conference-paper

ESACR: An Energy Saving Approach from Cloud Resources for Green Cloud Environment

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Abstract

Cloud is most recognized environment of computing due to the widely availability of its services to the users. Cloud data centers have adopted virtualization of resources technically known as virtual machines (VMs) for the effective and efficient computation of services. But power consumption through the cloud data centers (CDCs) highlighted as one of the major issues responsible to reduce the quality of services of Cloud computing. Because a large number of electronic resources like processing nodes, servers, disk storage, and networking nodes (i.e. switch/routers) in CDC consume a high degree of energy during computation. Energy is also consumed by cooling plants to cool the data centers as it produces a huge amount of heat (CO2) surrounding it. Due to the high energy consumption, the cloud providers pay a high cost of energy computation and it also contributes more carbon emissions to the atmosphere. Reducing energy consumption and CO2emission is a major challenge in turning the computation from cloud computing to green computing. So, our main focus in this paper is to develop an energy-saving approach for cloud computing based on resource management. Due to variations in the request of services by the users, the demand for resources also varies during the computation. The amount of users’ request are not always same for all 24 hours in a day. Some period of time it is very low and at that period of time, many resources become idle and consume some fixed amount of energy that is a wastage of energy. In this manner, the proposed ESACR approach first define active (required) and idle (non-required) resources as per the users’ request for services at any instance; after that, it converts the idle resources into an energy-saving mode (i.e., turn OFF) unless it is not required for the service of users’ request. So that the saving of energy will increased, if at any instance all non-useable resources is define in OFF mode.

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Publication details

DOI
10.1109/smart52563.2021.9676249
OpenAlex
W4205701366
Document type
conference-paper
Language
EN
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