Dynamic Carpooling Application Development

Dynamic Carpooling Application Development on Android Platform

C0458022313

Abstract — In today’s world, there are lots of people
commuting from place to place. Example: employees going back
home. Students going home from university etc. And lot of times,
people will be commuting via car or bike and there is place to
take a fellow employee along with him to give a ride. But the
problem is there is no easy way to know how many people a
person can take and co-ordination is a huge issue that there is no
effort by people to help each other by giving a lift and more over
this saves the environment in reducing fuel usage, reduces traffic
with fewer vehicles etc. The Carpool is an android application
which will provide the advanced searching techniques and
provide most relevant results for the carpooling in the city. This
will be help full in easy way Carpooling reduces the costs
involved in repetitive or long distance driving by sharing cars,
sharing rental charges, or paying the main car owner. Some
countries have introduced high-occupancy vehicle (HOV) lanes
to encourage carpooling and use of public transport, to combat
rising traffic congestion [1].
Index Terms— Car Owner, Ride Seeker, Pickup and Drop-Off
points, HOV [high-occupancy vehicle], OV [Origin &
Destination]

INTRODUCTION
In recent years, the problems of global warming and the
energy crisis have aroused widespread public concern. One
recommended solution for reducing the harmful factors
leading to such problems is carpooling. This type of
transportation service could make a big difference if
organized on a large scale by government or big companies,
particularly large corporations with many branches or subcompanies.
Carpooling schemes are designed to encourage
commuters to share travel expenses and resources with
colleagues. Carpooling (also known as car-sharing, ridesharing,
lift-sharing), is the shared use of a car by the driver
and one or more passengers, usually for commuting.
Carpooling arrangements and schemes involve varying
degrees of formality and regularity.

Formal carpool projects have been around in a structured
form since the mid-1970s [1]. Long-term carpooling is
defined as the sharing of a private vehicle by several
individuals who follow a semi-common route between
different points of origin and destination (OD) during a
specific period. In practice, a participant can request to share
the same trip with his/her friends, in which case they are
treated as a participant group with the same OD and travel
route/schedule. The results of such an action are the
following:
1) Reduction in the number of vehicles on the route;
2) Reduction in expenses for gas;
3) Reduction in energy consumption (CO2 emissions)
and Pollution;
4) Provision of social connections in an increasingly
Disconnected society [2].

The Dynamic Carpooling is more complicated than longterm/
daily many-to-one or one-to-many car pooling
problems. An efficient plan for the Dynamic Carpooling
may require matching participant groups to a car on a semi
common route or assigning a participant group to different
cars on different days. It is very difficult to simultaneously
and optimally determine every participant group’s role
(driver group or passenger group), driver group schedules,
and passenger group deliveries, as well as to suitably match
several participant groups in a car while still keeping in
mind fairness considerations. This process involves
complicated movements of driver groups (or vehicles) and
passenger groups in both time and space,

An Innovative Tour Recommendation System

An Innovative Tour Recommendation System for Tourists in Japan

An Innovative Tour Recommendation System

Abstract1— The paper demonstrates prototype of system that
is capable of suggesting optimal touring plans which are
composed of various points of interest (POI) and take travelers’
preferences and context into account. It systematically collects
and analyzes information on thousands of tourists attraction
areas and geographical nodes of Japan Railway (JR) train
stations together with concurrent weather information,
estimated travel time, associated expenses, and lists of multiple
cultural events in order to demonstrate practicality as well as
reliability of the system. A programmatic approach based on the
heuristic greedy search is employed for transforming the
obtained data into informative routes. It demonstrates the
feasibility of the approach through its mobile prototype on web
platform and tests it under various scenarios in eight different
places in Japan which includes Tokyo, Osaka, Kyoto, Kobe,
Yokohama, Nagoya, Fukuoka and Sapporo. Its result and the
performance can be considered as a stepping stone towards a
more localized and practical recommendation system in the field
of tourism in the near future.
Keywords— e-tourism, travel planning system, web scraping,
modeling, and data mining.

