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Green Cloud Computing: An Approach Towards Sustainability



The future of the IT industry is at the crossroads, and unless there is no sustainable solution formulated within the industry, it would potentially be the end of the planet. Data centers within the industry consume most of the energy, and there is an immediate need for these power centers to switch towards green and clean energy. This study investigates the dynamics of Green Cloud Computing services and performs a literature review to examine the need, barriers, and trends of green cloud computing. By investigating the characteristics, barriers, and trends, the study proposes that the future of IT is deeply entrenched with green energy. The results of the study note that green cloud computing can be highly effective in enhancing the benefits of cloud computing further and mitigating its effects on the environment.
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Green Cloud Computing: An Approach Towards Sustainability
Mr. Gopala Krishna Sriram*1
*1 Software Architect, EdgeSoft Corp, McKinney, TX USA
The future of the IT industry is at the crossroads, and unless there is no sustainable solution formulated
within the industry, it would potentially be the end of the planet. Data centers within the industry
consume most of the energy, and there is an immediate need for these power centers to switch towards
green and clean energy. This study investigates the dynamics of Green Cloud Computing services and
performs a literature review to examine the need, barriers, and trends of green cloud computing. By
investigating the characteristics, barriers, and trends, the study proposes that the future of IT is deeply
entrenched with green energy. The results of the study note that green cloud computing can be highly
effective in enhancing the benefits of cloud computing further and mitigating its effects on the
Keywords: Green Cloud Computing, Cloud Service Models, Power Usage, Data Centres, Cloud Architecture, Etc.
I. Introduction
The question of sustainability is at the helm of the 21st century. This is because sustainable
development is a strategy for survival for not only humanity but also the planet. It is highlighted by
Puthal et al. [1] that one of the biggest challenges to the environment lies in the computing field. This is
due to the fact that the modern world cannot function without reliance on computing technology.
Almost all of the large businesses are moving towards the use of cloud computing for daily operations,
without which their activities would be put in serious jeopardy. In doing so, the energy consumed by
cloud computing is putting the environment at great risk. The study of Mishra et al. [2] has further
discussed this point by stating that one of the key fields which utilize energy resources is cloud
computing. Sustainable development cannot be achieved unless and until the field of cloud computing is
switched towards green energy. Green cloud computing denotes cloud computing operations that rely
on renewable energy. Because it is among the key fields in local and international business, formulating
a green cloud computing technique is at the heart of sustainable development and mitigating the impact
of climate change. However, this is a very radical field as many businesses still have cloud computing
technology that consumes energy that is not clean. Therefore, any attempt towards saving the
environment needs to start with "Green Cloud Computing' whereby all of the businesses around the
world switch from the non-renewable source of energy towards sustainable and green energy. This
paper is set out to investigate the dynamics of Green Cloud Computing. It tends to build on the circular
economy and improve the energy efficiency of the entire cloud computing industry which is deemed one
of the major contributors to global carbon emissions.
II. Related Work
Given the importance of the field, many researchers and scientists have taken up the field and
produced relevant technologies and solutions. This paper is an attempt to bring those creative solutions
to light and open a debate around the new discipline of Green Cloud Computing. The related work is
discussed below.
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Power Usage Effectiveness (PUE)
As per Atrey et al. [3], PUE is a measure of how effectively and efficiently a data center uses its
energy. It evaluates the performance of energy by calculating the ratio of energy used as a whole against
the energy utilized by the IT resources alone. It was developed by the scientists working at Green Grid,
which aims at a swift movement of data centers towards green energy. PUE is among the most
important metric for denoting the energy used and wasted at the data centers.
Green Cloud Architecture (GCA)
The study of Pandya [4] has mentioned GCA as a way of redesigning the architecture of data
centers compatible with environmental sustainability. GCA is mindful of both the energy consumed and
wasted during the day-to-day process of cloud computing. It tends to provide a long-term solution to
both private and public cloud-based services by removing the unsustainable part in the cloud
architecture and making the services more ecologically friendly.
Cloud Service Models
There is the existence of different service models that include Software as a Service (SaaS),
Storage as a Service (SaaS) and, Processing as a Service (PaaS). All these models fall within the ambit of
cloud computing, and their compatibility with the environment is critical for the future of these services
[4]. The basic function of cloud computing is to provide these three types of services, and for the
development of Green Cloud Computing, these services have to be made compliant with energy
efficiency and conservation.
III. Work Flow
To understand the dynamics of Green Cloud Computing, the study will perform a pre-
determined methodology. This entails studying different academic papers, carving out different themes
relevant to the topic, and then bringing into perspective the author's own analysis. A detailed
methodology is given below.
