Abstract
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.
Highlights
IntroductionThe invention of smart frameworks has fascinated the manual day-to-day activities and has resulted in escalation of raw digital data being generated via internet of things (web of sensors, electronic devices and software that are connected using internet for amplification of the automation process of devices) [1] and its interlinked and symmetric smart architectural devices
The invention of smart frameworks has fascinated the manual day-to-day activities and has resulted in escalation of raw digital data being generated via internet of things [1] and its interlinked and symmetric smart architectural devices
Servers are arranged in ascending order of ratio of CPU capacity/power requirement and virtual machines are arranged in descending order of CPU capacity and makes allotment of M VMs onto N servers and calculation of makespan, energy and resource utilization is done
Summary
The invention of smart frameworks has fascinated the manual day-to-day activities and has resulted in escalation of raw digital data being generated via internet of things (web of sensors, electronic devices and software that are connected using internet for amplification of the automation process of devices) [1] and its interlinked and symmetric smart architectural devices This unprecedented demand of technology driven service extraction has led to production of enormous data which has subsequently arisen a need to propose better energy management solutions. The total cost of using the smart home architecture is directly proportional to the cost of energy used in storing and analyzing the raw data on cloud data centers Mitigation of this cost highly depends upon the usage of number of active servers or bins in cloud data centres and can be efficaciously reduced by turning off extra bins, limiting the usage of extra bins for service extraction [4].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