Addressing Mobile Cloud Computing Security Issues

Addressing Mobile Cloud Computing Security Issues: A Survey

Addressing Mobile Cloud Computing Security

Ahstract-The cloud heralds a new era of computing where
application services are provided through the Internet. Cloud
Computing is a flexible, cost-effective, and proven delivery
platform for providing business or consumer IT services over the
Internet. The computing capability of mobile systems is
enhanced by Cloud computing. Mobile devices can rely on cloud
computing and information storage resource, to perform
computationally intensive operations such as searching, data
mining, and multimedia processing. Along with traditional
computation services it provides, mobile cloud also enhances the
operation of traditional ad hoc network by treating mobile
devices as service nodes, e.g., sensing services. The sensed
information, such as location coordinates, health related
information, should be processed and stored in a secure fashion
to protect user’s privacy in the cloud.
While the economic ease for cloud computing is compelling,
the security challenges it poses are equally striking. The security
threats have become obstacles in the rapid adaptability of the
mobile cloud computing paradigm. Significant efforts have been
devoted in research organizations and academia to build secure
mobile cloud computing environments and infrastructures. In
spite of the efforts, there are a number of loopholes and
challenges that still exist in the security policies of mobile cloud
computing. We discuss these issues here, identifying the main
vulnerabilities in this kind of systems and the most important
threats found in the literature related to Cloud Computing and
its environment as well as to identify and relate vulnerabilities
and threats with possible solutions.
Index Terms – Mobile Computing (MC), Mobile Cloud
Computing (MCC), Mobile Cloud Security.

INTRODUCTION
Mobile devices are increasingly becoming an essential part
of human life as the most effective and convenient
communication tools not bounded by time and place [1] – [2].
The rapid progress of mobile computing (MC) becomes a
powerful trend in the development of IT technology as well as
commerce and industry fields. However, the mobile devices
are facing many challenges in their resources (e.g., battery life,
storage, and bandwidth) and communications (e.g., mobility and security). The limited resources significantly impede the
improvement of service qualities [3] – [4].
Furthermore, consider applications that require extensive
processing – image processing for video games, speech
synthesis, natural language processing, augmented reality,
wearable computing-all these demand high computational
capacities thus restricting the developers in implementing
applications for mobile phones. Considering the trends in
mobile phone architecture and battery, it is unlikely that these
problems will be solved in the future. This is, in fact, not
merely a temporary technological deficiency but intrinsic to
mobility [5] and a barrier that needs to be overcome in order
to realize the full potential of mobile computing.
In recent years, researchers addressed this problem through
cloud computing. Cloud computing can be defined as the
aggregation of computing as a utility and software as a service
[6]where the applications are delivered as services over the
Internet and the hardware and systems software in data centers
provide those services [7]. Also called ‘on demand
computing’, ‘utility computing’ or ‘pay as you go computing’,
the concept behind cloud computing is to offload computation
to remote resource providers.
The concept of offloading data and computation in cloud
computing is used to address the inherent problems in mobile
computing by using resource providers other than the mobile
device itself to host the execution of mobile applications. Such
an infrastructure where data storage and processing could
happen outside the mobile device could be termed a ‘mobile
cloud’. By exploiting the computing and storage capabilities
of the mobile cloud, computer intensive applications can be
executed on low resource mobile devices [8] – [10].
It is important to ensure secure and reliable datal
multimedia data transmissions between mobile users and the
media cloud. Since the data can be transferred and stored in a
cloud system through wireless, it becomes vulnerable to
unauthorized disclosures, modifications, and replay attacks. A
critical question must be answered when the mobile clients
upload their data or multimedia to the cloud: Can users trust
the cloud?
The remainder of this paper is organized as follows: Section
II describes the mobile cloud computing architecture. Section
III explains the technical challenges posed by MCC. Section
IV briefs about the approaches used. Section V provides
survey of existing security frameworks for MCC. Finally
future work and conclusion are identified in section VI and
VII.

Collaborative Filtering Based Recommender

A Survey of Collaborative Filtering Based Recommender Systems for Mobile Internet Applications

A Survey of Collaborative Filtering Based

Abstract—With the rapid development and application of the
mobile Internet, huge amounts of user data are generated and collected
every day. How to take full advantages of these ubiquitous
data is becoming the essential aspect of a recommender system.
Collaborative filtering (CF) has been widely studied and utilized
to predict the interests of mobile users and to make proper
recommendations. In this paper, we first propose a framework of
CF recommender system based on various user data including
user ratings and user behaviors. Key features of these two kinds
of data are discussed. Moreover, several typical CF algorithms
are classified as memory-based approaches and model-based
approaches and compared. Two case studies are presented in
an effort to validate the proposed framework.
Index Terms—Mobile Internet, Recommender System, Collaborative
Filtering.

