TY - JOUR
T1 - Mobile-Edge Computation Offloading for Ultradense IoT Networks
AU - Guo, Hongzhi
AU - Liu, Jiajia
AU - Zhang, Jie
AU - Sun, Wen
AU - Kato, Nei
N1 - Funding Information:
Manuscript received February 9, 2018; revised April 8, 2018; accepted May 15, 2018. Date of publication May 21, 2018; date of current version January 16, 2019. This work was supported in part by the National Natural Science Foundation of China under Grant 61771374, Grant 61771373, and Grant 61601357, in part by the China 111 Project under Grant B16037, and in part by the Fundamental Research Fund for the Central Universities under Grant JB171501, Grant JB181506, Grant JB181507, and Grant JB181508. (Corresponding author: Jiajia Liu.) H. Guo, J. Liu, J. Zhang, and W. Sun are with the State Key Laboratory of Integrated Services Networks, School of Cyber Engineering, Xidian University, Xi’an 710071, China (e-mail: liujiajia@xidian.edu.cn).
Publisher Copyright:
© 2014 IEEE.
PY - 2018/12
Y1 - 2018/12
N2 - The emergence of massive Internet of Things (IoT) mobile devices (MDs) and the deployment of ultradense 5G cells have promoted the evolution of IoT toward ultradense IoT networks. In order to meet the diverse quality-of-service and quality of experience demands from the ever-increasing IoT applications, the ultradense IoT networks face unprecedented challenges. Among them, a fundamental one is how to address the conflict between the resource-hungry IoT mobile applications and the resource-constrained IoT MDs. By offloading the IoT MDs' computation tasks to the edge servers deployed at the radio access infrastructures, including macro base station (MBS) and small cells, mobile-edge computation offloading (MECO) provides us a promising solution. However, note that available MECO research mostly focused on single-tier base station scenario and computation offloading between the MDs and the edge server connected to the MBS. Little works can be found on performing MECO in ultradense IoT networks, i.e., a multiuser ultradense edge server scenario. Toward this end, we provide this paper to study the MECO problem in ultradense IoT networks, and propose a two-tier game-theoretic greedy offloading scheme as our solution. Extensive numerical results corroborate the superior performance of conducting computation offloading among multiple edge servers in ultradense IoT networks.
AB - The emergence of massive Internet of Things (IoT) mobile devices (MDs) and the deployment of ultradense 5G cells have promoted the evolution of IoT toward ultradense IoT networks. In order to meet the diverse quality-of-service and quality of experience demands from the ever-increasing IoT applications, the ultradense IoT networks face unprecedented challenges. Among them, a fundamental one is how to address the conflict between the resource-hungry IoT mobile applications and the resource-constrained IoT MDs. By offloading the IoT MDs' computation tasks to the edge servers deployed at the radio access infrastructures, including macro base station (MBS) and small cells, mobile-edge computation offloading (MECO) provides us a promising solution. However, note that available MECO research mostly focused on single-tier base station scenario and computation offloading between the MDs and the edge server connected to the MBS. Little works can be found on performing MECO in ultradense IoT networks, i.e., a multiuser ultradense edge server scenario. Toward this end, we provide this paper to study the MECO problem in ultradense IoT networks, and propose a two-tier game-theoretic greedy offloading scheme as our solution. Extensive numerical results corroborate the superior performance of conducting computation offloading among multiple edge servers in ultradense IoT networks.
KW - Edge computing
KW - Internet of Things (IoT)
KW - Mobile-edge computation offloading (MECO)
KW - Mobile-edge computing (MEC)
KW - Ultradense IoT network
KW - Ultradense network (UDN)
UR - http://www.scopus.com/inward/record.url?scp=85047182823&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85047182823&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2018.2838584
DO - 10.1109/JIOT.2018.2838584
M3 - Article
AN - SCOPUS:85047182823
SN - 2327-4662
VL - 5
SP - 4977
EP - 4988
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 6
M1 - 8361406
ER -