that they show the potential of forming the communication backbone in vehicular ad hoc networks (VANETs). This paper focuses on the geocast in bus-based VANETs and presents a geocast routing mechanism named Vela. Specifically, Vela analyzes and mines historical bus trajectories and characterizes spatial–temporal patterns (i.e., bus travel-time patterns and bus spatial encounter patterns) in a moderate granularity of road segments, which makes the mined patterns both accurate and steady. Furthermore, Vela exploits these acquired patterns to build a probabilistic spatial–temporal graph model and provides the available routing paths with the best possible quality-of-service levels for data delivery requests. Moreover, Vela also employs a two-hop aware strategy that utilizes the real-time spatial–temporal relationships between buses to increase the chances of forwarding the data. The results of the experiments on the real and synthetic trajectories show that Vela performs much better in terms of delivery ratio and delay and has stronger scalability than the other solutions.

On Geocasting over Urban Bus-Based Networks by Mining Trajectories

This paper presents our field experience in data collection from remote sensors. By letting tractors, farmers, and sensors have short-range radio communication devices with delay-disruption tolerant networking (DTN), we can collect data from those sensors to our central database. Although, several implementations have been made with cellular phones or mesh networks in the past, DTN-based systems for such applications are still under explored. The main objective of this paper is to present our practical implementation and experiences in DTN-based data collection from remote sensors. The software, which we have developed for this research, has about 50 kbyte footprint, which is much smaller than any other DTN implementation. We carried out an experiment with 39 DTN nodes at the University of Tokyo assuming an agricultural scenario. They achieved 99.8% success rate for data gathering with moderate latency, showing sufficient usefulness in data granularity.

A DTN-Based Sensor Data Gathering for Agricultural Applications

A disruption-tolerant network (DTN) attempts to route packets between nodes that are temporarily connected. Difficulty in such networks is that nodes have no information about the network status and contact opportunities. The situation is different in public bus networks because the movement of buses exhibits some regularity so that routing in a deterministic way is possible. Many algorithms use a contacts oracle that provides the exact meeting times and durations between all nodes. However, in a real vehicular environment, an oracle is not always accurate, and deterministic routing gives poor results. In this paper, we present BLER, a routing algorithm that achieves effective routing in a buses environment. BLER, compared to other algorithms, performs routing at bus line level instead of bus level; it uses specific bus lines information to achieve good performances. We evaluate BLER on real traces of the bus network of Shanghai, and compare it to other routing algorithms. Performances provide good results for this kind of DTNs.

M. Sede

Papers

Routing in Large-Scale Buses Ad Hoc Networks