Paper Info
Title
Delay Guaranteed Energy-efficient Computation Offloading for Industrial IoT in Fog Computing
Abstract
Fog computing emerges as a promising mode to meet the stringent requirement of low latency in industrial Internet of Things (IIoT). By offloading partial computation-intensive tasks from fog node to cloud server, the computation experience of users can be further improved in fog computing system. In this paper, we develop an energy-efficient computation offloading scheme for IIoT in fog computing scenario. The purpose is to minimize energy consumption when computation tasks are accomplished within a desired energy overhead and delay. It has a comprehensive consideration on the components of energy consumption at fog node, which includes the energy consumption of local computing, transmitting and waiting states. To address this energy minimization problem, an accelerated gradient algorithm is proposed, it can find the optimal offloading ratio with a fast speed that improves the convergence speed of traditional method. Finally, the numerical results reveal that the proposed offloading scheme is superior to the local computing and full offloading schemes in terms of energy consumption and completion time, and further confirm the advantage of convergence rate.
Year
DOI
Venue
2019
10.1109/ICC.2019.8761199
IEEE International Conference on Communications
Keywords
Field
DocType
Computation offloading,fog computing,energy efficiency,industrial Internet of Things
Convergence (routing),Computer science,Fog computing,Computation offloading,Real-time computing,Rate of convergence,Latency (engineering),Energy consumption,Energy minimization,Computation
Conference
ISSN
Citations 
PageRank 
1550-3607
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Siguang Chen16312.91
Yimin Zheng200.34
Kun Wang342556.96
Weifeng Lu4102.50