Advances on Network Protocols and Algorithms for Vehicular Ad Hoc Networks

Jaime Lloret 0 1 3 Kayhan Z. Ghafoor 0 1 3 Danda B. Rawat 0 1 3 Feng Xia 0 1 3 0 D. B. Rawat Department of Electrical Engineering, Georgia Southern University , Statesboro, GA 30460, USA 1 K. Z. Ghafoor Faculty of Engineering, Koya University , Daniel Miterrand Boulevard, Koya KOY45, Kurdistan Region, Iraq 2 ) Integrated Management Coastal Research Institute, Universidad Politcnica de Valencia , C/Paranimf, n 1, Grao de Gandia 46730, Spain 3 F. Xia School of Software, Dalian University of Technology (DUT) , Development Zone, Dalian 116620, China Vehicular Ad Hoc Network (VANET) is an emerging area of wireless ad hoc networks that facilitates ubiquitous connectivity between smart vehicles through Vehicle-to-Vehicle (V2V) or Vehicle-to-Roadside (V2R) and Roadside-toVehicle (R2V) communications. This emerging field of technology aims to improve safety of passengers and traffic flow, reduces pollution to the environment and enables in-vehicle entertainment applications. The safety-related applications could reduce accidents by providing drivers with traffic information such as collision avoidances, traffic flow alarms and road surface conditions. Moreover, the passengers could exploit an available infrastructure in order to connect to the internet for infomobility and entertainment applications [1]. The increasing necessity of this network is an impetus for leading car manufacturers, research communities and governments to increase their efforts toward creating a standardized - platform for vehicular communications. However, VANETs unique characteristics and special requirements excite new challenges to the research community. To address these challenges in both safety- and comfort-oriented applications, there is a pressing need to develop new protocols and algorithms for channel characterization and modeling, Medium Access Control (MAC), obstacle modeling, adaptive geographical routing to sparse and dense traffic conditions. This special issue aimed to theme innovative research achievements in the field of vehicular networks and communications. We were seeking original, innovative and unpublished papers related to radio obstacle modeling in urban vehicular environments [2], VANET routing protocols [3] (such as efficient geographical routing [4], delay-aware routing protocols [5], delay tolerant routing protocols [6], routing protocol using movement trends [7], etc.), adaptive beaconing protocols [8], mobility management and handovers [9], network size [10], transmission power adaptation systems [11], Quality of Service [12], security and privacy issues [13], efficient packet forwarding optimization[14], modeling and simulation [15], etc. We also welcomed other typical VANET topics such as channel characterization, congestion control and resource management, medium access protocols and channel assignments, mobility models, message dissemination for safety-related applications, cooperative vehicular communications, test-beds, case studies, experimental systems and real evaluations. Our purpose was also to include new VANET topics such as Inter-domain Proxy Mobile IPv6 in VANETs [16], Vehicular Cloud Computing [17] and security in Vehicular Clouds [18]. We received 77 submissions and only the best 12 papers have been accepted, which means an acceptance ratio of 15.58 %. We give many thanks to the reviewers for their time revising and providing useful comments to the authors and to the authors for their patience when some steps have been delayed because of the amount of received papers. We have classified the accepted papers in the following list of topics: 1) Path and channel loss 2) Topology formation 3) Vehicle route prediction and vehicular mobility 4) Medium Access Control 5) Handover 6) Routing 7) Audio and video streaming 8) Security 2 Access layer 2.1 Path and channel loss In [19], H. Fernndez et al. analyze the path loss, in terms of the Transmitter-Receiver separation distance and fading statistics, in two different urban environments, with different road traffic densities and propagation characteristics, and in an expressway environment. Based on a narrowband channel measurement campaign carried out at 5.9 GHz, they present a Audio and video streaming MAC Handover Vehicular mobility Vehicular route prediction Topology formation Path and channel loss Fig. 1 Papers topics grouped in Layers vehicular path loss characterization and propose a simplified propagation model, which is suitable for VANETs simulators to evaluate and analyze the performance of safety and nonsafety applications under realistic propagation conditions. The proposed path loss model has a linear relationship between the path loss and the logarithmic of the Tx-Rx separation distance. They evaluated the packet error rate (PER) and the maximum achievable Tx-Rx separation distance for a PER threshold level of 10 % according to the digital short-range communications (DSRC) specifications. 2.2 VANET topology formation In [20], Y. Allouche and M. Segal present a self-organizing cluster-based topology to serve as the infrastructure for an efficient and reliable beacon dissemination process. This process provides a real-time, broad and coordinated map under the challenging VANET conditions. Moreover, they propose the Distributed Construct Underlying Topology (D-CUT) algorithm tailed specifically to provide an optimized topology for such beacon dissemination process. In order to achieve this goal, the network is partitioned into clusters of adjacent vehicles. Each cluster contains a designated vehicle that acts as the cluster head, connected by one-hop intra-cluster links to its cluster members. The second level of the topology connects adjacent cluster heads by multi-hop, inter-cluster links. The system integrates contention-free medium access control (MAC) protocols. Moreover, it aims to reduce the interference by geographically optimizing the topology, and, in this way, allows the execution of extensive but reliable inter-cluster bandwidth reuse. They evaluated the performance of the DCUT algorithm under realistic road conditions. Their simulation results support their theoretical findings with respect to logarithmic initial convergence time under realistic traffic scenarios. 2.3 Vehicle route prediction and vehicular mobility In [21], A. F. Merah et al. design and implement 5 communication schemes for depicting the road segments in which vehicles traverse through during their trips in a specific geographic area, as sequential patterns. These traces are compiled into a database of historical sequential patterns traversed by vehicles and make use of data mining techniques in order to build travel profiles for vehicles that may be tracked in a realtime fashion. They classified them in two categories: Based on Road Side Unit scheme, which periodically queries the vehicles to send their traversed paths to their neighbors and based on Vehicle schemes, where vehicles initiate the sen (...truncated)