A Survey of Mobile Cloud Computing Applications: Perspectives and

A Survey of Mobile Cloud Computing Applications: Perspectives and Challenges

Awodele Oludele

Babcock University, Ilishan Remo, Ogun State.

Otusile Oluwabukola

Babcock University, Ilishan Remo, Ogun State.

ABSTRACT

As mobile computing has been developed for decades, a

new model for mobile computing, namely, mobile cloud

computing, emerges resulting from the marriage of

powerful yet affordable mobile devices and cloud

computing. MCC integrates the cloud computing into the

mobile environment and overcomes obstacles related to

the performance.

This paper gives a survey of MCC application including

the definition, architecture, as well as speculate future

generation mobile cloud computing applications. The

challenges and existing solutions and approaches are

presented

KeyWords: Mobile computing, cloud computing, mobile

cloud computing, mobile cloud applications.

1.0 Introduction

The NIST defines cloud computing as a model for

enabling ubiquitous, convenient, on-demand network

access to a shared pool of configurable computing

resources that can be rapidly provisioned and released

with minimal management effort or service provider

interaction [14]. It has three layers of services, namely,

Software as a Service (SaaS), Platform as a Service

(PaaS), and Infrastructure as a Service (IaaS). The cloud

provides a powerful processing core and a massive

storage space with configurable computing resources for

users to do computation on it. Cloud service is

characterized as on-demand, elastic, quality of service

guaranteed, and pay-per-use. Cloud computing propels a

new class of applications which called MCC

applications.

7KHWHUP³PRELOHFORXGFRPSXWLQJ´ZDVintroduced not

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mid-2007. It has been attracting the attentions of

entrepreneurs as a profitable business option that reduces

the development and running cost of mobile applications,

of mobile users as a new technology to achieve rich

experience of a variety of mobile services at low cost,

and of researchers as a promising solution for green IT

[14].

Mobile cloud computing (MCC) at its simplest, refers to

an infrastructure where both the data storage and data

processing happen outside of the mobile device.

Alternatively, MCC can be defined as a combination of

mobile web and cloud computing [1] which is the most

popular tool for mobile users to access applications and

services on the Internet.

Mobile cloud applications move the computing power

and data storage away from the mobile devices and into

powerful and centralized computing platforms located in

clouds, which are then accessed over the wireless

connection based on a thin native client. Mobile cloud

computing brings new types of services and facilities for

mobile users to take full advantages of cloud computing.

MCC provides mobile users with the data processing and

storage services in clouds. The mobile devices do not

need a powerful configuration (e.g., CPU speed and

memory capacity) since all the complicated computing

modules can be processed in the clouds.

1.1 Why Mobile Cloud Computing?

 Mobile devices face many resource challenges

(battery life, storage, bandwidth etc.)

 Cloud computing offers advantages to users by

allowing them to use infrastructure, platforms and

software by cloud providers at low cost and

elastically in an on-demand fashion.

 Mobile cloud computing provides mobile users

with data storage and processing services in clouds,

obviating the need to have a powerful device

configuration (e.g. CPU speed, memory capacity

etc), as all resource-intensive computing can be

performed in the cloud.

2.0 MCC Architecture

Fig. 1. Mobile Cloud Computing (MCC) architecture.

In Fig. 1, mobile devices are connected to the mobile

networks via base stations (e.g., base transceiver station

(BTS), access point, or satellite) that establish and

control the connections (air links) and functional

interfaces between the networks and mobile devices.

Mobile uVHUV¶ UHTXHVWV DQG LQIRUPDWion (e.g., ID and

location) are transmitted to the central processors that are

connected to servers providing mobile network services.

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Proceedings of IMCIC - ICSIT 2016

Here, mobile network operators can provide services to

mobile users as AAA (for authentication, authorization,

and accounting) based on the home agent (HA) and

VXEVFULEHUV¶ GDWD Vtored in databases. After that, the

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Internet. In the cloud, cloud controllers process the

requests to provide mobile users with the corresponding

cloud services. These services are developed with the

concepts of utility computing, virtualization, and service-

oriented architecture (e.g., web, application, and database

servers).

2.1 Advantages of MCC

 Extending battery lifetime: Computation offloading

migrates large computations and complex

processing from resource-limited devices (i.e.,

mobile devices) to resourceful machines (i.e.,

servers in clouds). Many mobile applications take

advantages from task migration and remote

processing, thereby allowing remote application

execution to save energy significantly.

