a review on mobile cloud computing -...

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.



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



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



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]



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].



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.



[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

Kim. (2012). Mobile Cloud Computing Security

Considerations. Journal of Security Engineering. 9 (2), p1-8.

[12] Deepti Sahu, Shipra Sharma, Vandana Dubey, Alpika

Tripathi. (2012). Cloud Computing in Mobile

Applications. International Journal of Scientific and Research

Publications. 2 (8), p1-9.

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.

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