Research Approach
This research is approached through a qualitative framework. This means that non-numerical
data will be collected in order to make sense of the research topic. A qualitative research approach is
also focused on collecting experiences, opinions, and ideas related to the topic.
Data Collection
The primary source of data collection for this study is secondary. This means that the published
literature on the topic will be studied. This published literature will be academic work that has been
conducted all over the world by different academics and scholars.
Data Analysis
The data will be analyzed through a thematic analysis. As discussed by Neuendorf [5], a thematic
analysis allows the researcher to carve out different and most important themes for the stated topic. It
brings out important criteria related to Green Cloud Computing. The selection of these themes will be
based on their importance in the cloud computing field. As stated, the researcher plan to review
different academic material, and hence, the themes that are overlapping in these published papers will
be brought into the light.
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IV. Result and Discussion
Characteristics of Green Cloud Computing
Green Cloud Computing is a field that is still largely undeveloped, and this is the reason why
there is a need for the development of a model. This model should emphasize the key themes of cloud
computing and how it can be made viable with environmental sustainability. In this regard, the study of
Patil and Patil [6] has produced a framework on which the future of cloud computing should be
developed. This figure is given below.
Figure 1 Characteristics of Green Cloud Computing [6]
As per the above model, there are certain characteristics of the evolving field of Green Cloud
Computing. These characteristics include energy efficiency, virtualization, multi-tenancy, consolidation,
and eco-friendly. Among the most important of these characteristics, which are also not discussed in this
paper yet, are virtualization and multi-tenancy. Virtualization is a concept whereby several virtual
computers use the same abstraction process. Within the framework of Green Cloud Computing, this
would mean that multiple computers would rely on the shared tasks procession, which would then
ultimately reduce the energy consumption per computer and increase efficiency [7].
Similarly, multi-tenancy is a phenomenon that is akin to providing cloud servicing to multiple
tenants of the same category in order to avoid additional or marginal investment and energy utilized by
a distinct tenant [8]. Although this technique can have many benefits especially linked to energy
conservation, there is an immediate threat of risk of privacy between the tenants. Therefore, there is
room for further development of multi-tenancy characteristics of Green Cloud Computing. The last
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characteristic indicated in the workflow diagram is consolidation, which is highlighted by Patil and Patil
[6] as "the process of deploying different data centers related data processing applications on a single
server with virtualization technology. Broadly speaking, it means the process involved in Green Cloud
Computing and making it compatible with the sustainable development of the environment. These
processes mostly relate to the Application, Network, and Security on which the logic of cloud computing
is built.
Need for Green Cloud Computing
It is stated by Pirani [9] that IT generates around 2% of total global emissions. It is also without
doubt that the need for cloud computing would rise in the future, given the switch of analog business
models into digital arenas. As a result, the global emissions in the IT sector would also rise, which would
be contradictory to the health and safety of the planet. This might also cause the IT industry to become
one of the key polluters of carbon dioxide emissions. Hence, it is quite apparent that if the IT sector is to
develop in the future, it needs to be more sustainable and be made compliant with the environment. The
need for Green Cloud Computing is thus essential for the industry. Data centers are among the most
consumed energy centers in the IT solution, and hence, no solution of IT sustainability can be developed
without forming a sustainable solution for these data centers [10]. The study also highlights the
importance of power management and energy efficiency in the current data centers. However, there are
certain barriers to the field of Green Cloud Computing which are discussed subsequently.
Barriers towards Green Cloud Computing
The number one barrier towards large-scale implementation of Green Cloud Computing is cost.
This is discussed by Burton [11]. As per the researcher, the cost of the data center is itself very high, and
making it run on renewable energy makes it even higher. The study provides an estimate of data centers
which is estimated at $10 million and $12 million per megawatts. This is also one of the core reasons
why only a few companies have in-house data center facilities. Furthermore, there is a cost for
establishing a cloud computing data center as well. Here it is important to mention that the difference
between cloud computing and traditional data center is of the physical space. While data centers are
physically located and kept at a particular location, cloud computing exists virtually. The second barrier
towards Green Cloud Computing service is discussed by Agrawal et al. [10], and it is lack of management
support. IT department is usually not very cautious about the climate protocols, and there is not either
high awareness prevalent in the said department regarding environmental precautions. As a result, it is
very difficult for the IT management to convince about the benefits realized through fueling cloud
computing with green energy. This is already one of the biggest challenges towards the development of
Green Cloud Computing. It can be substantiated from the fact that many IT houses do not run on green
energy, and this is primarily because there are no specific international protocols that encourage IT
operations to go all green. Since Cloud Computing is a highly technical field, there is also a lack of
awareness among the environmental agencies about the energy utilized by data centers and the need for
cloud computing to switch to a green mode of energy.