INTRODUCTION
Along with the rapid development of mobile Internet and
cloud computing, massive amounts of data are produced every
day by both people and machines. Our society has already
entered the era of Big Data [1]. Thanks to the various smart
devices and mobile applications, Internet users can acquire
all sorts of information about education, shopping, social
activity, etc. [2] [3] [4] [5]. However, as the volume of data
increases, individuals have to face the problem of excessive
information, which makes it more difficult to make the right
decisions. This phenomenon is known as information overload
[6]. Moreover, limited by the input ability of mobile devices,
users are usually unwilling to type in lots of words to describe
what they want. Recommender system can alleviate these
problems by effectively finding users’ potential requirements
and selecting desirable items from a huge amount of candidate
information. Recommender systems are usually classified into
two categories, i.e., content-based and collaborative filtering
(CF) [7].
Content-based recommender system utilizes the contents of
items and finds the similarities among them. After analyzing
sufficient numbers of items that one user has already shown favor to, the user interests profile is established. Then the
recommender system could search the database and choose
proper items according to this profile. The difficulty of these
algorithms lies in how to find user preferences based on the
contents of items. Many approaches have been developed to
solve this problem in the areas of data mining or machine
learning. For example, in order to recommend some articles
to a specific reader, a recommender system firstly obtains all
the books this reader has already read and then analyzes their
contents. Key words can be extracted from the text with the
help of text mining methods, such as the well-known TF-IDF
[8]. After integrating all the key words with their respective
weights, a book can be represented by a multi-dimensional
vector. Specific clustering algorithms can be implemented to
find the centers of these vectors which represent the interests
of this reader.
On the other hand, collaborative filtering (CF) has become
one of the most influential recommendation algorithms [9].
Unlike the content-based approaches, CF only relies on the
item ratings from each user. It is based on the assumption that
users who have rated the same items with similar ratings are
likely to have similar preferences. CF is specifically designed
to provide recommendations when detailed information about
the users and items is inaccessible. Furthermore, it successfully
mitigates the problem of over-specialization [10], which is
quite common in content-based systems. Over-specialization
is the phenomenon that recommended items are always much
the same and the diversity of recommendations is neglected.
As CF makes recommendations according to the neighborhood
(people with similar preferences), the item one user has
consumed may be something new to his neighbors. The above
features are particularly attractive which make CF algorithms
extensively employed in recommender systems.
However, to the best of our knowledge, very few studies
have revealed the common features of the various CF algorithms
for mobile Internet applications. In addition, most of
the existing surveys merely introduce the principles of CF
algorithms, ignoring the importance of case study, which can
demonstrate the performances of typical algorithms visually
and specifically. Therefore, this paper focuses on collaborative
filtering based recommender systems for mobile Internet
applications. In particular, main contributions of this paper are
highlighted as follows:
 We introduce a general framework of CF recommender
system. This framework assists recommender developers to utilize the gathered data and to generate proper recommendations.
The features of data collected from both
user behaviors and user ratings are also discussed and
compared.
 CF algorithms are classified. Main procedures of CF are
briefly summarized and introduced.
 Two case studies are presented to validate the proposed
framework. Evaluations on representative CF algorithms
are conducted based on real-world datasets with detailed
analysis and comparison.
The rest of this paper is organized as follows. Section II
presents the framework of CF. Both classification and main
procedures of typical CF algorithms are introduced in Section
III. In Section IV, we conduct two case studies based on realworld
datasets in order to analyze the performances to utilize the gathered data and to generate proper recommendations.
The features of data collected from both
user behaviors and user ratings are also discussed and
compared.
 CF algorithms are classified. Main procedures of CF are
briefly summarized and introduced.
 Two case studies are presented to validate the proposed
framework. Evaluations on representative CF algorithms
are conducted based on real-world datasets with detailed
analysis and comparison.
The rest of this paper is organized as follows. Section II
presents the framework of CF. Both classification and main
procedures of typical CF algorithms are introduced in Section
III. In Section IV, we conduct two case studies based on realworld
datasets in order to analyze the performances of CF
algorithms. Finally, Section V concludes this paper.

