Open AccessTask arrival based energy efficient optimization in smart-IoT data center
Author(s) -
Bin Wang,
Fagui Liu
Publication year - 2021
Publication title -
mathematical biosciences and engineering
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2021138
Subject(s) - computer science , cloud computing , data center , internet of things , efficient energy use , energy consumption , scheduling (production processes) , distributed computing , real time computing , task (project management) , mathematical optimization , computer network , embedded system , engineering , operating system , mathematics , electrical engineering , systems engineering
With the growth and expansion of cloud data centers, energy consumption has become an urgent issue for smart cities system. However, most of the current resource management approaches focus on the traditional cloud computing scheduling scenarios but fail to consider the feature of workloads from the Internet of Things (IoT) devices. In this paper, we analyze the characteristic of IoT requests and propose an improved Poisson task model with a novel mechanism to predict the arrivals of IoT requests. To achieve the trade-off between energy saving and service level agreement, we introduce an adaptive energy efficiency model to adjust the priority of the optimization objectives. Finally, an energy-efficient virtual machine scheduling algorithm is proposed to maximize the energy efficiency of the data center. The experimental results show that our strategy can achieve the best performance in comparison to other popular schemes.