The evolution of communication networks shows a clear shift of focus from just improving the communications aspects to enabling new important services, from Industry 4.0 to automated driving, virtual/augmented reality, the Internet of Things (IoT), and so on. This trend is evident in the roadmap planned for the deployment of the fifth-generation (5G) communication networks. This ambitious goal requires a paradigm shift toward a vision that looks at communication, computation, and caching (3. C) resources as three components of a single holistic system. The further step is to bring these 3. C resources closer to the mobile user, at the edge of the network, to enable very low latency and high reliability services. The scope of this chapter is to show that signal processing techniques can play a key role in this new vision. In particular, we motivate the joint optimization of 3. C resources. Then we show how graph-based representations can play a key role in building effective learning methods and devising innovative resource allocation techniques.

The edge cloud. A holistic view of communication, computation, and caching

Sardellitti S.;
2018-01-01

Abstract

The evolution of communication networks shows a clear shift of focus from just improving the communications aspects to enabling new important services, from Industry 4.0 to automated driving, virtual/augmented reality, the Internet of Things (IoT), and so on. This trend is evident in the roadmap planned for the deployment of the fifth-generation (5G) communication networks. This ambitious goal requires a paradigm shift toward a vision that looks at communication, computation, and caching (3. C) resources as three components of a single holistic system. The further step is to bring these 3. C resources closer to the mobile user, at the edge of the network, to enable very low latency and high reliability services. The scope of this chapter is to show that signal processing techniques can play a key role in this new vision. In particular, we motivate the joint optimization of 3. C resources. Then we show how graph-based representations can play a key role in building effective learning methods and devising innovative resource allocation techniques.
2018
9780128136775
5G networks
graph-based learning
wireless communications
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12606/7228
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