Self-Sustaining Caching Stations: Towards Cost-Effective 5G-Enabled Vehicular Networks

In this article, we investigate the cost-effective 5G-enabled vehicular networks to support emerging vehicular applications, such as autonomous driving, in-car infotainment and location-based road services. To this end, self-sustaining caching stations (SCSs) are introduced to liberate on-road base stations from the constraints of power lines and wired backhauls. Specifically, the cache-enabled SCSs are powered by renewable energy and connected to core networks through wireless backhauls, which can realize "drop-and-play" deployment, green operation, and low-latency services. With SCSs integrated, a 5G-enabled heterogeneous vehicular networking architecture is further proposed, where SCSs are deployed along roadside for traffic offloading while conventional macro base stations (MBSs) provide ubiquitous coverage to vehicles. In addition, a hierarchical network management framework is designed to deal with high dynamics in vehicular traffic and renewable energy, where content caching, energy management and traffic steering are jointly investigated to optimize the service capability of SCSs with balanced power demand and supply in different time scales. Case studies are provided to illustrate SCS deployment and operation designs, and some open research issues are also discussed.Comment: IEEE Communications Magazine, to appea

High-throughput, big data and complexity in clinical proteomics: an interview with Jasminka Godovac-Zimmermann

Interview with Professor Jasminka Godovac-Zimmermann, PhD by Claire Raison (Commissioning Editor) Professor Jasminka Godovac-Zimmermann is Head of the Proteomics and Molecular Cell Dynamics Group at University College London, UK. Professor Godovac-Zimmermann trained at the Max Planck Institute of Biochemistry, Germany, and specialized in protein chemistry. Her research focuses on proteomics in cancer and systems biology. Here she talks about the clinical impact of her work and her hopes and predictions for how proteomics and diagnostics could work together in future