TY - GEN

T1 - Mobile Edge Computing Partial Offloading Techniques for Mobile Urban Scenarios

AU - Bozorgchenani, Arash

AU - Tarchi, Daniele

AU - Emanuele Corazza, Giovanni

N1 - ©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2019/2/21

Y1 - 2019/2/21

N2 - Edge Computing refers to a recently introduced approach aiming to bring the storage and computational capabilities of the cloud to the proximity of the edge devices. Edge Computing is one of the main techniques enabling Fog Computing and Networking. Among several application scenarios, the urban scenario seems one of the most attractive for exploiting edge computing approaches. However, in an urban scenario, mobility becomes a challenge to be addressed, affecting the edge computing. By gaining from the the presence of two types of devices, Fog Nodes (FNs) and Fog-Access Points (F-APs), the idea in this paper is that of exploiting Device to Device (D2D) communications between FNs for assisting computation offloading requests between FNs and F-APs by exchanging status information related to the F-APs. With this knowledge, this paper proposes a partial offloading approach where the optimal tasks amount to be offloaded is estimated for minimizing the outage probability due to the mobility of the devices. In order to reduce the outage probability we have further considered a relaying approach among F-APs. Moreover, the impact of the number of tasks that each F-AP can manage is shown in terms of task processing delay. Numerical results show that the proposed approaches allow to achieve performance closer to the lower bound, by reducing the outage probability and the task processing delay.

AB - Edge Computing refers to a recently introduced approach aiming to bring the storage and computational capabilities of the cloud to the proximity of the edge devices. Edge Computing is one of the main techniques enabling Fog Computing and Networking. Among several application scenarios, the urban scenario seems one of the most attractive for exploiting edge computing approaches. However, in an urban scenario, mobility becomes a challenge to be addressed, affecting the edge computing. By gaining from the the presence of two types of devices, Fog Nodes (FNs) and Fog-Access Points (F-APs), the idea in this paper is that of exploiting Device to Device (D2D) communications between FNs for assisting computation offloading requests between FNs and F-APs by exchanging status information related to the F-APs. With this knowledge, this paper proposes a partial offloading approach where the optimal tasks amount to be offloaded is estimated for minimizing the outage probability due to the mobility of the devices. In order to reduce the outage probability we have further considered a relaying approach among F-APs. Moreover, the impact of the number of tasks that each F-AP can manage is shown in terms of task processing delay. Numerical results show that the proposed approaches allow to achieve performance closer to the lower bound, by reducing the outage probability and the task processing delay.

U2 - 10.1109/GLOCOM.2018.8647240

DO - 10.1109/GLOCOM.2018.8647240

M3 - Conference contribution/Paper

SN - 9781538647288

BT - 2018 IEEE Global Communications Conference (GLOBECOM)

PB - IEEE Publishing

ER -