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International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 10, October 2014
ISSN: 2278 – 7798 All Rights Reserved © 2014 IJSETR 2600
A Review on Mobile Cloud Computing
D.Priyanka, Rajasekhar Boddu, B.Sunil Kumar, C.Srinivasulu
Abstract--Cloud computing is an emerging technology
that paved way for potential commoditization of
computing resources. This technology is on top of
virtualization that makes the cloud offerings affordable.
With the advent of mobile and hand held devices and
innovations with underlying mobile technologies and
the ubiquitous nature of mobiles, cloud computing
expands to mobile devices as well. This led to mobile
cloud computing where mobile devices are associated
with cloud computing and leverage benefits of cloud. As
people of all walks of life are using mobile devices, the
mobility feature of the devices can have tremendous
impact on usage of cloud computing. There is steady
growth rate projected with respect to mobile cloud
computing in future. As mobile devices are energy and
resource constrained, they are vulnerable to various
security threats. Unless these threats are addressed,
mobile cloud computing cannot be adapted easily. This
paper throws light into the mobile cloud computing, its
architecture, issues involved and solutions. The insights
obtained through review of important papers can help
in making well informed decisions with respect to
mobile cloud computing and its applications in the real
world.
I. INTRODUCTION
Cloud computing is the technology that realizes the
dream of commoditizing computing resources in
similar fashion to electricity and water. In fact cloud
computing enables users to access huge computing
resources. This new model of computing helps
people and organizations to access computing
resources in pay as you use fashion. Thus the model
avoids the need for capital investment. It has got
service models like Software as a Service (SaaS),
Platform as a Service (PaaS) and Infrastructure as a
Service (IaaS). Its deployment models include private
cloud, public cloud, community cloud and hybrid
cloud. Mobile Cloud Computing (MCC) is the cloud
computing where mobile devices are involved. In fact
MCC is nothing but the cloud computing that
involves mobility. It involves mobile users whose
storage and processing is done in cloud i.e. outside
the mobile devices [1]. The architecture of MCC is as
shown in Figure 1.
Figure 1 – Architecture of MCC [1]
As can be seen in Figure 1, it is evident that the cloud
computing facilities are being utilized by mobile
devices. Mobile users get services from network
operators. In turn the network operators are able to
gain access to cloud services through Internet. There
are many technologies that enable MCC. They are
Web4.0, Cloudlets, Hypervisor, HTML5, 4G and
CSS3. Mobile computing has plethora of advantages
that include offloading of computations, executing
applications remotely, remote processing, task
migration, improved storage capacity and processing,
improved availability and reliability, scalability,
dynamic programming, ease of integration, multi-
tenancy, mobile commerce, mobile learning, mobile
healthcare, health cloud, telemedicine, mobile
gaming and so on [1]. Businesses across the world
grow faster with mobile computing. There are future
projections that speak about the possible usage of
MCC in future. Figure 2 presents the forecast
pertaining to revenues on MCC in the period 2009
and 2015.
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International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 10, October 2014
ISSN: 2278 – 7798 All Rights Reserved © 2014 IJSETR 2601
Figure 2 – Forecast on revenues on MCC [1]
As can be seen in Figure 2, it is well known that the
overall revenues on MCC across the globe are
increasing year by year in rapid pace. This is the
indication that the mobile computing plays an
important role to make mobile cloud computing a
successful paradigm in future.
According to Pragya and Sudha (2012), MCC has
revolutionized the experience of mobile users as they
can obtain plethora of cloud services on the go. In
addition to this mobile computing technologies are
growing rapidly making the cloud usage feasible and
affordable. As many things are done outside mobile,
the MCC causes increased bandwidth, storage and
energy. Kovachev et al. (n.d) [3] provides
comparison of MCC application models. The models
help in understanding the true dynamics of MCC to
bring effectiveness in cloud computing. There are
certain challenges faced by MCC. They include
limitations of mobile devices, communication
quality, and the division of labor of application
services. These limitations can be overcome by using
technologies or methods like virtualization, task
migration, upgrading bandwidth, and elastic
application division [4]. Huang et al. [5] proposed a
framework for MCC known as MobiCloud for
enhancing communication quality in the MCC
operations. Frenando et al. (2013) [6] provides a
good survey of MCC and its related researches that
have been carried out besides contrasting cloud
computing and MCC. Dinh et al. [7] provides good
architecture of MCC and its applications and
approaches. They also provide insights into the issues
in MCC and its solutions that are possible.
