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Edge and Central Cloud Computing: A Perfect Pairing for High Energy Efficiency and Low-Latency

Hu, X; Wang, L; Wong, KK; Tao, M; Zhang, Y; Zheng, Z; (2020) Edge and Central Cloud Computing: A Perfect Pairing for High Energy Efficiency and Low-Latency. IEEE Transactions on Wireless Communications , 19 (2) pp. 1070-1083. 10.1109/TWC.2019.2950632. Green open access

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Abstract

In this paper, we study the coexistence and synergy between edge and central cloud computing in a heterogeneous cellular network (HetNet), which contains a multi-antenna macro base station (MBS), multiple multi-antenna small base stations (SBSs) and multiple single-antenna user equipment (UEs). The SBSs are empowered by edge clouds offering limited computing services for UEs, whereas the MBS provides high-performance central cloud computing services to UEs via a restricted multiple-input multiple-output (MIMO) backhaul to their associated SBSs. With processing latency constraints at the central and the edge networks, we aim to minimize the system energy consumption used for task offloading and computation. The problem is formulated by jointly optimizing the cloud selection, the UEs’ transmit powers, the SBSs’ receive beamformers, and the SBSs’ transmit covariance matrices, which is a mixed-integer and non-convex optimization problem. Based on the methods such as decomposition approach and successive pseudoconvex approach, a tractable solution is proposed via an iterative algorithm. The simulation results show that our proposed solution can achieve great performance gain over conventional schemes using edge or central cloud alone. Also, with large-scale antennas at the MBS, the massive MIMO backhaul can significantly reduce the complexity of the proposed algorithm and obtain even better performance.

Type: Article
Title: Edge and Central Cloud Computing: A Perfect Pairing for High Energy Efficiency and Low-Latency
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TWC.2019.2950632
Publisher version: http://dx.doi.org/10.1109/TWC.2019.2950632
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Cloud computing, Edge computing, Task analysis, Wireless communication, Computer architecture
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10093398
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