scholarly journals Managing Energy Consumption in Distributed Data Centers using Genetic algorithm

2019 ◽  
Vol 8 (4) ◽  
pp. 6594-6597

This work shows a multi-target approach for planning vitality utilization in server farms thinking about customary and environmentally friendly power vitality information sources. Cloud computing is a developing innovation. Cloud computing offers administrations such as IaaS, SaaS, PaaS and it gives computing resources through virtualization over data network. Data center consumes huge amount of electrical energy in which it releases very high amount of carbon-di-oxide. The foremost critical challenge in cloud computing is to implement green cloud computing with the help of optimizing energy utilization. The carbon footprint is lowered while minimizing the operating cost. We know that renewable energies that are produced on-site are highly variable and unpredictable but usage of green energy is very important for the mankind using huge amount of single sourced brown energy is not suggested, so our algorithm which evolves genetically and gives practical solution in order to use renewable energy

Author(s):  
Vasaki Ponnusamy ◽  
Bobby Sharma ◽  
Gan Ming Lee

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.


2021 ◽  
Vol 12 (1) ◽  
pp. 74-83
Author(s):  
Manjunatha S. ◽  
Suresh L.

Data center is a cost-effective infrastructure for storing large volumes of data and hosting large-scale service applications. Cloud computing service providers are rapidly deploying data centers across the world with a huge number of servers and switches. These data centers consume significant amounts of energy, contributing to high operational costs. Thus, optimizing the energy consumption of servers and networks in data centers can reduce operational costs. In a data center, power consumption is mainly due to servers, networking devices, and cooling systems, and an effective energy-saving strategy is to consolidate the computation and communication into a smaller number of servers and network devices and then power off as many unneeded servers and network devices as possible.


Author(s):  
Burak Kantarci ◽  
Hussein T. Mouftah

Cloud computing aims to migrate IT services to distant data centers in order to reduce the dependency of the services on the limited local resources. Cloud computing provides access to distant computing resources via Web services while the end user is not aware of how the IT infrastructure is managed. Besides the novelties and advantages of cloud computing, deployment of a large number of servers and data centers introduces the challenge of high energy consumption. Additionally, transportation of IT services over the Internet backbone accumulates the energy consumption problem of the backbone infrastructure. In this chapter, the authors cover energy-efficient cloud computing studies in the data center involving various aspects such as: reduction of processing, storage, and data center network-related power consumption. They first provide a brief overview of the existing approaches on cool data centers that can be mainly grouped as studies on virtualization techniques, energy-efficient data center network design schemes, and studies that monitor the data center thermal activity by Wireless Sensor Networks (WSNs). The authors also present solutions that aim to reduce energy consumption in data centers by considering the communications aspects over the backbone of large-scale cloud systems.


2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Vasileios Moysiadis ◽  
Panagiotis Sarigiannidis ◽  
Ioannis Moscholios

In the emerging area of the Internet of Things (IoT), the exponential growth of the number of smart devices leads to a growing need for efficient data storage mechanisms. Cloud Computing was an efficient solution so far to store and manipulate such huge amount of data. However, in the next years it is expected that Cloud Computing will be unable to handle the huge amount of the IoT devices efficiently due to bandwidth limitations. An arising technology which promises to overwhelm many drawbacks in large-scale networks in IoT is Fog Computing. Fog Computing provides high-quality Cloud services in the physical proximity of mobile users. Computational power and storage capacity could be offered from the Fog, with low latency and high bandwidth. This survey discusses the main features of Fog Computing, introduces representative simulators and tools, highlights the benefits of Fog Computing in line with the applications of large-scale IoT networks, and identifies various aspects of issues we may encounter when designing and implementing social IoT systems in the context of the Fog Computing paradigm. The rationale behind this work lies in the data storage discussion which is performed by taking into account the importance of storage capabilities in modern Fog Computing systems. In addition, we provide a comprehensive comparison among previously developed distributed data storage systems which consist of a promising solution for data storage allocation in Fog Computing.


2020 ◽  
Vol 142 (2) ◽  
Author(s):  
Oluwaseun Awe ◽  
Jimil M. Shah ◽  
Dereje Agonafer ◽  
Prabjit Singh ◽  
Naveen Kannan ◽  
...  

Abstract Airside economizers lower the operating cost of data centers by reducing or eliminating mechanical cooling. It, however, increases the risk of reliability degradation of information technology (IT) equipment due to contaminants. IT Equipment manufacturers have tested equipment performance and guarantee the reliability of their equipment in environments within ISA 71.04-2013 severity level G1 and the ASHRAE recommended temperature-relative humidity (RH) envelope. IT Equipment manufacturers require data center operators to meet all the specified conditions consistently before fulfilling warranty on equipment failure. To determine the reliability of electronic hardware in higher severity conditions, field data obtained from real data centers are required. In this study, a corrosion classification coupon experiment as per ISA 71.04-2013 was performed to determine the severity level of a research data center (RDC) located in an industrial area of hot and humid Dallas. The temperature-RH excursions were analyzed based on time series and weather data bin analysis using trend data for the duration of operation. After some period, a failure was recorded on two power distribution units (PDUs) located in the hot aisle. The damaged hardware and other hardware were evaluated, and cumulative corrosion damage study was carried out. The hypothetical estimation of the end of life of components is provided to determine free air-cooling hours for the site. There was no failure of even a single server operated with fresh air-cooling shows that using evaporative/free air cooling is not detrimental to IT equipment reliability. This study, however, must be repeated in other geographical locations to determine if the contamination effect is location dependent.