Asrani [8] explored MCC platform for important
applications like M-Commerce, M-Healthcare, and
M-Gaming. It also throws light into the possible
challenges of MCC and underlying solutions that can
overcome the problems involved I MCC. Kumar and
Lu [9] completely focused on energy efficiency of
MCC as the mobile nodes outsource computing and
storage. How mobile devices can save energy by
offloading work was the main focus of their research.
Miettinen and Nurminen [10] also did research on
similar lines. They focused much on energy
efficiency possibilities of MCC. This research is
important as it finds the reasons why MCC is useful
for mobile devices. As mobile devices are energy
constrained and their network lifetime is affected by
the storage and processing, offloading these activities
certainly reduce the power consumption. Thus MCC
is able to achieve energy efficiency.
Mobile devices are vulnerable to various attacks.
This might have its impact on MCC. Ko et al. [11]
focused on security issues pertaining to MCC. This
has very important aspect as the security issues cause
problems in MCC. Security considerations need to be
a continuous process as the overcoming of the issues
can impact on the growth rate of MCC in the real
world. Sahu et al. [12] also focused on issues with
MCC and possible solutions that can be used to
overcome problems and leverage the power of cloud
and the ubiquitous nature of mobiles. The rest of this
paper reviews important papers on mobile cloud
computing that provide insights into the research area
pertaining to the present state of the art besides
knowing its implications on the real world.
II. RELATED WORKS
This section reviews some of the important papers
which provide insights into the mobile cloud
computing, its issues and solutions. The review also
bestows various models in the mobile cloud
computing besides other useful information.
Energy efficiency of mobile clients in cloud
computing
Miettinen and Nurminen [10] focused on the mobile
cloud computing research. Especially they considered
energy efficiency problem. The reason behind this is
that mobile devices are energy constrained and they
lack sufficient resources. Optimum utilization of the
resources is the fundamental aspect with respect to
mobile cloud computing. Mobile devices consume
less energy when they can offload storage and
processing operations to cloud. However, the energy
savings thus made should be more than the additional
communication cost incurred for associating with a
cloud. In [10] detailed analysis is made with respect
to critical factors that affect the energy efficiency of
the mobiles connected to a network. They also
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International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 10, October 2014
ISSN: 2278 – 7798 All Rights Reserved © 2014 IJSETR 2602
presented some sort of measurements to measure the
characteristics of mobile or hand held devices. The
measures are with respect to the balance between the
remote and local computing that can affect nodes
consuming energy. Their paper also demonstrates a
concrete example to describe the process of saving
energy in mobile cloud computing.
Miettinen and Nurminen made an energy trade-off
analysis to find whether mobiles involving in mobile
cloud computing can save energy. The energy
required for local computations is represented as Elocal
while the energy required to outsource storage and
processing operations to cloud is represented as
Ecloud. Ideally the beneficial situation is achieved with
the equation presented below [10].
Ecloud < Elocal
It does mean that the energy consumed when the
storage and processing operations in the local device
should be less that of the cloud. When this ideal
situation is met, energy saving is possible.
Considering D is the amount of data to be transferred
and C is the computational power required in order to
transfer the data. Provides these details the following
equation is used to compute Ecloud and Elocal.
Ecloud = D/Deff
Elocal = C/Ceff
The computational characteristics for two kinds of
mobile devices are presented in Table 1. The devices
used for experiments are Nokia N810 and Nokia
N900.
Table 1 – Energy characteristics of local computing [10]
As can be seen in Table 1, energy consumption
details of two devices are presented with respect to
local computing while the wireless computing results
for the same is presented in Table 2.