 Improving data storage capacity and processing

power: MCC enables mobile users to store/access

large data on the cloud. It helps reduce the running

cost for computation intensive applications by not

been constrained by storage capacity on the devices

because their data now is stored on the cloud

therefore improving reliability and availability:

with data and services in the clouds, then are

always (almost) available even when the users are

moving.

 Dynamic provisioning: Dynamic on-demand

provisioning of resources on a fine-grained, self-

service basis therefore there is no need for

advanced reservation

 Scalability: Mobile applications can be performed

and scaled to meet the unpredictable user demands

and Service providers can easily add and expand a

service

 Multi-tenancy: Service providers can share the

resources and costs to support a variety of

applications and large no. of users.

 Ease of Integration: Multiple services from

different providers can be integrated easily through

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demands.

2.2 MCC Applications

Mobile applications gain increasing share in a global

mobile market. Various mobile applications have taken

the advantages of MCC. We have witnessed a number of

MCC applications in recent years, including mobile

commerce, multimedia sharing, mobile learning, mobile

sensing, mobile healthcare, mobile gaming, mobile social

networking, location-based mobile service, and

augmented reality. Mobile commerce, such as e-banking,

e-advertising and e-shopping, uses scalable processing

power and security measures to accommodate a high

volume of traffic due to simultaneous user access and

data transaction processing multimedia sharing provides

secure viewing and sharing of multimedia information

stored on smartphones while providing administrative

controls to manage user privileges and access rights

necessary to ensure security. Mobile learning allows a

thin terminal to access learning materials on the cloud

any time and any place. Mobile sensing utilizing sensor-

equipped smartphones to collect data will revolutionize

many MCC applications including healthcare, social

networking, and environment/health monitoring. Mobile

healthcare allows an enormous amount of patient data to

be stored on the cloud instantaneously. A doctor can

conveniently look at the patient records on his/her mobile

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for preventive actions. Mobile gaming achieves

scalability by leveraging scalable computation and

instantaneous data update on the cloud side and screen

refresh at the mobile device side. Mobile social

networking allows a group of mobile users to upload

audio/video/multimedia data for real-time sharing, with

cloud computing providing not only storage for data, but

also security to protect secrecy and integrity of data.

2.3 MCC Issues

 Mobile communication issues:

± Low bandwidth: One of the biggest issues,

because the radio resource for wireless networks

is much more scarce than wired networks

± Service availability: Mobile users may not be

able to connect to the cloud to obtain a service

due to traffic congestion, network failures,

mobile signal strength problems

± Heterogeneity: Handling wireless connectivity

with highly heterogeneous networks to satisfy

MCC requirements (always-on connectivity, on-

demand scalability, energy efficiency) is a

difficult problem

 Computing issues:

Computation offloading:

 One of the main features of MCC

 Offloading is not always effective in saving

energy

 It is critical to determine whether to offload and

which portions of the service codes to offload

3.0 Related Works

Weiguang Song et. al. [1] summarize the core concepts

of Mobile Cloud Computing [MCC] by developing a

basic idea model of Mobile Cloud Computing. Major

problems faced by MCC are discussed such as stability

of wireless connectivity, tackling the unnecessary battery

usage etc. Also, few possible solutions are suggested.

Qureshi et. al. [2] discusses about the mobile cloud

computing technology and proposes the implementation

methods for Mobile Cloud Computing solutions such as

General Purpose Mobile Cloud Computing (GPMCC)

and Application Specific Mobile Cloud Computing

(ASMCC). Certain barriers such as network availability

and bandwidth are focused. Two aspects of security

issues such as mobile device security and cloud security

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Proceedings of IMCIC - ICSIT 2016

are addressed. Le Guan et. al. [3] addresses the

challenges in Mobile Cloud Computing design such as

network latency, limited bandwidth and availability. In

order to analyze Mobile Cloud Computing technology, a

concept model is proposed which includes context

management, resource scheduling, client and

transmission channel. A Cloud architecture of Mobile

Cloud Computing is described for organization of Mobile

Cloud Computing systems. Application partition and

offloading and various context aware services are

explained briefly. Dejan et. al. [4] addresses several

mobile cloud approaches. An overview of various

possibilities of Mobile Cloud Computing is given. Native

and web applications are too extremes of mobile

applications. The cost model of elastic mobile cloud

applications is described.