Trends in Green Cloud Computing
Since the theme of this research is to highlight the importance and dynamics of Green Cloud
Computing, it is imperative to show the recent trends and happenings in the field. This is discussed in
length by Radu [12]. As per the researcher, the most notable trend in the industry is Community Cloud.
Community Cloud is also discussed by Pal and Singh [13], who regards community cloud as a
collaborative effort whereby organizations from different fields share a space for the storage and
processing of operations. The reason why this is included in this paper is although community cloud
may run on a non-renewable source of energy, the fact that community cloud conserves and save energy
is akin to the spirit of Green Cloud Computing. Having such a technology run on green energy should
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then be the next step which must first be implemented by large organizations such as Amazon Web
Service (AWS), which is among the largest public cloud computing service in the world.
The study of Kaushal et al. [14] has also pointed to a very important development in recent times
with respect to cloud computing that is virtualization. As per the researchers, virtualization is a theme in
cloud computing that is very consistent with the need of moving away from high-powered data centers.
In order to make the process of virtualization commonly spread, the authors have used the term
Hypervisor. It is one of the software programs that allow different types of operating software to run on
a single machine. This is essentially the logic behind cloud computing and is very compatible with Green
Cloud Computing. As per the estimates in the study, virtualization can enable the conservation of energy
up to 70%, which is truly a breakthrough in the cloud computing industry. This is also because if the
servers are shared and not used distinctively, then it can reduce the cooling energy required to lower
the temperature of the machines. Therefore, virtualization can and have the potential for ensuring the
sustainability of the IT industry. However, as with green cloud computing, this type of technology is still
in its adolescence, and there are still key areas that need to be developed for the large-scale
implementation of virtualization. These key areas of development include security and performance.
Performance is among the core issues in virtualization, and this is primarily because when systems are
shared, there is a compromise in the performance. Similarly, it can also put the security at great risk
since the storing device used for different systems is the same; the break-ins and security breaches are
more widespread.
Furthermore, another emerging trend in the Green Cloud Computing industry is eco-labeling.
This is more of a compliance method whereby companies use environmental certification to label them
as eco-friendly. It is further discussed by Di Salvo [15]. As per the researchers, green labeling is rather a
sort of evaluation criteria for the clients when assessing the selection of cloud computing companies.
This can be used as a sustainable advantage, especially in an industry where there is high-intensity
competition. However, green labeling is more of a mentality where the companies do judge one another
through the criteria of how much sustainability they provide to the environment. Green labeling should
be based on two important factors that include energy efficiency and carbon dioxide emissions. This is a
responsibility that first relies on big and large companies since it is only the large companies that have
the capacity and resources to make a switch towards green energy. Once this is adopted by the industry
leader, then it becomes a norm that can then encourage the smaller companies to pursue the same
Another very important aspect of Green Cloud Computing is awareness. Although this has been
touched on in the earlier discussion, it is one of the noticeable trends in recent times. As discussed by
Abugabah and Abubaker [16], the major driver of awareness regarding the benefit of Green Cloud
Computing is a discourse that should flow from top to bottom. This should not only be practiced within
the industry but also within a company. This is to say that the major responsibility of making aware the
members of the IT community must flow from the executives that should work for invoking the
consciousness among the people regarding the benefits and dynamics of Green IT. There must be
regular conferences at the workplace regarding the efforts put in by the company to switch towards a
green source of energy. The industry should make use of articles and journals that stresses the need for
clean energy for fueling the operations of a company. Until and unless there is a consensual agreement
regarding the need to adopt a more sustainable form of energy and a sense of awareness among the
members of the fraternity, the possibility of switching the entire IT industry towards clean and green
energy would remain a distant dream.
V. Conclusion
The point of departure of this study was to highlight the need for Green Cloud Computing as a
way forward for sustainable development. This is quite a novice theme in the IT industry, and it must be
admitted that the modern discourse in the sector does not highlight the need to make the transition
from non-renewable sources of energy towards more sustainable forms. This is quite alarming because
data centers use a tremendous amount of energy which puts the lives of millions at risk. There is a clear
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need for Green Cloud Computing, a terminology that emphasizes the processes and practices to make
computing and other IT resources in accordance with climate safety. The study then dwells on
important jargon prevalent in the Green Cloud Computing sector, such as PUE or GCA. Most often than
not, these criteria do not serve as the basis of evaluation, and this is one of the problems that the
industry is facing. The clientele of cloud computing is in ignorance when it comes to energy efficiency or
carbon dioxide emissions which serve as an incentive for the producers to continue with the practices
that promise to bring large-scale destruction to the planet. Therefore, the study then proceeds to
highlight the core characteristic of Green Cloud Computing which include energy usage metrics,
virtualization, multi-tenancy, and consolidation. These are also among the prevalent trends in the
industry. Lastly, barriers towards large-scale adoption of Green Cloud Computing such as cost and
resources are highlighted. It is clear that the entire responsibility of adoption of Green Cloud Computing
rests on the industry, and it is indeed the big and small companies that should make a swift transition
towards sustainable development.
