An Efficient Container Management Scheme for Resource-Constrained Intelligent IoT Devices

被引:18
|
作者
Chhikara, Prateek [1 ,2 ,3 ]
Tekchandani, Rajkumar [1 ,2 ,3 ]
Kumar, Neeraj [1 ,2 ,3 ]
Obaidat, Mohammad S. [4 ,5 ,6 ]
机构
[1] Thapar Inst Engn & Technol, Dept Comp Sci & Engn, Patiala 147004, Punjab, India
[2] Univ Petr & Energy Studies, Sch Comp Sci, Dehra Dun 248007, Uttarakhand, India
[3] Asia Univ, Dept Comp Sci & Informat Engn, Taichung, Taiwan
[4] Univ Sharjah, Coll Comp & Informat, Sharjah, U Arab Emirates
[5] Univ Jordan, King Abdullah II Sch Informat Technol, Amman 11942, Jordan
[6] Univ Sci & Technol Beijing, Beijing 100083, Peoples R China
关键词
Containers; Cloud computing; Edge computing; Virtual machining; Logic gates; Energy consumption; Servers; Best fit; cloud data centers; container management; energy efficiency; heap data structures; IoT; CONSOLIDATION;
D O I
10.1109/JIOT.2020.3037181
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Virtualization is an essential feature in the IoT-resource-constrained environment due to which the service providers are facing challenges to minimize the energy consumption by IoT devices. Energy consumption models are pivotal in designing and optimizing energy-efficient operations to curb excessive energy consumption of IoT devices, which are an integral part of the modern data centers. A lot of research work has focused on efficient management of energy consumption by virtue of virtual machine consolidation. The existing virtualization techniques may not be suitable for this problem due to high computational overhead. As containers have been recently getting much popularity to encapsulate fog services, so they are the best candidate to handle this problem, especially for intelligent IoT devices. Keeping the focus on all these issues, in this article, we propose an energy-efficient container migration scheme by migrating the container from the source host server to the destination host server to meet the container's resource requirement. We used a novel approach to find the best destination host for container placement to solve host overload or underload problems using the best-fit container placement technique. The results obtained on the benchmark data set with respect to various performance evaluation metrics prove the efficacy of the designed scheme in comparison to the other existing state-of-the-art schemes.
引用
收藏
页码:12597 / 12609
页数:13
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