This research aims at using vehicular ad-hoc networks as infra-structure for an urban cyber-physical system in order to gather data about a city. In this scenario, all nodes are data sources and there is a gateway as ultimate destination for all packets. Because of the volatility of the network connections and uncertainty of actual node placement, we argue that a broadcast-based protocol is the most adequate solution, despite the high overhead. The Urban Data Collector (UDC) protocol has been proposed which uses a distributed election of the forwarding node among the nodes receiving the packet: nodes that are nearer to the gateway have shorter timers and a higher forwarding probabilities. The performance of the UDC protocol has been evaluated with different suppression levels in terms of the amount of collected data from each road segment using NS-3, and our results show that UDC can achieve significantly higher sensing accuracy than to other broadcast-based protocols.
Existing solutions for VANET sensing either apply on-demand querying for local dissemination @cite_7 , sometimes keeping the data in the location @cite_15 , or rely on delay-tolerant networking and open Wi-Fi access points for sending the data to the Internet backbone @cite_16 . The first are inefficient for real-time monitoring due to the query overhead and the need to globally access the data, and the latter cannot guarantee up-to-date data.
@cite_15 @cite_16 @cite_7
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Vehicular Adhoc Networks (VANETs) have been attracted a lot of research recent years. Although VANETs are deployed in reality offering several services, the current architecture has been facing many difficulties in deployment and management because of poor connectivity, less scalability, less flexibility and less intelligence. We propose a new VANET architecture called FSDN which combines two emergent computing and network paradigm Software Defined Networking (SDN) and Fog Computing as a prospective solution. SDN-based architecture provides flexibility, scalability, programmability and global knowledge while Fog Computing offers delay-sensitive and location-awareness services which could be satisfy the demands of future VANETs scenarios. We figure out all the SDN-based VANET components as well as their functionality in the system. We also consider the system basic operations in which Fog Computing are leveraged to support surveillance services by taking into account resource manager and Fog orchestration models. The proposed architecture could resolve the main challenges in VANETs by augmenting Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Base Station communications and SDN centralized control while optimizing resources utility and reducing latency by integrating Fog Computing. Two use-cases for non-safety service (data streaming) and safety service (Lane-change assistance) are also presented to illustrate the benefits of our proposed architecture. Several multihop applications developed for vehicular ad hoc networks use broadcast as a means to either discover nearby neighbors or propagate useful traffic information to other vehicles located within a certain geographical area. However, the conventional broadcast mechanism may lead to the so-called broadcast storm problem, a scenario in which there is a high level of contention and collisions at the link layer due to an excessive number of broadcast packets. While this is a well-known problem in mobile ad hoc wireless networks, only a few studies have addressed this issue in the VANET context, where mobile hosts move along the roads in a certain limited set of directions as opposed to randomly moving in arbitrary directions within a bounded area. Unlike other existing works, we quantify the impact of broadcast storms in VANETs in terms of message delay and packet loss rate in addition to conventional metrics such as message reachability and overhead. Given that VANET applications are currently confined to using the DSRC protocol at the data link layer, we propose three probabilistic and timer-based broadcast suppression techniques: weighted p-persistence, slotted 1-persistence, and slotted p-persistence schemes, to be used at the network layer. Our simulation results show that the proposed schemes can significantly reduce contention at the MAC layer by achieving up to 70 percent reduction in packet loss rate while keeping end-to-end delay at acceptable levels for most VANET applications. A new kind of ad hoc network is hitting the streets: Vehicular Ad Hoc Networks (VANets). In these networks, vehicles communicate with each other and possibly with a roadside infrastructure to provide a long list of applications varying from transit safety to driver assistance and Internet access. In these networks, knowledge of the real-time position of nodes is an assumption made by most protocols, algorithms, and applications. This is a very reasonable assumption, since GPS receivers can be installed easily in vehicles, a number of which already comes with this technology. But as VANets advance into critical areas and become more dependent on localization systems, GPS is starting to show some undesired problems such as not always being available or not being robust enough for some applications. For this reason, a number of other localization techniques such as Dead Reckoning, Cellular Localization, and Image Video Localization has been used in VANets to overcome GPS limitations. A common procedure in all these cases is to use Data Fusion techniques to compute the accurate position of vehicles, creating a new paradigm for localization in which several known localization techniques are combined into a single solution that is more robust and precise than the individual approaches. In this paper, we further discuss this subject by studying and analyzing the localization requirements of the main VANet applications. We then survey each of the localization techniques that can be used to localize vehicles and, finally, examine how these localization techniques can be combined using Data Fusion techniques to provide the robust localization system required by most critical safety applications in VANets. It may not be feasible for sensor networks monitoring nature and inaccessible geographical regions to include powered sinks with Internet connections. We consider the scenario where sinks are not present in large-scale sensor networks, and unreliable sensors have to collectively resort to storing sensed data over time on themselves. At a time of convenience, such cached data from a small subset of live sensors may be collected by a centralized (possibly mobile) collector. In this paper, we propose a decentralized algorithm using fountain codes to guarantee the persistence and reliability of cached data on unreliable sensors. With fountain codes, the collector is able to recover all data as long as a sufficient number of sensors are alive. We use random walks to disseminate data from a sensor to a random subset of sensors in the network. Our algorithms take advantage of the low decoding complexity of fountain codes, as well as the scalability of the dissemination process via random walks. We have proposed two algorithms based on random walks. Our theoretical analysis and simulation-based studies have shown that, the first algorithm maintains the same level of fault tolerance as the original centralized fountain code, while introducing lower overhead than naive random-walk based implementation in the dissemination process. Our second algorithm has lower level of fault tolerance than the original centralized fountain code, but consumes much lower dissemination cost.