Time- and Computation-Efficient Data Localization at Vehicular Networks\u27 Edge

As Vehicular Networks rely increasingly on sensed data to enhance functionality and safety, efficient and distributed data analysis is needed to effectively leverage new technologies in real-world applications. Considering the tens of GBs per hour sensed by modern connected vehicles, traditional analysis, based on global data accumulation, can rapidly exhaust the capacity of the underlying network, becoming increasingly costly, slow, or even infeasible. Employing the edge processing paradigm, which aims at alleviating this drawback by leveraging vehicles\u27 computational power, we are the first to study how to localize, efficiently and distributively, relevant data in a vehicular fleet for analysis applications. This is achieved by appropriate methods to spread requests across the fleet, while efficiently balancing the time needed to identify relevant vehicles, and the computational overhead induced on the Vehicular Network. We evaluate our techniques using two large sets of real-world data in a realistic environment where vehicles join or leave the fleet during the distributed data localization process. As we show, our algorithms are both efficient and configurable, outperforming the baseline algorithms by up to a 40 7 speedup while reducing computational overhead by up to 3 7 , while providing good estimates for the fraction of vehicles with relevant data and fairly spreading the workload over the fleet. All code as well as detailed instructions are available at https://github.com/dcs-chalmers/dataloc_vn

Distributed and Communication-Efficient Continuous Data Processing in Vehicular Cyber-Physical Systems

Processing the data produced by modern connected vehicles is of increasing interest for vehicle manufacturers to gain knowledge and develop novel functions and applications for the future of mobility.Connected vehicles form Vehicular Cyber-Physical Systems (VCPSs) that continuously sense increasingly large data volumes from high-bandwidth sensors such as LiDARs (an array of laser-based distance sensors that create a 3D map of the surroundings).The straightforward attempt of gathering all raw data from a VCPS to a central location for analysis often fails due to limits imposed by the infrastructure on the communication and storage capacities. In this Licentiate thesis, I present the results from my research that investigates techniques aiming at reducing the data volumes that need to be transmitted from vehicles through online compression and adaptive selection of participating vehicles. As explained in this work, the key to reducing the communication volume is in pushing parts of the necessary processing onto the vehicles\u27 on-board computers, thereby favorably leveraging the available distributed processing infrastructure in a VCPS.The findings highlight that existing analysis workflows can be sped up significantly while reducing their data volume footprint and incurring only modest accuracy decreases. At the same time, the adaptive selection of vehicles for analyses proves to provide a sufficiently large subset of vehicles that have compliant data for further analyses, while balancing the time needed for selection and the induced computational load

TDMA Slot Reservation in Cluster-Based VANETs

Vehicular Ad Hoc Networks (VANETs) are a form of Mobile Ad Hoc Networks (MANETs) in which vehicles on the road form the nodes of the network. VANETs provide several services to enhance the safety and comfort of drivers and passengers. These services can be obtained by the wireless exchange of information among the vehicles driving on the road. In particular, the transmission of two different types of messages, safety/update and non-safety messages. The transmission of safety/update message aims to inform the nearby vehicles about the sender\u27s current status and/or a detected dangerous situation. This type of transmission is designed to help in accident and danger avoidance. Moreover, it requires high message generated rate and high reliability. On the other hand, the transmission of non-safety message aims to increase the comfort on vehicles by supporting several non-safety services, from notifications of traffic conditions to file sharing. Unfortunately, the transmission of non-safety message has less priority than safety messages, which may cause shutting down the comfort services. The goal of this dissertation is to design a MAC protocol in order to provide the ability of the transmission of non-safety message with little impact on the reliability of transmitting safety message even if the traffic and communication densities are high. VANET is a highly dynamic network. With lack of specialized hardware for infrastructure and the mobility to support network stability and channel utilization, acluster-based MAC protocol is needed to solve these overcomes. This dissertation makes the following contributions: 1. A multi-channel cluster-based TDMA MAC protocol to coordinate intracluster communications (TC-MAC) 2. A CH election and cluster formation algorithm based on the traffic flow and a cluster maintenance algorithm that benefits from our cluster formation algorithm 3. A multi-channel cluster-based CDNIA/TDMA hybrid MAC protocol to coordinate inter-cluster communications I will show that TC-MAC provides better performance than the current WAVE standard in terms of safety/update message reliability and non-safety message delivery. Additionally, I will show that my clustering and cluster maintenance protocol provides more stable clusters, which will reduce the overhead of clusterhead election and re-clustering and leads to an efficient hierarchical network topology

Location-aware mechanism for efficient video delivery over wireless mesh networks

Due to their flexibility, ease of use, low-cost and fast deployment, wireless Mesh Networks have been widely accepted as an alternative to wired network for last-mile connectivity. When used in conjunction with Peer-to-Peer data transfer solutions, many innovative applications and services such as distributed storage, resource sharing, live TV broadcasting or Video on Demand can be supported without any centralized administration. However, in order to achieve a good quality of service in such variable, error-prone and resource-constrained wireless multi-hop environments, it is important that the associated Peer-to-Peer overlay is not only aware of the availability, but also of the location and available path link quality of its peers and services. This thesis proposes a wireless location-aware Chord-based overlay mechanism for Wireless Mesh Networks (WILCO) based on a novel geographical multi-level ID mapping and an improved finger table. The proposed scheme exploits the location information of mesh routers to decrease the number of hops the overlay messages traverse in the physical topology. Analytical and simulation results demonstrate that in comparison to the original Chord, WILCO has significant benefits: it reduces the number of lookup messages, has symmetric lookup on keys in both the forward and backward direction of the Chord ring and achieves a stretch factor of O(1). On top of this location-aware overlay, a WILCO-based novel video segment seeking algorithm is proposed to make use of the multi-level WILCO ID location-awareness to locate and retrieve requested video segments from the nearest peer in order to improve video quality. An enhanced version of WILCO segment seeking algorithm (WILCO+) is proposed to mitigate the sometimes suboptimal selection of the WILCO video segment seeking algorithm by extracting coordinates from WILCO ID to enable location-awareness. Analytical and simulation results illustrate that the proposed scheme outperforms the existing state-of-the-art solutions in terms of PSNR and packet loss with different background traffic loads. While hop count is frequently strongly correlated to Quality of Service, the link quality of the underlying network will also have a strong influence on content retrieval quality. As a result, a Cross-layer Wireless Link Quality-aware Overlay peer selection mechanism (WLO) is proposed. The proposed cross-layer mechanism uses a Multiplication Selector Metric (MSM) to select the best overlay peer. The proposed MSM overcomes the two issues facing the traditional summation-based metric, namely, the difficulty of bottleneck link identification and the influence of hop count on behavior. Simulation results show that WLO outperforms the existing state-of-the-art solutions in terms of video quality at different background loads and levels of topology incompleteness. Real life emulation-based tests and subjective video quality assessments are also performed to show that the simulation results are closely matched by the real-life emulation-based results and to illustrate the significant impact of overlay peer selection on the user perceived video quality