Blood Bank Management System

A Standard Compliant Blood Bank Management System with Enforcing Mechanism

A Standard Compliant Blood Bank Management

Abstract—Blood is a non-replenishable entity, the only source of which are humans. Timely availability of quality blood is a crucial requirement for sustaining the healthcare services.
Therefore, maintaining quality of blood and identification of Professional Donors is a major responsibility of blood banks.
NACO (National AIDS Control Organization) and NABH (National Accreditation Board for hospitals and Healthcare Providers) have provided guidelines for ensuring the quality of blood and identifying Professional Donors. Moreover, manually monitoring standards and identifying professional donors is a challenging job. In this work, we develop a standard compliant Blood Bank Management System with a novel rule based enforcing mechanism. The developed system is an end-to-end solution for not only managing but implementing enforcing strategies and providing decision support to the users. The proposed Blood Bank Management System has been implemented across 28 blood banks and a major hospital. It has been found extremely effective in streamlining the workflow of blood banks.
Keywords—Blood Bank Management System; Blood Stock; NACO; NABH; Professional Donor; Donor Repository

The major concern of blood banks is to ensure efficient and effective collection and maintenance of quality blood stock as well as identification of Professional Donors (Section II-E).
This becomes crucial since the span of time, especially in emergency situations, between requirement, arrangement and delivery of blood is very narrow. Moreover, blood banks across the state, districts are not able to utilize the available blood stock appropriately due to lack of connectivity and time taken to propagate information via conventional channels.
National AIDS Control Organization (NACO) and National Accreditation Board for hospitals and Healthcare Providers (NABH) have provided guidelines to ensure the quality of blood. But there is absence of effective enforcement strategy to ensure the adherence to these guidelines. In view of this, we propose a comprehensive IT solution i.e. a Blood Bank Management System (BBMS) attempting to address this problem by providing means to connect, digitize and streamline the workflow of blood banks.
The need for automating blood banks have been there for a long time. In early days of digitization, the primary purpose of an IT solution for blood banks was inventory management [6][13]. With time, the processes involved in management of services of blood bank as well as Blood Transfusion System [5][4] have become more complex. The main issue, which plagues BBMS in the country is enforcing the standards and identification of the Professional Donors. Therefore, in the modern world the purpose of BBMS is not only to passively act as inventory management system but to actively enforce standard operating procedures along with providing decision support. Recent Blood Bank Management Systems tend to focus on adapting the system to local practices instead of enforcing standard practices. The developed solution augments the functionality of the contemporary systems.
Authors in [15] developed a blood bank management system which adhered to the requirements of a single hospital. The system developed in [3] caters to a National level transfusion service, but limits the scope to providing citizen centric services and inventory management. Authors in [8], attempt to address the issue of safe transfusion by developing an end to end solution. A real time system for blood bank has been proposed in [1].
A recent study [12] has observed that the existing workflow of blood banks needs to be strengthened, both in terms of planning and monitoring. Also, there are many gaps in the management of blood supply [16] [9]. Our work
addresses the following gaps as compared to similar systems.
Firstly, the existing systems have been designed to take care of routine functioning of blood bank and care not able to enforce the guidelines and standards based on rules. Secondly, identification of professional donors, if available, is usually based on bio-metric devices only. Such identification mechanisms mostly require an additional level of integration effort and scrutiny by the blood bank staff. Thirdly, quality checks are based on manual entry processes. In addition to these fundamental issues, there are many challenges that are encountered when such a system is implemented across a large number of locations. These challenges are discussed in Section II-A. In view of the above, the contributions of this paper are:
• Development of a standard compliant Blood Bank Management System including a stringent rule based enforcing mechanism.
• Architecture for a fault-tolerant deployment especially for rural and areas with sparse connectivity.
• Identifying key requirements and learnings from implementation of a Blood Bank Management System for large scale deployments

The rest of the paper is organized as follows. The next section describes the proposed system. Section III presents the details of implementation. The impact of the system as compared to pre-deployment scenario is discussed in Section IV. Finally, Section V concludes this paper.

Realizing Near-Field Communication Mobile Payments

A Review of Technical Approaches to Realizing Near-Field Communication Mobile Payments

