TY - GEN
T1 - Optimal Scheduling of IoT Tasks in Cloud-Fog Computing Networks
AU - He, Zhiming
AU - Zhao, Qiang
AU - Mei, Haoran
AU - Peng, Limei
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - The huge volume of IoT data generated by emerging IoT end devices have triggered the prosperous development of Fog computing in the past years, mainly due to their real-time requirements. Fog computing aims at forming the idle edge devices that are in the vicinity of IoT end devices as instantaneous small-scale Fog networks (Fogs), so as to provide one-hop services to satisfy the real-time requirement. Since Fogs may consist of only wireless nodes, only wired nodes or both of them, it is significant to map IoT tasks with diverse QoS requirements to appropriate types of Fogs, in order to optimize the overall Fog performance in terms of the OPEX cost and transmission latency. Regarding this, we propose an integer linear programming (ILP) model to optimally map the IoT tasks to different Fogs and/or Cloud, taking into consideration of the task mobility and real-time requirements. Numerical results show that the real-time and mobility requirements have significant impact on the OPEX cost of the integrated Cloud-Fog (iCloudFog) framework.
AB - The huge volume of IoT data generated by emerging IoT end devices have triggered the prosperous development of Fog computing in the past years, mainly due to their real-time requirements. Fog computing aims at forming the idle edge devices that are in the vicinity of IoT end devices as instantaneous small-scale Fog networks (Fogs), so as to provide one-hop services to satisfy the real-time requirement. Since Fogs may consist of only wireless nodes, only wired nodes or both of them, it is significant to map IoT tasks with diverse QoS requirements to appropriate types of Fogs, in order to optimize the overall Fog performance in terms of the OPEX cost and transmission latency. Regarding this, we propose an integer linear programming (ILP) model to optimally map the IoT tasks to different Fogs and/or Cloud, taking into consideration of the task mobility and real-time requirements. Numerical results show that the real-time and mobility requirements have significant impact on the OPEX cost of the integrated Cloud-Fog (iCloudFog) framework.
KW - Cloud computing
KW - Fog computing
KW - IoT
KW - Mobility
KW - Real-time
UR - http://www.scopus.com/inward/record.url?scp=85097369405&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-56178-9_8
DO - 10.1007/978-3-030-56178-9_8
M3 - Conference contribution
AN - SCOPUS:85097369405
SN - 9783030561772
T3 - Studies in Computational Intelligence
SP - 103
EP - 112
BT - Artificial Intelligence and Robotics
A2 - Lu, Huimin
PB - Springer Science and Business Media Deutschland GmbH
T2 - 4th International Symposium on Artificial Intelligence and Robotics, ISAIR2019
Y2 - 20 August 2019 through 24 August 2019
ER -