Nokia profiler is used to measure energy
consumption. As per the energy efficiency formulae,
the local performance of the devices is measured and
recorded. Afterwards, the cloud performance of the
devices will be recorded and compared.
Experiments and Future Work
When data is transferred, the energy consumption is
depending on the bit rate. The more bit rate is the less
energy consumption is. It does mean that energy
efficiency is achieved by using high bit rate channels.
Energy efficiency in case of cellular network actually
depends on the data to be transferred and bit rate.
Figure 3 illustrates the bit rate and energy efficiency
dynamics.
Figure 3 – Energy per bit for N95 WLAN and 3G
As can be seen in Figure 3 it is evident that there is
relation between bit rate, data transfer and energy
efficiency. Energy efficiency is sensitive to bit rate in
case of cellular networks when compared to WLAN.
Figure 4 – Illustrate traffic pattern effect for N95 WLAN
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International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 10, October 2014
ISSN: 2278 – 7798 All Rights Reserved © 2014 IJSETR 2603
As can be seen in Figure 4, it is evident that
dynamics are presented for bursty traffic sources and
smooth traffic sources with respect to Nokia N95
device in WLAN. When bit rate is 1W it causes
smooth communication while the bit rate 0.6W it
causes bursty communication.
Figure 5 – Illustrates power consumption for viewing PDF
As can be seen in Figure 5, example measured curves
are presented that reflect the power required by the
local viewer with respect to the device N900 WLAN.
The remote cases needed higher average power.
Interestingly the remote case causes less power
consumption as the execution time is shorter. When
compared with WLAN, 3G network causes more
energy consumption. Future work includes studying
end to end chain for mobile energy consumption with
respect to mobile cloud computing.
Securing Mobile Cloud Computing
Communications
Huang et al. [5] proposed an architecture for mobile
cloud computing. Their proposed architectural
framework is named “MobiCloud”. The MobiCloud
is the combination of traditional services and modern
services. The framework makes use of trust
management, risk management and secure routing
concepts to overcome corresponding issues. With this
framework in place, it is possible to deploy and use a
new class of applications to leverage the power of
cloud computing through small hand held devices
[5]. Figure 6 presents the architectural overview of
MobiCloud.
Figure 6 – Architectural overview of MobiCloud [5]
As can be seen in Figure 6, it is seen that cloud and
mobile networks are integrated. MobiCloud service
provisioning, MobiCloud trust management server,
MobiCloud Resource Manager, and MobiCloud
service or application store are the important
components involved. The solid lines in the
architecture include direct links while the dotted lines
include indirect links. The secure communication is
made possible with SSL connections. Secure Sockets
Layer is the protocol that makes the communications
in mobile cloud computing secure. The MobiCloud is
using SSL connections to ensure that the
communications are encrypted while sending and
receiving. Mobile Ad Hoc Network is also involved
as part of architecture [5].
Attribute Based Encryption
The security to communication is made using a
special encryption scheme known as attribute based
encryption. The scheme has various things such as
attributes from A1 to An and private key components,
and secret sharing threshold gates besides a key for
data encryption [5]. The encryption scheme is
visualized as shown in Figure 7.
Figure 7 – Illustrates attribute based encryption [5]
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International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 10, October 2014
ISSN: 2278 – 7798 All Rights Reserved © 2014 IJSETR 2604
As can be seen in Figure 7, the attribute based
encryption scheme has encryption mechanism that
makes use of attributes. The attribute based
encryption is used for efficient key management
scheme for access control. With this scheme and the
MobiCloud framework it is possible to conceive
many application scenarios. The scenarios include
inter-operable communications, efficient
communications, security scenarios, isolation
scenarios, and delay tolerance communication
scenarios. The MobiCloud can also be improved in
future to support damage recovery, secure isolation
of fine-grained resource isolation. Operation delay is
the real time issue with respect to performance of
MobiCloud. The applications that run in this cloud
are to be designed carefully keeping the framework
in mind and thus they can have the desired features.