VI. Future Studies
This study takes a holistic approach and outlines the current state of Green Cloud Computing. In
doing so, it leaves out the specific details that can and should be researched further. For instance,
Electronic Recycling Programs, Edge Computing, or Mobile Clouds are specific areas that call for a
greater investigation. Hence, future studies on the topic can take a narrower approach and highlight the
specific actions the industry needs to embark on in making the IT industry more sustainable. Future
studies can also be based on producing criteria such as Eco-labeling or Green labeling to invoke a
discourse on how the companies should select the cloud computing services. In this sense, the present
study is a drop in the ocean, which is targeted to bring the entire discussion about Green IT into the
helm of the world and the need for IT companies and professionals to ensure that the sector remains
compliant with the protocols of climate change.
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... With the deterioration of Internet security, spatial awareness has become a top issue in the area. e breadth and depth of data, business logic with which it is processed, and the clarity and intuitive with which the information is analyzed all influence the effect of situational awareness decision-making processes [24,25]. Historically, research on network security incidents has made achievements in different fields, but from a macro perspective, they are all scattered. ...
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Network security situation awareness is a critical basis for security solutions because it displays the target system’s security state by assessing actual or possible cyber-attacks in the target system. Aiming at the security and stability of global information flow, this paper studies the perception and measurement of the overall situation of network security. Through the Scrappy web crawler framework, data were collected from several Zhiming network security event websites, and based on the vulnerability database of China Computer Network Intrusion Prevention Center, the network security event database was designed and established, which enriched the data of situational awareness research. This study investigates the analysis and processing of network security events, a crucial parameter in the stage of security insight and perception, and builds and implements a text-based network security event analysis tool. By designing a network security event analysis tool based on text processing, the data cleaning of network security time text information is completed, and a set of network security event processing solutions with high applicability and comprehensiveness are formed. Statistical experimental results show that the network security event database built based on the crawler algorithm contains 43,848 pieces of data, which increases the capacity by 12.79% and 29.33% compared with the traditional algorithm, and reduces the reading time by 63.5% and 87.2%.
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Innovative technologies enable businesses to stay competitive in the marketplace while also increasing profits in the manufacturing of nanocomposites for water treatment. The aforementioned driving factors resulted in the adoption of a number of innovative technologies, and no other trend has had a greater impact in recent years than Industry 4.0. Industry 4.0 is a comprehensive term that encompasses data management, manufacturing competitiveness, manufacturing processes, and efficiency. The term "Industry 4.0" refers to a group of key enabler technologies, such as cyber-physical models, Internet of Things (IoT), artificial intelligence (AI), and big data analytics, including embedded devices which are all significant components to the mechanized and digitized industrial environments. AI approaches have been used for water treatment processes as well as desalination in recent years for optimizing the process along with providing realistic answers to water scarcity and water pollution-related issues. AI applications have been used to predict and minimize water treatment process operational costs by lowering costs and optimizing chemical utilization. Several AI models are successful and accurate in predicting effectiveness of various adsorbents used in the removal process of a variety of contaminants from water. To identify the current level of research and future development prospects of smart manufacturing, this study uses a comprehensive literature review technique for manufacturing sustainability of nanocomposite fabrication for water treatment applications. The model provided will help to create a baseline for AI and hybrid models in the water treatment and wastewater management sectors, allowing for the increased performance and innovative growth. It will serve to provide the framework and give guidance for researchers interested in creating superior nanocomposites for waste and fresh water treatment and management using Industry 4.0. This study looks at a variety of AI approaches as well as how they may be used in water treatment, with an emphasis on pollutant adsorption. This assessment also identified certain obstacles and research gaps in the field of AI applications in water treatment processes.
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Vibration compensation in track displacement monitoring is explored by using rail image feature points. The key point is to compare the image of the rail to be tested with the image of the standard rail. A downstream section of Metro Line A is selected for real time analysis of image. The sampling frequency of the detection system is 0.5m/point, and the driving speed of the detection vehicle is about 40km/h, take the distance of 100m between K23+000‐K22+900 of kilometer mark, total 200 points, and analyze the image data by grey scale conversion concept. In order to verify the accuracy of the vibration compensation data, one point is taken at an interval of 5m, and a total of 20 points are measured, and compare and analyze with dynamic real‐time detection data. After vibration compensation, the geometric parameters of the contact rail are closer to the expected value, and the maximum error can be controlled within …
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