A Review of Technical Approaches to

Mobile phones that support near- eld communication
(NFC)a contactless, low-power
technology that lets devices communicate over distances
on the order of a few centimeterscan act like
a smart card when presented to a contactless terminal
in so-called card emulation mode. One of this mode’s
main use cases is payments at the point of sale (POS),
an increasingly important ability in light of mobile
phones’ central role, ubiquity, and connectivity capabilities.
Yet, despite these advantages and the fact that
the core NFC technology has been available for several
years, there’s still no global established pay-with-yourphone
mechanism. In part, this is due to the complexity
of the NFC ecosystem, which includes a wide
variety of banks, mobile network operators (MNOs),
phone manufacturers, and other stakeholders who
o en have competing interests in the recurring revenue
generated from payment transactions. Traditionally,
 nancial institutions and payment networks shared
the per-transaction commission, but with phone payments
becoming increasingly popular, commissions
must be shared among more entities, which is clearly
unappealing to established stakeholders.
So far, no single POS mobile payment scheme has
risen to dominance, in spite of multiple a empts backed
by powerful players. Some have disappeared without
ever gaining a foothold, while others have evolved by
dropping, adapting, and mixing speci c technologies.
So cardinitially known as Isis Mobile Walletwas
one such scheme backed in the US by AT&T, T-Mobile,
and Verizon; it eventually shut down in March 2015
without much fanfare. Google Wallet (www.google
.com/wallet) launched several years ago for in-store use
but nowadays seems to be limited to sending money
within the US. Presently, Apple Pay (www.apple.com
/apple-pay), Android Pay (www.android.com/pay),
and Samsung Pay (www.samsung.com/us/samsung
-pay) are the most prevalent schemes. LG Pay was discretely
announced a few months ago but remains to
be launched. At present, all these schemes have limitations
in terms of supported countries, merchants, and
cards.  is situation is expected to improve with time; however, given this dynamic and fragmented landscape,
instead of focusing on a particular payment scheme, I
aim to address the fundamentals of how they work from
a technical standpoint.

Cross Domain Handshake Scheme

A Provably-Secure Cross-Domain Handshake Scheme with Symptoms-Matching for Mobile Healthcare Social Network

A Provably-Secure Cross-Domain Handshake

Abstract—With rapid developments of sensor, wireless and mobile communication technologies, Mobile Healthcare Social Networks
(MHSNs) have emerged as a popular means of communication in healthcare services. Within MHSNs, patients can use their mobile
devices to securely share their experiences, broaden their understanding of the illness or symptoms, form a supportive network, and
transmit information (e.g. state of health and new symptoms) between users and other stake holders (e.g. medical center). Despite the
benefits afforded by MHSNs, there are underlying security and privacy issues (e.g. due to the transmission of messages via a wireless
channel). The handshake scheme is an important cryptographic mechanism, which can provide secure communication in MHSNs (e.g.
anonymity and mutual authentication between users, such as patients). In this paper, we present a new framework for the handshake
scheme in MHSNs, which is based on hierarchical identity-based cryptography. We then construct an efficient Cross-Domain
HandShake (CDHS) scheme that allows symptoms-matching within MHSNs. For example, using the proposed CDHS scheme, two
patients registered with different healthcare centers can achieve mutual authentication and generate a session key for future secure
communications. We then prove the security of the scheme, and a comparative summary demonstrates that the proposed CDHS
scheme requires fewer computation and lower communication costs. We also implement the proposed CDHS scheme and three
related schemes in a proof of concept Android app to demonstrate utility of the scheme. Findings from the evaluations demonstrate
that the proposed CDHS scheme achieves a reduction of 18.14% and 5.41% in computation cost and communication cost, in
comparison to three other related handshake schemes.
Index Terms—Mobile healthcare social networks, cross-domain handshake, secure handshake, authentication, elliptic curve, security.

INTRODUCTION
ACcording to Moody’s Investor Service, the world is
facing a ageing challenge where more than 20% of the
world’s population are over 65, partly due to a longer life
span but declining birth rate. For example, it is predicted
that 13 countries will be ”super-aged” by 2020 and 34
countries by 2034 [1]. An aging demographic will be a test
for existing healthcare systems and may place a strain on the
healthcare industry, if technologies do not keep pace with
the changing requirements. Wireless Body Area Networks
(WBANs), for example, can play an active role in supporting
and complementing existing healthcare system.

WBAN is a relatively new network paradigm designed
to provide users with a remote and periodical healthcare
monitor in healthcare system. In WBANs, each patient in
the system wears one or more wireless body sensor nodes
(BSNs). These sensor nodes monitor and collect personal
information (PHI) such as blood pressure, heartbeat, and
temperature, regardless of the patient’s location and condition
(e.g. lying in bed or taking a stroll). Collected PHI will
be sent to a smart mobile device, such as a smart phone, via
bluetooth, cognitive radio or other communication channel
(e.g. WiFi). The mobile smart device will then transmit
the PHI to a remote healthcare center via a 3G/4G or
WiFi network. This allows the medical practitioner (e.g.
medical doctor and specialist) to monitor and understand
the patient’s health condition, and respond to any lifethreatening
situation in real-time (e.g dispatching medical
workers to the patient in the event of a potential heart attack
or a stroke); thus, providing better quality healthcare for
patients. A typical healthcare-monitoring scenario is shown
in Fig.1.

