Wireless Edge Computing With Latency and Reliability Guarantees

By Mohammed S. Elbamby, Cristina Perfecto, Chen-Feng Liu, Jihong Park, Sumudu Samarakoon, Xianfu Chen, Medhi Bennis. 2019

149 citations recorded by the source corpus.

Edge computing is an emerging concept based on distributed computing, storage, and control services closer to end network nodes. Edge computing lies at the heart of the fifth-generation (5G) wireless systems and beyond. While the current state-of-the-art networks communicate, compute, and process data in a centralized manner (at the cloud), for latency and compute-centric applications, both radio access and computational resources must be brought closer to the edge, harnessing the availability of computing and storage-enabled small cell base stations in proximity to the end devices. Furthermore, the network infrastructure must enable a distributed edge decision-making service that learns to adapt to the network dynamics with minimal latency and optimize network deployment and operation accordingly. This paper will provide a fresh look to the concept of edge computing by first discussing the applications that the network edge must provide, with a special emphasis on the ensuing challenges in enabling ultrareliable and low-latency edge computing services for mission-critical applications such as virtual reality (VR), vehicle-to-everything (V2X), edge artificial intelligence (AI), and so on. Furthermore, several case studies where the edge is key are explored followed by insights and prospect for future work.

Subfields: Computer Networks and Communications

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In Computer Networks and Communications

Citations in the corpus

Harnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learning (2020, methodology): “In this experiment, we assume that there are sufficient subcarriers to upload every update in one time slot, and focus on wireless communication energy consumption that often exceeds computing energy [25].”
Wireless Network Intelligence at the Edge (2018, background): “The bottleneck is the offloading communication overhead, and optimizing such a computation–communication tradeoff is a large field of research in mobile edge computing (MEC) [119]–[122].”
Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications (2020, background): “In this case, as studied in [119], an effective solution could be scheduling the resultant stragglers while offloading their computationally demanding tasks (or even training data with a loss of privacy) to neighbors or edge servers, a conceptual design known as mobile edge computing (MEC) [120], [1”
Computer Science Review (unknown): “Edge computing systems often rely on wireless networks, which can be subject to interference, channel stochasticity, and signal attenuation [12], leading to fluctuating bandwidth, intermittent connectivity, and unpredictable delays.”