The main services of MobiCloud includes monitoring
services that observe node status information while
the on-demand services take care of many services
that arise on the fly. Other important service is
known as advising service which emulates MANET
activities for analyzing post events [5].
Experiments and Future Work
Experiments are made with MobiCloud with
MANET involved in mobile cloud computing. The
data transmission interval and routing overhead ratio
are observed in MANET. The protocols used for
experiments include DSR and AODV [5]. The data
transmission intervals include 10, 100 and 1000. The
experimental results are presented in Figure 8.
Figure 8 – Routing overhead ratios vs. data transmission interval
for DSR and AODV [5]
As can be seen in Figure 8 it is evident that the
routing overhead ratio is more with AODV protocol
when compared with DSR protocol. The future work
include damage recovery which does mean the loss
of mobile devices, and fine grained resource and
security isolation which brings about control and
efficiency in mobile cloud computing [5].
III. APPLICATION MODELS FOR
MOBILE CLOUD COMPUTING
Dejan et al. [3] provide a collection of application
models that can leverage the concept of mobile cloud
computing. The models are designed systematically.
They observed that decoupling of service delivery
from the methods or techniques, reducing cost,
processing cost, software cost over Internet, and
delivery of services are the foundation of the cloud
computing. However, it is challenging task to achieve
all these benefits in case of mobile cloud computing.
With respect to current status in mobile applications,
there are two kinds such as Online and offline
applications. The mobile experiences and
environments are changing rapidly. Based on this the
online and offline applications should get updated to
resolve issues [3].
Novel Application Models for Mobile Cloud
Computing
Various models are described in [3] of applications
models for mobile cloud computing. They include
augmented execution model, elastic partitioned
model, application mobility and ad-hoc mobile
clouds.
Figure 9 – Models for augmented execution [3]
As can be seen in Figure 9, it is evident that there are
many models for augmented execution with respect
to mobile cloud computing. The models include
outsourcing primary functionality, background
augmentation, mainline which is in between primary
and background, hardware which makes use of
virtual machines, and multiplicity model is used for
parallel execution of tasks [3].
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International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 10, October 2014
ISSN: 2278 – 7798 All Rights Reserved © 2014 IJSETR 2605
Figure 10 – Reference architecture for elastic applications [3]
As can be seen in Figure 10, it is evident that the
application in this architecture is split into three
components. They are UI component, weblet
component and manifest component. The UI
component is related to user interface. The functional
software entities that are invoked from UI are known
as weblets. The cloud elasticity service has
application manager, cloud sensing, cloud manager,
and cloud fabric interface. The manifest component
contains the details of the UI and the weblets
available for the application. In [3], many existing
and proposed application models with respect to
mobile cloud applications. The summary of the
findings is presented in Table 3.
Table 3 – Summary of comparison of existing and proposed
mobile cloud models [3]
As can be seen in Table 3, it is evident that there are
architectures for mobile computing that have been
proposed and some of them already implemented.
The technologies used for the mobile cloud
computing include Hadoop, web services, distributed
file system, restful web services, C#, OSGi, Java and
HTML 5 [3].
Future Work
An important direction for future work is to continue
with interdisciplinary research pertaining to Human
Computer Interaction (HCI), networks and systems.
This will help in enhancing the utility of mobile
cloud computing in future.
IV. CONCLUSION
This paper provides insights pertaining to mobile
cloud computing. It covers issues pertaining to
mobile clients in cloud computing and possible
techniques to resolve issues. One such issue is energy
efficiency. Since the mobile devices are energy
constrained, they need to be utilized properly. It does
mean that the integration with cloud should bring
about energy efficiency as the work of the mobiles is
offloaded to cloud. The operations such as storage
and processing are outsourced to cloud. The energy
saving due to cloud computing should be greater than
the communication overhead. Towards this end many
models came into existence. This paper focuses more
on energy efficiency in mobile cloud computing,
securing mobile cloud computing applications and
various application models that are best used with
mobile cloud computing. The paper also presents
results of the work of those papers and provides
possible future directions in the area of mobile cloud
computing.