Cloudlet Scheme for Bigdata

A Mobile Cloud Computing Model Using the Cloudlet Scheme for Big Data Applications

A Mobile Cloud Computing Model Using the Cloudlet Scheme for Big Data

Abstract- The wide spread of smart phones and their capabilities
made them an important part of many people’s life over the
world. However, there are many challenges facing these devices
such as: low computing power and fast energy drain from their
batteries. One solution is to use mobile cloud computing services
to run certain tasks at the cloud and returning back the results to
the mobile device saving space and processing power. In this
research, we introduce efficient Mobile Cloud Computing model
based on the Cloudlet sheme. In our model, the mobile device
don’t need to communicate with the enterprise cloud server and
instead contact the Cloudlet directly using cheaper technologies
such as Wi-Fi, and no need for 3G/4G. Also, we propose a
master-cloudlet management scheme to organize the
communication between the cloudlets themselves. Our efficient
mobile cloud computing model can be applied in many
environments including universities and hospitals were big
amounts of data is collected, stored and processed. The real
implementation results show that our model out performs
classical non-cloudlet mobile cloud computing models.
Keywords— Mobile Cloud Computing, CloudLet Scheme, Big Data
Applications.

INTRODUCTION
Nowadays, technology has rapidly risen from sticking to a
single working area to variable locations depending on many
factors including comfort and high speed stable internet
connection. Those factors emerge the use of mobile computing
for an easier life. Therefore, mobile computing continues to be
a main service in data communication and networking
technologies [1].
Mobile Computing is a technology which allows sending
and receiving data to any other wireless enabled device without
having to be connected to a fixed physical link. As shown in
Figure (1), mobile computing include using small size portable
computer to run standalone applications through wireless
networks or 3G, 4G technology [2].

Another recent raising technology trend is the cloud
computing that integrates different technologies to build a new
type of the organizations IT infrastructure. In cloud the
technology is used when you need it and for as long as you
need it without installing it on your machine. All resources you
need (hardware and software) are provided for you as a service
by another vendor and accessed over the Internet in an efficient
and easy way [3] as can be seen from Figure 2.

The cloud computing environment contains set of scalable
resources that include hardware infrastructure, storage,
computation platforms, software and applications, which can
be provisioned as a service to the user reducing the cost and
application hosting and storage [4]. Examples of cloud
computing infrastructures and platforms are Microsoft Azure,
Amazon EC2, and Aneka [5]. Also, the cloud services might be
deployed as public, private, hybrid or community cloud [6],
allowing access to the stored information from anywhere at any
time. So, in conclusion, cloud computing can be used in
environments that require cost and time efficiency, backup and
recovery, and enhancing productivity [7].

In addition to cloud computing, Mobile Cloud Computing
(MCC) is a recent technology that is growing rapidly. But in
reality there are many challenges facing the real
implementation of MCC environment including the short life
of the battery in mobile devices. Also, those devices don’t have
enough memory and processing capability to perform
applications with intensive calculations such as image
processing and social networking [8]. This drives the need to
provide an integrated framework for enabling energy-efficient
reliable mobile cloud services. The MCC model allows data
storage and processing to be offloaded to the cloud platform
resulting in better reliability and availability and optimized
energy [9].
In this paper, we introduce efficient and secure Mobile
Cloud Computing (MCC) model that is based on the Cloudlet
scheme. In the new model, the mobile devices don’t need to
contact the cloud server and instead contact the Cloudlet. This
will allow users to connect directly to cloud resources using
cheaper technologies such as Wi-Fi.
The rest of this paper is organized as follows: related work
is presented in the next section. Section III presents the
proposed mobile cloud computing model based on the cloudlet
scheme. The experimental implementation results are shown in
Section IV, and Section V concludes this work.

