TY - JOUR
T1 - Hierarchical Offloading for Delay-Constrained Applications in Fog RAN
AU - Guo, Kun
AU - Sheng, Min
AU - Tang, Jianhua
AU - Quek, Tony Q.S.
AU - Qiu, Zhiliang
N1 - Funding Information:
Manuscript received May 17, 2019; revised September 30, 2019 and December 26, 2019; accepted January 23, 2020. Date of publication February 10, 2020; date of current version April 16, 2020. This work was supported in part by the Natural Science Foundation of China under Grant 61725103 and Grant 91638202, in part by the Shaanxi Innovation under Grant 2017KCT-30-03, in part by the Key Industry Innovation Chain of Shaanxi under Grant 2017ZDCXL-GY-04-04, in part by the National S&T Major Project under Grant 2018ZX03001014-004, and in part by the SUTD Growth Plan Grant for AI. The review of this article was coordinated by Dr. S. Misra. (Corresponding author: Min Sheng.) Kun Guo, Min Sheng, and Zhiliang Qiu are with the State Key Laboratory of ISN, Xidian University, Xi’an 710071, China (e-mail: guokun1218@ foxmail.com; [email protected]; [email protected]).
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2020/4
Y1 - 2020/4
N2 - By computation offloading, fog radio access network (RAN) can support delay-constrained applications, since such a hierarchical network architecture enables parallel computing at local computing layer (LCL), edge computing layer (ECL), and cloud computing layer (CCL). Comparing to processing applications exclusively at the LCL, the assistance of processing at the ECL and the CCL can reduce computation latency, while introduce extra communication latency. These two latency are not only influenced by the hierarchical offloading decision but also by the available communication and computational resources at multiple computing layers. In this regard, this paper aims to jointly provision communication and computational resources for a powerful hierarchical offloading mechanism in fog RAN to complete delay-constrained applications with high-efficiency resource utilization. Specifically, we formulate a deadline-constrained energy minimization problem, which is followed by feasibility analysis, effective solution, and application extension. Through theoretical analyses and simulation results, we provide some insights on hierarchical offloading conditions and demonstrate advantages of our proposed algorithms in terms of the minimum affordable latency, total energy consumption, and scalability.
AB - By computation offloading, fog radio access network (RAN) can support delay-constrained applications, since such a hierarchical network architecture enables parallel computing at local computing layer (LCL), edge computing layer (ECL), and cloud computing layer (CCL). Comparing to processing applications exclusively at the LCL, the assistance of processing at the ECL and the CCL can reduce computation latency, while introduce extra communication latency. These two latency are not only influenced by the hierarchical offloading decision but also by the available communication and computational resources at multiple computing layers. In this regard, this paper aims to jointly provision communication and computational resources for a powerful hierarchical offloading mechanism in fog RAN to complete delay-constrained applications with high-efficiency resource utilization. Specifically, we formulate a deadline-constrained energy minimization problem, which is followed by feasibility analysis, effective solution, and application extension. Through theoretical analyses and simulation results, we provide some insights on hierarchical offloading conditions and demonstrate advantages of our proposed algorithms in terms of the minimum affordable latency, total energy consumption, and scalability.
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U2 - 10.1109/TVT.2020.2972734
DO - 10.1109/TVT.2020.2972734
M3 - Article
AN - SCOPUS:85083812935
SN - 0018-9545
VL - 69
SP - 4257
EP - 4270
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 4
M1 - 8988183
ER -