Rajesh M. Hegde

Over the past decade, cloud computing has played a dominant role in supporting the applications we rely on today. Mobile networks have been acting mostly as communication pipes connecting users to the cloud and with each other. As we evolve toward the Internet of Things (IoT), our 5G/6G and future mobile networks must support a much wider range of applications, including vehicular networking, automated manufacturing, smart cities, drones, smart grids, e-health, and the many emerging AI-enabled applications such as Virtual Reality (VR) and Augmented Reality (AR). The cloud computing plus communication pipe model is no longer adequate for supporting these emerging applications. For example, many IoT applications cannot tolerate the delays incurred by cloud computing. The endpoints are creating a vast and ever growing amount of data that needs to be processed locally because sending all the data to the cloud will often be infeasible due to network bandwidth constraint-s and regulatory restrictions. Connecting every device directly to the cloud can often be impractical due to factors such as limited resources on the devices, software and management complexity, limited network agility and cognition, and system scalability. In such scenarios, users will desire local services. Many resource-constrained devices will also require local services to help perform many tasks that they cannot perform by themselves. Such tasks may range from computational-intensive user applications to security tasks that require heavy processing or information that the resource-constrained devices do not have. Future mobile networks will also require computing capabilities inside or close to the radio access networks (RANs) to enable advanced networking capabilities, such as establishing radio connections more timely and adjusting radio channel coding dynamically in response to changing user needs and communication environments, and allow user applications to be hosted in the RANs that are closer to the users.