Vehicular Networks enable a vast number of innovative applications, which rely on the efficient exchange of information between vehicles and often also with infrastructure. However, efficient and reliable data dissemination is a particularly challenging task in the context of vehicular networks due to the underlying properties of these networks, limited availability of network infrastructure and variable penetration rates for distinct communication technologies. This paper presents a novel system and mechanism for information collection and dissemination based on virtual infrastructure selection in combination with multiple communication technologies. The system has been evaluated using a simulation framework, involving network simulation in conjugation with realistic vehicular mobility traces. Simulation results show the feasibility of the proposed mechanism to achieve maximum message penetration in a geographical area with reduced overhead. The judicious vehicle selection also enables scalable data collection and leads to improved network utilization through the offload of traffic to the short-range network.

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One of the key radio resource management functions in mobile broadband networks is radio scheduling (also called MAC scheduling), which coordinates the access to shared radio resources. In Long Term Evolution (LTE), advanced scheduling algorithms are needed to provide proper QoS for multi-services and optimize the trade-off between QoS and resource efficiency. Moreover, in order to reduce the overall operation effort and costs, it is also more and more desired by the mobile network operators to develop a self-optimization function which can automatically adapt the optimized settings of the MAC scheduler in accordance with the traffic and network changes during the continuing operations. In this paper we use a novel OSA (Optimized Service Aware) scheduling algorithm for LTE, which provides a good balance between multi-QoS provisioning to support mixes of real-time/non-real-time traffic and system performance maximization in a proportionally fair manner. We present extensive simulation results to investigate the impact of the parameter settings of the OSA scheduler on the service and system performance, and further compare with the well known Proportional Fair (PF) scheduler. In addition, we explore the sensitivity of the optimal setting of the OSA scheduler with respect to different traffic scenarios. Then based on the investigations, we discuss the potential gain of applying SON (Self-Organizing Networks) functions to the OSA scheduler.

Abstract-Vehicular networking requires high message transmission rate but also faces limited radio resources. This may lead to congestion in the radio access network and incur long delay for the messages. On the other hand, applications also have stringent requirement for latency (or freshness) of the received information. In this paper, we focus on cellular-based vehicular networks and propose a method for finding an optimal trade-off between network congestion and the freshness of received information. We suggest a feedback-based scheme for vehicles and a centralized entity (GeoServer) to coordinate with each other to determine a message transmission rate that best satisfies the application requirements. We first outline the framework of the proposed mechanism, and then analytically derive the optimal solution. Following that, the performance of the proposed mechanism is evaluated via simulations.

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