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

Abstract

In this paper, we study the coexistence and synergy between edge and central cloud computing in heterogeneous cellular networks (HetNets), in which multi-antenna small base stations (SBSs) empowered by clouds at the edge offer computing services for user equipments (UEs), whereas a macro base station (MBS) provides computing services from a central cloud via a high-speed backhaul.With processing latency constraints at the edge cloud and backhaul, we aim to minimize the network energy consumption (the energy used for task offloading as well as computation) through jointly optimizing the cloud selection, the UE's transmit power, the SBS's receive beamformer, and the SBS's transmit covariance matrix. We devise a tractable solution that can achieve great performance gain over conventional schemes. With large-scale antennas at the MBS, the massive multiple-input multipleoutput (MIMO) backhaul can significantly reduce the complexity of our algorithm and obtain even better performance.

UAV-Assisted Relaying and Edge Computing: Scheduling and Trajectory Optimization

“…The rationale behind MEC is that UEs' computing tasks can be offloaded and completed at the edge of wireless networks by deploying cloud servers at the access points (APs), so as to liberate the UEs from heavy computing workloads and prolong their battery lifetime [3,4]. Recently, MEC has been widely used in cellular networks, focusing on improving the energy efficiency or reducing the latency of various cellular-based MEC systems [5][6][7][8][9][10][11][12][13][14]. A multicell MEC system was studied in [5], where the total energy consumption was minimized by jointly optimizing the radio and computational resources.…”

“…Later in [7], the scenario of a UE with multiple tasks was considered, where multiple APs assisted the UE to reduce its total task execution latency and energy consumption. A two-tier heterogeneous network with the coexistence of edge and central cloud computing was studied in [8], and the cloud selection was optimized to minimize the network's energy consumption. In [9], a device-todevice (D2D) fogging was explored to achieve energy-efficient task completion by sharing computation and communication resources amongst mobile devices.…”

Joint Beamforming and Computation Offloading for Multi-User Mobile-Edge Computing

“…, c K ] T is the offloading decisions of all MDs. P k max is the maximum transmit power of MD k. Note that in (5), the constraint (5b) guarantees that the offloading decision of each MD is binary variable. Constraint (5c) denotes the maximum transmission power of each MD, and constraint (5d) indicates the maximum tolerable delay.…”

“…Multi-antenna based energy harvesting strategy was introduced into MEC system [4] to enhance the computation capability and prolong the operation time of MDs. To realize wireless backhaul and exploit benefits from multi-antenna, the authors in [5] proposed to use receive beamforming at a multi-antenna BS, while multiple single antenna MDs transmit by using orthogonal multiple access techniques such as time/frequency-division. To improve the computation offloading efficiency, the authors in [6] utilized multi-antenna at both MD and BS to realize MIMO transmission.…”

Wireless-Powered Mobile Edge Computing with Cooperated UAV

“…To deal with this issue, the mobile edge computing (MEC) has emerged as a promising technology to provide cloud computing services for UEs at the edge of communication networks [1], e.g., at the access points (APs). The energy efficiency and latency are two important criteria for MEC works [2][3][4][5], where the energy computation or the latency (or the cost including both the energy and latency) for completing the UEs' computation tasks is minimized by jointly optimizing the radio and computing resource allocation. However, the traditional battery-based UEs cannot take full advantage of the edge computing when their energy is running out, and thus the technology of wireless power transfer (WPT) has been leveraged in a mass of works [6][7][8] to improve the efficiency of MEC.…”