Han Qi et. al. [10] discuss Mobile cloud computing

(MCC) as a development and extension of mobile

computing (MC) and cloud computing (CC) which has

inherited high mobility and scalability. The proposed

system in the paper explains the principle of MCC,

characteristics, recent research work, and future research

trends. Proposed system analyzes the features and

infrastructure of mobile cloud computing and also

analyzes the challenges of mobile cloud computing.

Vinod et. al. [12] discuss about the cloud computing

which enables the work anywhere anytime by allowing

application execution and data storage on remote servers.

This is useful for mobile computing and communication

devices that are constrained in terms of computation

power and storage. The goal of the paper is to

characterize under what scenarios cloud-based

applications would be relatively more energy-efficient

for users of mobile devices.

Hung et. al. [7] analyzes the performance of many

mobile applications which are weak due to lack of

computation resources, storage, and bandwidth and

battery capacity. To overcome this, application is rebuilt

using the cloud services. The proposed system explains a

framework to execute the mobile application in cloud

based virtualized environment with encryption, and

isolation to protect against unauthenticated cloud

providers. Results show the execution of mobile

application by offloading the workload with efficient

application level migration method via mobile networks.

The migration of application form one device to another

is easy and quick in the proposed system. Ricky et. al.

[13] discuss that mobile cloud computing allows mobile

applications to use the large resources in the clouds. In

order to utilize the resources, migration of the

computation among mobile nodes and cloud nodes is

necessary. Therefore, a highly portable and transparent

migration approach is needed. The paper uses a Java byte

code transformation technique for task migration without

effecting normal execution. Asynchronous migration

technique is used to allow migrations to take place

virtually anywhere in the user codes. The proposed Twin

Method Hierarchy minimizes the overhead from state-

restoration codes in normal execution. Milos et. al. [5]

discusses the Biometric applications such as fingerprint

identification, face, or iris scanning. These applications

actually work in a laboratory setting where the client

computer has unlimited access to the throughput and

computational resources of the network. The problem

focused here is on the battery power of the device and the

throughput of the communication channel of the client

node to the cloud. The paper explains the mobile cloud

computing technique for biometric applications such as

fingerprint identification, face recognition and iris

recognition. Debessay et. al. [6] analyzes and studies the

impact of cloudlets in interactive mobile cloud

applications. In order to study the impact, cloudlet

network and service architecture is proposed. This

architecture focuses on file editing, video streaming, and

collaborative chatting. The performance gains with the

usage of clouds are shown by simulation results. NKosi

et. al. [8] discusses mobile devices which are used in

Health information delivery access and communication

challenges like power, bandwidth, and security. The

proposed system explains how cloud computing can be

used in mobile devices to provide sensor signals

processing and security. The system described in the

proposed system uses an NGN/IMS system with cloud

computing to reduce the burden of organizing and also

for improving the functions of existing mobile health

monitoring systems. The interaction between health

service provider, IMS network operator and cloud

computing service providers should be regulated so that

identity management and security verification is

performed.

Yan Gu et. al. [9] focuses on the fundamental issue in the

mobile application platform which is the deployment

decision for individual tasks when the battery life of the

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experience. The proposed system explains the

deployment scheme to offload expensive computational

tasks from thin, mobile devices to powered, powerful

devices on the cloud. The proposed system is

implemented and various experiments on the Android

devices for individual components. Chun et. al. [11]

discuss about the mobile applications which are

providing functionality on mobile devices. Also, mobile

devices provide strong connectivity with more powerful

machines ranging from laptops and desktops to

commercial clouds. The proposed system in the paper

presents the design and implementation of CloneCloud.

CloneCloud is a system that automatically transforms

mobile applications to get benefit from the cloud.

CloneCloud uses a combination of static analysis and

dynamic profiling to automatically partition an

application.

