1 Vehicles as Connected Resources: Opportunities and Challenges Soumya Kanti Datta, J´ erˆ ome H¨ arri, Christian Bonnet, Rui Pedro Ferreira Da Costa EURECOM 450 route des Chappes, 06904 Sophia Antipolis, France E-mails: {dattas, haerri, bonnet, ferreira}@eurecom.fr Abstract—With the introduction of smartphones, cloud & edge computing and mobile Internet, the automotive ecosystem is shifting towards the Internet of Vehicle (IoV). This paper looks at this evolution leading to IoV and identifies related research and engineering challenges including (i) co-existence of cloud, edge computing and data caching strategies at the edge, (ii) integration of data processing and management as IoV services and (iii) seamless interoperability among vehicular sensors, computing platforms and consumer devices. To address these challenges, we present an IoT architecture, which considers vehicles as IoT resources and provides (i) mechanisms to integrate them in an IoV ecosystem and (ii) seamless interoperation among components (e.g. vehicular sensors, computational platform and consumers). The functional elements and operational stages of the architecture also assist in maintaining interoperability among the components. I. I NTRODUCTION The consumer expectations of the automotive industry have undergone significant change during the last decade. The factors prompting the evolution include mobile Inter- net, smartphone, powerful On Board Units (OBU) and V2X communications. In parallel, the smart city initiatives are deploying infrastructure to provide better road safety and co- operative mobility management while reducing the effect on environment. According to NTT 1 , it is evident that the Auto 1.0 and Auto 2.0 ecosystems are not able to meet the smart city requirements due to the absence of powerful OBUs, V2X hardware, proper standards etc. The automotive industry is responding to the evolution with Auto 3.0. Here the focus is shifting towards (i) supporting intelligent transportation system (ITS) through V2X communications, (ii) exposing vehicular resources through web interfaces for data collection, processing, and storage and (iii) seamless communication and information exchange among vehicular gateways, edge servers, cloud systems and consumer resources. The Auto 3.0 ecosystem enables automatic vehicle infor- mation discovery and exchange with a computing systems and other vehicles. The enhanced access and core networking technologies coupled with computation on vehicular sensor data are the stepping stone for vehicles to be a part of the Internet of Things (IoT) ecosystem. Thus vehicles are considered as a resource [1] for IoT systems. An advantage 1 http://www.ntti3.com/wp-content/uploads/Automotive as a Digital Business V1.03-1.pdf of this philosophy is that the large variety of vehicular sen- sor data can now be used for pollution monitoring, traffic flow management and road intersection management, which are essential for smart city initiatives. The expanded IoT ecosystem integrates vehicular data with components from ITS, edge & cloud computing and big data paving way for Internet of Vehicles (IoV). The most important goal of IoV is to enable seamless interoperation exchange among consumer smart devices, vehicular things and external computational platforms (edge and cloud servers). At the same time, it aims to improve the computability, extensibility and sustainability of complex network systems and vehicular information flow. The goal is to reach a collaborative awareness and cognition among consumers, vehicles, IoT resources and computing platforms. Our approach is complementary to [13] as it aims at integrating IoT mechanisms such those described in the special issue in a vehicular context. This paper aims to study the IoV ecosystem and its current landscape. We identify the research and engineering challenges related to Auto 3.0 and IoV. Our research contributions are - (i) presentation of a data driven IoT architecture that addresses the identified challenges and enables seamless interoperability among consumers, vehicles and computing platforms leading to creation of an IoV ecosystem, (ii) describing a framework (that follows the architecture) and its operational phases to create IoV applications and (iii) deployment details of the framework that advocates for a distributed approach through coexistence of edge and cloud computing platforms. II. I OVLANDSCAPE A. IoV Use Cases Despite its current deployment, the success of IoT in future Smart Cities is pledged by the Industry strong tendency to create data silos and individual standards. Integrating vehicles in the IoV ecosystem will require to break these silos in order to provide critical use cases for road automation, such as rapid detection of road users, cooperative contextual map exchanges, or even decentralized traffic management. Due to the short notice capabilities, autonomous vehicles will not be able to rely only on their own internal sensors, detectors and maps. Vulnerable Road Users (VRU) detected by either another car, or available as a IoT service should be made available to them. Similarly, maps need to be constantly