TY - JOUR
T1 - POST
T2 - Parallel Offloading of Splittable Tasks in Heterogeneous Fog Networks
AU - Liu, Zening
AU - Yang, Yang
AU - Wang, Kunlun
AU - Shao, Ziyu
AU - Zhang, Junshan
N1 - Funding Information:
Manuscript received July 22, 2019; revised September 26, 2019, November 5, 2019, and December 15, 2019; accepted January 1, 2020. Date of publication January 10, 2020; date of current version April 14, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 61801463; in part by the National Key Research and Development Program of China under Grant YFB0102104; in part by the Nature Science Foundation of Shanghai under Grant 19ZR1433900; and in part by the State Scholarship Fund of China Scholarship Council under Grant 201908310166. (Corresponding author: Kunlun Wang.) Zening Liu is with the School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China, also with the Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China, also with the University of Chinese Academy of Sciences, Beijing 100049, China, and also with the Shanghai Institute of Fog Computing Technology, Shanghai 201210, China.
Publisher Copyright:
© 2014 IEEE.
PY - 2020/4
Y1 - 2020/4
N2 - Fog computing has been promoted to support delay-sensitive applications in future Internet of Things (IoT). For a general heterogeneous fog network consisting of many dispersive fog nodes (FNs), it may well happen that some of them have delay-sensitive tasks to process, i.e., task nodes (TNs), and some have spare resources to help the TNs to process tasks, i.e., helper nodes (HNs). It remains a fundamental challenge to effectively map multiple tasks or TNs into multiple HNs to minimize every task's service delay in a distributed manner, i.e., the multitask multihelper (MTMH) problem. The problem becomes more challenging as tasks are splittable, i.e., tasks can be divided into multiple subtasks and offloaded to multiple HNs to further reduce the service delay via the scheme similar to distributed computing, because it introduces the more complicated task division problem which results in a much larger and more complex solution space. To tackle this challenge, in this article, a generalized Nash equilibrium problem (GNEP), called parallel offloading of splittable tasks (POST), is formulated and studied thoroughly. The structural properties of the problem are characterized and thus the existence of generalized Nash equilibrium (GNE) is proven via the fixed-point theorem. Furthermore, the corresponding distributed task offloading algorithm is developed via the Gauss-Seidel-type method. The simulation results show that the proposed POST algorithm can offer much better performance in terms of the system average delay, individual delay, delay reduction ratio (DRR), and number of beneficial TNs, compared with the existing solution to the counterpart problem for nonsplittable tasks.
AB - Fog computing has been promoted to support delay-sensitive applications in future Internet of Things (IoT). For a general heterogeneous fog network consisting of many dispersive fog nodes (FNs), it may well happen that some of them have delay-sensitive tasks to process, i.e., task nodes (TNs), and some have spare resources to help the TNs to process tasks, i.e., helper nodes (HNs). It remains a fundamental challenge to effectively map multiple tasks or TNs into multiple HNs to minimize every task's service delay in a distributed manner, i.e., the multitask multihelper (MTMH) problem. The problem becomes more challenging as tasks are splittable, i.e., tasks can be divided into multiple subtasks and offloaded to multiple HNs to further reduce the service delay via the scheme similar to distributed computing, because it introduces the more complicated task division problem which results in a much larger and more complex solution space. To tackle this challenge, in this article, a generalized Nash equilibrium problem (GNEP), called parallel offloading of splittable tasks (POST), is formulated and studied thoroughly. The structural properties of the problem are characterized and thus the existence of generalized Nash equilibrium (GNE) is proven via the fixed-point theorem. Furthermore, the corresponding distributed task offloading algorithm is developed via the Gauss-Seidel-type method. The simulation results show that the proposed POST algorithm can offer much better performance in terms of the system average delay, individual delay, delay reduction ratio (DRR), and number of beneficial TNs, compared with the existing solution to the counterpart problem for nonsplittable tasks.
KW - Fog computing
KW - generalized Nash equilibrium problem (GNEP)
KW - multitask multihelper (MTMH)
KW - splittable tasks
KW - task offloading
UR - http://www.scopus.com/inward/record.url?scp=85083731042&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85083731042&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2020.2965566
DO - 10.1109/JIOT.2020.2965566
M3 - Article
AN - SCOPUS:85083731042
SN - 2327-4662
VL - 7
SP - 3170
EP - 3183
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 4
M1 - 8956076
ER -