mobile edge computing

6G in the sky: On‐demand intelligence at the edge of 3D networks

Sixth generation will exploit satellite, aerial, and terrestrial platforms jointly to improve radio access capability and unlock the support of on-demand edge cloud services in three-dimensional (3D) space, by incorporating mobile edge computing (MEC) functionalities on aerial platforms and low-orbit satellites. This will extend the MEC support to devices and network elements in the sky and forge a space-borne MEC, enabling intelligent, personalized, and distributed on-demand services.

Where, when, and how mmWave is used in 5G and beyond

Wireless engineers and business planners commonly raise the question on where, when, and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next generation network is not just a new radio access standard, but also an integration of networks for vertical markets with diverse applications, answers to the question depend on scenarios and use cases to be deployed. This paper gives four 5G mmWave deployment examples and describes in chronological order the scenarios and use cases of their probable deployment, including expected system architectures and hardware prototypes.

Enabling effective mobile edge computing using millimeterwave links

Mobile Edge Computing (MEC) plays a key role in the 5G roadmap, as a way to bring information technology (IT) services closer to the mobile users by empowering radio access points with additional functionalities, like caching or computation offloading capabilities. At the physical layer, some of the key technologies enabling very low latency mobile services are dense deployment of radio access points, massive MIMO and millimeter-wave (mmW) communications for radio access as well as for radio fronthaul/backhaul.

Latency-constrained dynamic computation offloading with energy harvesting IoT devices

In this paper, we address the problem of dynamic computation offloading with Multi-Access Edge Computing (MEC), considering an Internet of Things (IoT) environment where computation requests are continuously generated locally at each device, and are handled through dynamic queue systems. In such context, we consider simple devices (e.g., sensors) with limited battery and energy harvesting capabilities.

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