Research On Key Technologies Of Crowd Sensing And Service In The Internet Of Vehicles

The Internet of Vehicles(IoV)is a derivative of the Internet of Things(IoT)and mobile Internet in the field of transportation.By leveraging state-of-the-art communication and information technologies,IoV can fully connect vehicles with other vehicles,humans,roads,and service platforms,thereby facilitating intelligent information exchanging among these entities.IoV can largely in-crease the intelligence of vehicles,therefore it is a promising paradigm to real-ize automated driving,intelligent transportation,and smart city.The collective intelligence of vehicles can break through the limitations of single vehicle which include sensing accuracy and range,and communication,computing and storage capability.To this end,we fully exploit the collaboration between vehi-cles,clouds,and edges to improve the quality of sensing and service in IoV,while reducing sensing and communication overhead.In this article,our main concerns include the following:regional crowd sensing and effective infor-mation dissemination in IoV;cost-effective global crowd sensing in IoV;and context-aware service data delivery in IoV.Our study yields following results:1)In terms of the regional crowd sensing and service,we propose a traffic condition sensing and traffic information dissemination method based on the collaboration among vehicles,which can improve the accuracy,timeliness,and effectiveness of traffic information.Specifically,each vehicle collects periodic beacons to build its individual view of the traffic condition.Then vehicles fuse their individual views via chain collaboration to build a comprehensive,accu-rate and consistent view of the traffic situation.Furthermore,we propose a ki-netic-energy-based spatiotemporal information effectiveness model,which dy-namically controls the dissemination range and effect strength of the traffic in-formation,to avoid information overload.The experiments using traffic simu-lation software demonstrate that the proposed method can cost-effectively per-form traffic condition sensing as well as information dissemination,and then largely improve urban transport efficiency.2)In terms of the global crowd sensing,we propose a cost-effective,large-scale,fine-grained urban environment sensing method,which can deal with the uneven spatiotemporal distribution of sensing resources.This method utilizes probabilistic matrix factorization to reveal the latent features of sensing data and to predict the missing sensing data.Then,based on these latent features,the method uses entropy and mutual information to select representative sens-ing areas,thereby improving sensing efficiency.Additionally,the method con-siders the distribution of sensing resources when performing sensing task as-signment.Furthermore,the method designs a checkpoint mechanism to super-vise the sensing progress,which can guarantee sensing quality.The experi-ments using taxicab trajectory data show that the proposed method can signifi-cantly improve sensing quality while reducing sensing as well as communica-tion costs.3)In terms of the global IoV service,we propose an edge-assisted space-and-time-constrained service data delivery method,which can empower cellu-lar networks to meet the massive data requirements of various IoV services.Taking advantage of the computing and storage capability at base stations,this method adopts time series analysis to forecast service demands and cache pop-ular contents accordingly.Then we propose a space-and-time-constrained data offloading algorithm.The algorithm builds probabilistic contact graph to rep-resent communication opportunities among vehicles.Moreover,an offloading tree is extracted from the probabilistic contact graph to evaluate vehicles' in-fluence on opportunistic dissemination.Finally,the most influential vehicles are heuristically selected as offloading seeds to bootstrap or boost the data dis-semination among vehicles.The experiments using opportunistic network sim-ulator with a real road network demonstrate that the proposed method can sig-nificantly relief the overloaded cellular networks while ensuring the spatiotem-poral constraints on IoV service content delivery.