Annotated Bibliography on Energy Efficiency in Cloud Computing

ANNOTATED BIBLIOGRAPHY 1
Annotated Bibliography
Name
Date

ANNOTATED BIBLIOGRAPHY 2
Introduction
Agrawal, K., Chowdhury, A., & Tripathi, P. (2015). Scrutiny of Energy Efficiency for Green
Cloud Computing. International Journal of Computer Applications, 121(3), 25-28.
doi:10.5120/21521-4499
Research Significance
The author makes critical observations on energy efficiency issues in cloud computing and
discusses some of the research done s far to tackle the issue. The author does a comprehensive
analysis that provides a better understanding of green cloud computing energy efficiency
Literature Review
Discusses ways green clouding computing can be achieved, including data center design,
virtualization, use of algorithms for optimization, and power management. The authors also look at
research on energy efficiency for green cloud computing and put forth mechanisms ad approaches
for achieving green cloud computing
Research Gap
The research is too general and has a wide scope; research aimed at solving problems ought
to be specific and to the point (Spradlin, 2012)
Aim of Research
This research is focused on practices starting from design: specifically data center design, e-
waste recycling, telecommunications, and best practices in energy management
Dabbagh, M., Hamdaoui, B., Guizani, M., & Rayes, A. (2015). Toward energy-efficient cloud
computing: Prediction, consolidation, and overcommitment. IEEE Network, 29(2), 56-
61. http://dx.doi.org/10.1109/mnet.2015.7064904
Research Significance
The research recognizes the challenges faced by cloud service providers in the context of
energy efficiency and goes further to highlight some of the problems and propose novel solutions
Originality of Approach
The research proposes two unique methods for ensuring energy efficiency that would not
require significant capital investments: it proposes two novel approaches of workload prediction,
Workload consolidation and VM Placement, and resource overcommitment. The researchers
demonstrate their effectiveness using data and graphs
Literature Review

ANNOTATED BIBLIOGRAPHY 3
The researchers sought to evaluate the energy challenges faced by cloud service providers
and also looked at the available opportunities, before proposing solutions based on evidence. The
researchers propose solutions to solve the problem of limited growth in the performance of cloud
data centers due to the ever increasing consumption of energy of the computing systems
(Beloglazov, Buyya, Lee & Zomaya, 2011). The approach is original in that it proposes practices
that will not add significant costs to energy saving. The authors show how great energy savings can
be achieved in data centers through practices that include turning more servers to a low power state
and increasing utilization of existing servers. These are made possible by workload prediction,
resource overcommitment, and VM consolidation and placement with graphical evidence based on
experimental data showing reduced energy use.
Research Gap
The researchers present a model but this may not be applicable to small data centers; further,
their approaches have limitations when used on their own, such as resource over-utilization. What is
needed is a comprehensive approach rather than basic suggestions, for instance, a new algorithm in
data processing.
Aim of Research
This research aims at proposing a model that achieves continuous energy savings with a
comprehensive approach that is sustainable even as workloads increase. The proposed strategies
include e-waste recycling (can the wasted data center energy be recycled?), follow basic ethics in
computing, and energy efficient design for data centers, as well as telecommunication
Shu, W., Wang, W., & Wang, Y. (2014). A novel energy-efficient resource allocation algorithm
based on immune clonal optimization for green cloud computing. EURASIP Journal
On Wireless Communications And Networking, 2014(1).
http://dx.doi.org/10.1186/1687-1499- 2014-64
Research Significance
It proposes a clonal algorithm as a way of that is based on energy consumption and time cost
models to ensure dynamic energy savings and efficient utilization.
Literature Review
The proposed solution is interesting because it is an improved algorithm that goes beyond
traditional approaches to data center energy efficiency and they use a simulated experimental
research approach that shows immense potential. The model can also meet SLA agreements in data
center agreements, given that SLA agreements are very important in cloud computing

ANNOTATED BIBLIOGRAPHY 4
(Marudhadevi, Dhatchayani & Sriram, 2014). The research proposes DVFS (dynamic voltage and
frequency scaling) as a model for energy efficiency optimization. Further, the authors propose a
make-span optimization model as well as a multi-objective optimization model and use these to
generate an improved clonal selection algorithm, a very popular, nature inspired artificial immune
system model (Sharma & Sharma, 2011).
Research Gap
The proposed solutions are based on simulations and not real tests; simulations has its limits
and may not give similar outcomes when applied in real life (Coale, 2012)
Aim of Research
This research aims at proposing a mixed solution system that can be practically applied and
not just based on simulations. This paper proposes e-waste recycling, telecommunication, follow
basic ethics in computing, and energy efficient design for data centers
Gai, K., Qiu, M., Zhao, H., Tao, L., & Zong, Z. (2016). Dynamic energy-aware cloud let-based
mobile cloud computing model for green computing. Journal Of Network And
Computer Applications, 59, 46-54. http://dx.doi.org/10.1016/j.jnca.2015.05.016
Research Significance
The research seeks to address the important and emerging issue of energy waste and latency
delays in mobile cloud computing and solves one of the myriad challenges in the increasing use of
mobile cloud computing (Shahzad & Hussain, 2013)
Literature Review
The researchers propose a novel approach that leverages dynamic cloud-lets using a
dynamic energy aware cloud-let based model for cloud computing DECM. The solution is unique,
given the increased use of mobile devices (Arun & Jaiganesh, 2016)
Research Gap
The proposed solution, while novel and unique, also uses simulation of a real life situation
which has limitations I the context of scalability and credibility (Rampfl, 2013)
Aim of Research
My research aims at using telecommunication, ethical computer practices, energy efficient
design for data centers, and e-waste recycling as practical solutions for data center energy efficiency
for all forms pf cloud computing, not just mobile cloud computing