Green Energy in Data Centers Using Internet of Things

Green Energy in Data Centers Using Internet of Things

Vasaki Ponnusamy, Bobby Sharma, Gan Ming Lee
Copyright: © 2021 |Pages: 22
DOI: 10.4018/978-1-7998-6709-8.ch010
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Abstract

Green energy infrastructure with the internet technologies relies on five important domains: green machine to machine (M2M), green cloud computing (CC), green data center (DC), green ICT, and green cellular. The ever-increasing demand for cloud computing and heavy dependence on cloud for storage, processing, and applications results in the need for more data centers with high capacity. Power management using wireless sensor networks (WSN) can be a potential solution as there has been a lot of works suing WSN for power management for green buildings, green home, and green farming. The same design can be applied to data centers with modifications to cater for data centers. Since WSN is part of IoT, various IoT-related solutions can be proposed for green data center solutions. A hybrid model that consists of virtualization, cooling systems, and IoT shows energy efficient data center designs. There have been various efforts as such, and this research will present green energy designs and mainly IoT-related initiatives for green-aware data centers.
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Problem Statement

In today’s technological world, it is proven that there is a significant relationship between data center and investment in capital overlay and outgoing costs. Table 1 shows the detailed breakdown on the distribution of the cost from data center (Greenberg et al., 2008).

The design of computing system is being optimized based on the execution time and operates at low consumption due to entrapment of resources and fragmentation of data. No concern was made for the issue of energy consumption by the system. Uncontrolled usage of energy in data centers has negative effects on the reliability, density, scalability of information processing and the environment. Need and awareness are raised across nation through multiple solution and disciplines to optimize and save energy use in data management system (Barroso. L.A, 2005). System or even its components like CPUs, memory and disk are hardly distributing energy efficiently. It trades power for performance (US Department, 2013). Power management has become a critical issue due to large energy usage and all over the world government has started imposing the taxes on the carbon emission, ultimately aiming to reduce the emission and help make computing into green computing (Bansal et al., 2011).

Although research was conducted in designing power aware applications, an effort for implementing has not been taken place. Large expenses and allocations need to be augmented when data center reaches maximum provisioned power (Bansal et al., 2011). In the very near future, energy efficiency is expected to be one of the key procuring arguments in the society. Research should focus in building power-aware database management systems (DBMS) or GreenDB.

Table 1.
Guide On The Distribution Of Data Center Costs.
Amortized CostComponentSub-component
~ 45%ServersCPU, memory, storage systems.
~ 25%InfrastructurePower distribution and cooling.
~15%Power drawElectrical utility costs.
~15%NetworkLinks, transit, equipment.

a. Source of data: A. Greenberg et al, “The cost of a cloud: research problems in data center networks”, ACM SIGCOMM Computer Communication Review, 39(1), pp. 68, 2008

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