Smart Architecture Energy Management through Dynamic Bin-Packing Algorithms on Cloud

被引:0
|
作者
Gupta, Neha [1 ]
Gupta, Kamali [1 ]
Rani, Shalli [1 ]
Koundal, Deepika [2 ]
Zaguia, Atef [3 ]
机构
[1] Chitkara Univ, Inst Engn & Technol, Chandigarh, Punjab, India
[2] Univ Petr & Energy Studies, Sch Comp Sci, Dept Syst, Dehra Dun 248007, Uttarakhand, India
[3] Taif Univ, Coll Comp & Informat Technol, Dept Comp Sci, POB 11099, At Taif 21944, Saudi Arabia
来源
SYMMETRY-BASEL | 2021年 / 13卷 / 12期
关键词
smart-home; internet of things; cloud computing; virtualization; bin-packing technique; IOT;
D O I
10.3390/sym13122298
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Smart Home Architecture is suitable for progressive and symmetric urbanization. Data being generated in smart home appliances using internet of things should be stored in cloud where computing resources can analyze the data and generate the decisive pattern within no time. This additional requirement of storage, majorly, comprising of unfiltered data escalates requirement of host machines which carries with itself extra overhead of energy consumption; thus, extra cost has to be beard by service providers. Various static algorithms are already proposed to improve energy management of cloud data centers by reducing number of active bins. These algorithms are not able to cater to the needs of present heterogeneous requests generated in cloud machines by people of diversified work environment with adhering to the requirements of quality parameters. Therefore, the paper has proposed and implemented dynamic bin-packing approaches for smart architecture that can significantly reduce energy consumption without compromising upon makespan, resource utilization and Quality of Service (QoS) parameters. The novelty of the proposed dynamic approaches in comparison to the existing static approaches is that the proposed approach dynamically creates and dissolves virtual machines as per incoming and completed requests which is a dire need of present computing paradigms via attachment of time-frame with each virtual machine. The simulations have been performed on JAVA platform and dynamic energy utilized-best fit decreasing bin packing technique has produced better results in maximum runs.
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页数:13
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