REFERENCES [1] Anonymous. (n.d), Mobile Cloud Computing, p1-47.
[2] Pragya Gupta and Sudha Gupta. (2012). Mobile Cloud
Computing: The Future of Cloud. International Journal of
Advanced Research in Electrical, Electronics and Instrumentation
Engineering. 1 (3), p1-12.
[3] Dejan Kovachev, Yiwei Cao and Ralf Klamma. (n.d). Mobile
Cloud Computing: A Comparison of Application Models., p1-8.
[4] Han Qi and Abdullah Gani. (n.d). Research on Mobile Cloud
Computing: Review, Trend and Perspectives., p1-8.
[5] Dijiang Huang, Xinwen Zhang, Myong Kang and Jim Luo.
(2010). MobiCloud: Building Secure Cloud Framework for Mobile
Computing And Communication. IEEE, P1-8
[6] Niroshinie Fernando, Seng W. Loke and Wenny Rahayu.
(2013). Mobile cloud computing: A survey. Future Generation
Computer Systems, Elsevier. 29 (.), p84-106.
[7] Hoang T. Dinh, Chonho Lee, Dusit Niyato, and Ping Wang.
(n.d). A Survey of Mobile Cloud Computing: Architecture,
Applications, and Approaches. Wireless Communications and
Mobile Computing - Wiley, p1-38.
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International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 10, October 2014
ISSN: 2278 – 7798 All Rights Reserved © 2014 IJSETR 2606
[8] Priyanka Asrani. (2013). Mobile Cloud
Computing. International Journal of Engineering and Advanced
Technology (IJEAT). 2 (4), p1-4.
[9] Karthik Kumar and Yung-Hsiang Lu,. (2010). CLOUD
COMPUTING FOR MOBILE USERS: CAN OFFLOADING
COMPUTATION SAVE ENERGY?. IEEE, P51-57.
[10] Antti P. Miettinen and Jukka K. Nurminen. (n.d). Energy
efficiency of mobile clients in cloud computing, p1-7.
[11] Soeung-Kon(Victor) Ko1, Jung-Hoon Lee and Sung Woo
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[12] Deepti Sahu, Shipra Sharma, Vandana Dubey, Alpika
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AUTHORS
Mrs. D. Priyanka completed M.Tech from Vignana Bharathi Institute of
Technology Affiliated to JNTUH. I am Presently
working as Assistant Professor in Department of
Computer Science & Engineering in Vignana
Bharathi Institute of Technology, I am having 6+
years of Teaching Experience. My interested subjects
are Formal Languages and Automata Theory, Data
Base Management Systems, Computer Networks,
Mobile computing, Digital Logic Design and Computer Organization,
Mr.Rajasekhar Boddu completed M.Tech and B.Tech from JNTU
Hyderabad, India. Presently working as Lecturer in
Department of Software Engineering, College of
Computing and Informatics(CCI), Haramaya
University, Ethiopia. He is having 5 years of teaching
experience. He is a member in UACEE, IACSIT,
CSTA, IAENG, ACM. His research interests are Security, Data Mining and Cloud Computing.
Mr. B. Sunil Kumar working as
Assistant Professor in Department of Computer
Science & Engineering in Jawaharlal Nehru Institute
of Technology, Hyderabad, India. I am having 5
years of Teaching Experience. My interested subjects are Web Technologies, Linux Programming, Mobile
computing, cloud computing, Computer Networks,
Operating System, Computer Organisation, Java, C,
and C++.
Mr. C. Srinivasulu pursing
M.Tech(cse) from VignanaBharathi Institute of Technology affiliated to JNTU-H. Completed
B.Tech(cse) from Visvodaya Institute of Technology
& Science, Kavali (formerly affiliated to JNTU-H). I
am currently working as a Team Lead with NTT
DATA. I am having 1.7 years of experience in
Teaching and 8+ years of experience as a Java
Developer. My interested subjects are Cloud
computing, Java, C++, Web Technologies, Web
Services, Computer Networks.