Connected cars generate a huge amount of Internet of Things (IoT) sensor information called Controller Area Network (CAN) data. Recently, there is growing interest in collecting CAN data from connected cars in a cloud system to enable life-critical use cases such as safe driving support. Although each CAN data packet is very small, a connected car generates thousands of CAN data packets per second. Therefore, real-time CAN data collection from connected cars in a cloud system is one of the most challenging problems in the current IoT. In this paper, we propose an Edge computing-enhanced network Redundancy Elimination service (EdgeRE) for CAN data collection. In developing EdgeRE, we designed a CAN data compression architecture that combines in-vehicle computers, edge datacenters and a public cloud system. EdgeRE includes the idea of hierarchical data compression and dynamic data buffering at edge datacenters for real-time CAN data collection. Across a wide range of field tests with connected cars and an edge computing testbed, we show that the EdgeRE reduces bandwidth usage by 88% and the number of packets by 99%.

Communications in locally structured wireless networks, such as ad hoc networks, will play an important role for network services and applications in the ubiquitous networking environments of the future. Most of the time, however, mobile networks are used in much the same way as fixed networks: most of the time, mobile terminals merely access information which is stored in the backbone network. Applications based on the local exchange of information gathered or generated by mobile terminals will open up many novel possibilities. A new online storage system named CAOSS facilitates such exchange and constitutes a building block for various new applications. CAOSS is a server-less system that provides high availability of data in mobile and wireless network environments. We describe CAOSS and its application in a mobile video-information-sharing system named GT. Thanks to the good performance of CAOSS, the GT system gives users a convenient and easy way to share and accumulate video data in a wireless environment. We confirm that CAOSS has strong enough performance to deal with large volumes of video data.