Mobile Cloud Computing

A Distributed Mobile Cloud Computing Model for Secure Big Data

A Distributed Mobile Cloud Computing Model for

Abstract—Mobile cloud computing provides a novel ecommerce
mode for organizations without any upfront investment.
Since cloud computing uses distributed resources in open
environment, it is important to provide secure keys to share the
data for developing cloud computing applications. To ensure a
correctness of users’ data in the cloud, we propose an effective
and secure distributed model including a Self-Proxy Server (SPS)
with self-created algorithm. The model resolves a communication
bottleneck due to re-encryption of a shared data in the cloud
whenever users are revoked. It offers to reduce security risks and
protect their resources because a distributed SPS dynamically
interacts with Key Manager (KM) when the mobile users take on
cloud services. This paper presents a comprehensive mobile cloud
design which provides an effective and secure cloud computing
services on mobile devices.
Index Terms—mobile cloud computing, self-proxy server, key
manager, distributed cloud computing, mobile cloud provider.

INTRODUCTION
Acloud system is difficult to synchronize login and
authentication data between external clouds and internal
systems without exposing internal security data. The cloud
technologies are rapidly being adopted throughout the
Information Technology (IT) due to their various attractive
properties. In spite of their spread, they has raised a range
of significant security and privacy concerns which interrupt
their adoption in sensitive environments.
The cloud computing technology provides IT services and
resources to the customers through public network such as
internet. The cloud computing services and infrastructure
are mostly owned by a third party called cloud service
providers. Cloud computing provides an innovative model
for the organizations to use software applications, storage
and processing capabilities of cloud without investing on
the infrastructure. As compared to existing IT models, the
cloud computing provides many advantages like scalability,
flexibility, efficiency and non-core activities [1]. Despite these
extraordinary benefits of cloud computing, it is important to
consider the security risks present in a cloud environment in
order to find enough security solutions[ 2, 3].
From mobile user prospective, mobile cloud computing is
a marvelous improvement because it diminishes the mobile
resources issues like limited battery power, slow processing
power, low internet bandwidth, small storage space and less
energy consumption [4].
Mobile cloud computing offers data processing and storage
capabilities in the cloud which the mobile user can access
using mobile device’s web browser. The mobile users do not
need high data processing and storage capabilities services
on their mobile devices because cloud resources are used for
all the data processing and storage. The number of cloud
users are low despite of the advantages which mobile cloud
computing has brought into mobile computing world. The
major reason is the risks in terms of security and privacy of
the data and services [5]. Companies are still concerned about
security when using cloud computing. Users are worried
about the vulnerability to attacks, when information and
critical IT resources are outside the firewall.
The scheme of [6] has provided comprehensive information
regarding the cloud security problems. It has been estimated
the security problem from cloud architecture point of
view, the cloud stakeholders’ point of view and at the end
from cloud services delivery models point of view. From
stakeholder prospective, the security configurations needs to
be organized and each service should be maintained a level at
runtime. From service delivery model prospective, the cloud
management security issues and cloud access method security
issues are also highlighted.
The scheme of [2] has presented details about the security
issues which cloud service providers are facing when they
dig deep for cloud engineering. There are some serious
issues and challenges which cloud computing is facing in
the domain of cyber security. The paper also covers security
management models for the cloud service providers in order
to meet security compliance.
The scheme of [5] has identified the serious threats and risks
related to privacy and security for the mass and corporate
users when they will integrate their mobile hand held devices
with the cloud infrastructure. The paper point out towards
the different motivational factors which are forcing mobile
cloud operators to move their services and operations to
cloud. It conducted a survey that how wireless mobile devices
integrates with the cloud.
The scheme of [7] has explained the security issues related to
private data and mobile cloud applications in detail. Keeping
the security issues and the existing solution limitations in
mind, it proposed a mobile computing applications security
framework to make sure that the security of the data is achieved when it is transmitted between the components of
the same mobile application.
The scheme of [8] has proposed a mechanism for improving
the security application of cloud computing. The mechanism
is based on dynamic intrusion detection system which
dispatches its detectors on the networking system domain
through multi layers and multi stages deployment. It provides
wide range of security protection like protection of web sites
and pages threats, detection of any intrusion, verification of
the database access and security in cloud side, the detection
of system side data leakage and some other issues related
processes. However, in spite of these schemes, there are
still a number of challenges, which are currently addressed
by researchers, academicians and practitioners in the field.
Mobile cloud computing currently faces some serious security
issues and challenges which limits its adoption among the
mobile users.
The remaining sections are as follows: section 2 discusses
cloud computing architecture, section 3 proposes a secure
mobile cloud computing design with Self-Proxy Server,
section 4 presents the conclusion.