connected, most immersive experience witnessed thus far. The concept of content caching has been recently investigated in great detail, where the idea is to cache essential content at the edge of the network (e.g., a base station), devices, or other intermediate locations. One distinguishes between reactive and proactive caching. While the former serves end users when they request contents, the latter is proactive and anticipates users' requests. Proactive caching depends on the availability of fine-grained spatial-temporal traffic predictions. Miscellaneous information such as user's location, mobility patterns, and social behavior and connections can be further exploited to optimize the services provided to the end user. Storage will play a crucial role in AR/VR where for instance upon the arrival of a task query, the network/server needs to promptly decide whether to store the object if the same request will come in the near future or instead recompute the query from scratch if the arrival rate of the queries will be sparse in the future. Content/media location and delivery will also be important in terms of storing differ- ent qualities of the same content at various network locations. Migrating computationally intensive tasks/processes from AR/VR devices to more resource- ful cloud/fog servers is necessary in order to relax some additional computational require- ments for the low-cost devices and to extend the battery life of such devices. For this purpose, MEC is used to enable the client on-demand access to the cloud/fog resources (e.g., infrastructures, platforms, and software). While the current solutions allocate cloud- based radio and computing resources in a centralized manner, for optimal AR/VR perfor- mance, both radio access and computational resources must be brought closer to the users xcii Introduction and Background by binding the availability of small-cell base stations with proximity access to computing/ storage/memory resources. Furthermore, the network infrastructure must enable a fully dis