HOTSPOT: A UAV-Assisted Dynamic Mobility-Aware Offloading for Mobile-Edge Computing in 3-D Space

Abstract

For massive access to the Internet of Things, edge computing servers are installed on cellular ground base stations (GBSs) with fixed geographical locations, which easily suffer from traffic overload of the end user (EU) with high density and mobility. To provide reliable and flexible offloading service, unmanned aerial vehicles (UAV) are explored to assist edge computing, which relieves the computation offloading pressure of both EUs and GBS. However, most existing UAV researches focus on trajectory design to reduce offloading delay, which ignoring the variability of user distribution and the energy limitation of UAV. This article proposes a novel UAV-assisted edge computing framework, named as HOTSPOT, which locates the UAV in 3-D space according to the time-varying hot spot of user distribution and provides the corresponding edge computing offloading assistance. By formulating the UAV positioning problem into a maximum clique problem, a light-weighted deterministic algorithm is proposed based on stochastic gradient descent to search the optimal location of UAV. With the elaborate UAV position, HOTSPOT further gives an opportunistic offloading balanced scheme to reach low latency. Simulation results show that when the GBS load is 75%, HOTSPOT reduces the average offloading delay by 33%. When the GBS load reaches 90%, the average delay reduction is up to 80%.