4.0 Emerging and Future MCC Applications

Future MCC applications must leverage unique

characteristics of MCC. Due to limitation of power,

intensive data processing on mobile devices is always

costly. With the technology advancement, however,

mobile devices are equipped with more functional units,

such as high-resolution camera, barometer, light sensor,

etc. Emerging and Future MCC Applications includes:

 Application Category References

 Crowdsourcing (crowd computing) [15] [16]

[17]

 Collective sensing [18] [19] [20] [21]

 - Traffic/Environment monitoring [22, 23, 24]

[25]

 - Mobile cloud social networking [26] [27] [28]

 - Mobile cloud healthcare [29] [30] [31]

 Location-based mobile cloud service [32] [33]

 Augmented reality and mobile gaming [34]

[35]

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Proceedings of IMCIC - ICSIT 2016

Future MCC applications must leverage deep sensing

capability of smartphones for data collection. Data can be

uploaded to the cloud and the cloud can integrate pieces

of observations from mobile devices and utilize data

analytics techniques to mine and visualize trends or

patterns embedded in massive data collected in parallel at

runtime from millions of mobile devices. For instance,

given a severe natural disaster, people nearby can send

photos taken from the cameras in their smartphones to

the cloud, and the cloud server can process these data,

analyze possible crucial points, and plot a detailed map,

covering not only visible objects but also invisible

physical phenomena, such as the presence of poisonous

air to help facilitating the rescue mission. With

potentially unlimited storage and processing power,

MCC brings out potential killer applications.

Crowdsourcing (crowd computing) is one of the

emerging MCC applications [15]. It utilizes sensing

functions of pervasive mobile devices and high

processing capability of the cloud. Two future

crowdsourcing applications discussed in [16] can

potentially benefit from MCC. One is for finding a lost

child; one is for disaster relief. In the first application,

smartphones upload pictures taken within an hour to a

website in response to an amber alert via texting, and a

policeman searches for the lost child by doing data

analytics on thousands of photos uploaded using an

application in his smartphone.

In the second case, after a disaster the infrastructure

around the disaster site is broken and there is no way to

assess the damage using the existing infrastructure. By

using cameras on smartphones, citizens take pictures of

the disaster site and transmit them via wireless

communication, helping a detailed map of the disaster

site to be reconstructed, such that rescue work can be

effectively and efficiently performed. Defining scalable

architectures, creating efficient algorithms for

crowdsourcing, stimulating crowd participation, and

preserving user privacy are major issues. Yang et al. [17]

devised two incentive mechanisms for user-centric and

platform-centric computing.

On the user side, users contribute data through a bidding

process to maximize their profits. On the cloud side, a

game theoretical approach based on auctioning is used to

maximize the system utility.

Another emerging and future mobile cloud application is

collective sensing [18]. Cheng et al. designed

SenseOrchestra [19] for node location tracking via

collective sensing. Lu et al. [20] designed SoundSense to

run in Apple iPhones to recognize events by collectively

sound sensing. Lastly, Sensorly [21] provides a map of

free wireless coverage through collective sensing by its

mobile cloud members. Emerging collective sensing

applications include composing a realtime traffic map

from collective traffic data sensing [22, 23, 24],

monitoring environmental pollution [25], mobile cloud

social networking [26] [27] [28], and mobile cloud based

healthcare [29, 30, 31].

Location-based mobile service is also an emerging MCC

application. Tamai et al. [32] designed a platform for

location-based services leveraging scalable computation

and large storage space to answer a large number of

location-based queries efficiently. Location-based mobile

service is often context-aware. In addition to taking

account of location information, location-based mobile

services also consider the environment and application

context, such as people, other devices and time between

changes. The environment information can be feasibly

obtained. Social networking can connect several people

around sharing common interests. For example, the

application can recommend an online game to play or a

chat session connecting people with common interests.

La et al. [33] developed a framework for location-based

mobile service with user mobile devices monitoring the

context information to send to the cloud and with the

cloud analyzing and adapting the context information to

suggest location-based mobile services to users sharing

common interests.

Lastly, augmented reality and mobile gaming is emerging

as a MCC killer application. While traditionally

augmented reality is made possible only with special

equipment with huge processing power, it is now made

possible with mobile cloud computing with scalable

computation and big data storage.

Kangas et al. [34] developed mobile code to be processed

by the cloud to realize augmented reality. Luo [35]

proposed an augmented reality application to enhance

user experiences.

4.0 CONCLUSIONS

This paper surveys the challenges, scope, approaches and

solutions in the area of Mobile Cloud Computing. The

paper focusses on Energy conservation in mobile

devices, migration issues, application development

platforms and the various mobile cloud computing

applications.

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