Open AccessTeaching Learning Based Optimization (TLBO) for energy efficiency in Fog Computing
Author(s) -
Amanpreet Kaur,
Heena Wadhwa,
Pardeep Singh,
Harpreet Kaur Toor
Publication year - 2021
Publication title -
cgc international journal of contemporary technology
Language(s) - English
Resource type - Journals
ISSN - 2582-0486
DOI - 10.46860/cgcijctr.2021.12.31.248
Subject(s) - computer science , energy consumption , latency (audio) , efficient energy use , fog computing , process (computing) , shortest path problem , real time computing , energy (signal processing) , simulation , distributed computing , embedded system , engineering , internet of things , telecommunications , graph , statistics , operating system , mathematics , theoretical computer science , electrical engineering
Fog Computing is eminent to ensure quality of service in handling huge volume and variety of data and to display output, or for closed loop process control. It comprises of fog devices to manage huge data transmission but results in high energy consumption, end-to end-delay, latency. In this paper, an energy model for fog computing environment has been proposed and implemented based on teacher student learning model called Teaching Learning Based Optimization (TLBO) to improve the responsiveness of the fog network in terms of energy optimization. The results show the effectiveness of TLBO in choosing the shortest path with least energy consumption.