Author(s):  
Milton Meckler

What does remain a growing concern for many users of Data Centers is their continuing availability following the explosive growth of internet services in recent years, The recent maximizing of Data Center IT virtualization investments has resulted in improving the consolidation of prior (under utilized) server and cabling resources resulting in higher overall facility utilization and IT capacity. It has also resulted in excessive levels of equipment heat release, e.g. high energy (i.e. blade type) servers and telecommunication equipment, that challenge central and distributed air conditioning systems delivering air via raised floor or overhead to rack mounted servers arranged in alternate facing cold and hot isles (in some cases reaching 30 kW/rack or 300 W/ft2) and returning via end of isle or separated room CRAC units, which are often found to fight each other, contributing to excessive energy use. Under those circumstances, hybrid, indirect liquid cooling facilities are often required to augment above referenced air conditioning systems in order to prevent overheating and degradation of mission critical IT equipment to maintain rack mounted subject rack mounted server equipment to continue to operate available within ASHRAE TC 9.9 prescribed task psychometric limits and IT manufacturers specifications, beyond which their operational reliability cannot be assured. Recent interest in new web-based software and secure cloud computing is expected to further accelerate the growth of Data Centers which according to a recent study, the estimated number of U.S. Data Centers in 2006 consumed approximately 61 billion kWh of electricity. Computer servers and supporting power infrastructure for the Internet are estimated to represent 1.5% of all electricity generated which along with aggregated IT and communications, including PC’s in current use have also been estimated to emit 2% of global carbon emissions. Therefore the projected eco-footprint of Data Centers into the future has now become a matter of growing concern. Accordingly our paper will focus on how best to improve the energy utilization of fossil fuels that are used to power Data Centers, the energy efficiency of related auxiliary cooling and power infrastructures, so as to reduce their eco-footprint and GHG emissions to sustainable levels as soon as possible. To this end, we plan to demonstrate significant comparative savings in annual energy use and reduction in associated annual GHG emissions by employing a on-site cogeneration system (in lieu of current reliance on remote electric power generation systems), introducing use of energy efficient outside air (OSA) desiccant assisted pre-conditioners to maintain either Class1, Class 2 and NEBS indoor air dew-points, as needed, when operated with modified existing (sensible only cooling and distributed air conditioning and chiller systems) thereby eliminating need for CRAC integral unit humidity controls while achieving a estimated 60 to 80% (virtualized) reduction in the number servers within a existing (hypothetical post-consolidation) 3.5 MW demand Data Center located in southeastern (and/or southern) U.S., coastal Puerto Rico, or Brazil characterized by three (3) representative microclimates ranging from moderate to high seasonal outside air (OSA) coincident design humidity and temperature.


2020 ◽  
Vol 8 (3) ◽  
pp. 69-81
Author(s):  
Nitin Chawla ◽  
Deepak Kumar ◽  
Dinesh Kumar Sharma

Cloud computing is gradually increasing its popularity in enterprise-wide organizations. Information technology organizations e.g., IBM, Microsoft, and Amazon have already shifted towards Cloud computing. Cloud-based offerings such as Software as a Service, Platform as a Service and Infrastructure as a Service (IAAS) are the most famous offerings. Most of the existing enterprise applications are deployed using an on-premise model. Organizations are looking for Cloud based offerings to deploy or upgrade their existing applications. SAP, Microsoft Dynamics, and Oracle are the most famous ERP or CRM application OEMs. These enterprise applications generate lots of data are hosted in an organization or on client data centers. Moving data from one data center to the Cloud is always a challenging tasks which cost a lot and takes much effort. This study proposes an efficient approach to optimize cost for data migration in cloud computing. This study also proposes the approach to optimize cost for data collection from multiple locations which can be processed centrally and then migrate to Cloud Computing.


2013 ◽  
Vol 427-429 ◽  
pp. 2184-2187
Author(s):  
Le Jiang Guo ◽  
Feng Zheng ◽  
Ya Hui Hu ◽  
Lei Xiao ◽  
Liang Liu

Cloud computing data centers can be called cloud computing centers. It has put forward newer and higher demands for data centers with the development of cloud computing technologies. This paper will discuss what are cloud computing data centers, cloud computing data center construction, cloud computing data center architecture, cloud computing data center management and maintenance, and the relationship between cloud computing data centers and clouds.


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