Gearing up of resource poor mobile devices using cloud
Gearing resource poor
mobile devices with
PROJECT GUIDE :
DATA FLOW DIAGRAM
Cloud computing is a paradigm in which computing resources
such as processing, memory, and storage are not physically
present at the user’s location.
Mobile cloud computing is a paradigm for mobile applications
whereby the data processing and storage are moved from the
mobile device to clouds.
We introduce three common mobile cloud
architectures, computation offloading and capability extending
and real-world application.
Many applications are too computation intensive to perform on
a mobile systems.
Offloading such applications to the cloud can save energy and
extend battery lifetimes for mobile users.
The resource-constrained nature of mobile devices, like the
limited battery life on mobile devices has been a block to
improvements of mobile application.
Mobile cloud computing (MCC) is introduced to resolve these
conflicts, the cloud serves as a powerful complement to
resource-constrained mobile devices.
For example, Apple’s iCloud enables users to store and
synchronize their data (photos, videos, contacts, etc.) in the
The architectures define the way mobile devices are connected to
and interact with the cloud
The three architectures are Centralized cloud , Cloudlet and Ad
Hoc mobile cloud.
Centralized Cloud :The cloud resource is placed in a remote
centralized cloud infrastructure.
Cloudlet :It is a resource-rich server that has Internet access and
is connected to mobile devices via LAN. Reduces delay.
Ad Hoc Mobile Cloud :This architecture regards a crowd of
mobile devices as an “ad hoc mobile cloud,” where the
neighboring mobile devices are pooled together for resource
Computation Offloading :Offload parts of resource-intensive
tasks to the cloud.
Capability Extending: Cloud computing helps to extend the
capabilities of mobile devices in three aspects: computation,
storage, and networking.
Challenges and opportunities in MCC , with respect to the
stochastic characteristics of wireless networks are EnergyEfficient Interactions, Virtual machine migration overhead,
Privacy and Security.
Some of the real-world applications enabled by MCC are
Augmented reality, Remote healthcare and Web applications.
The modules are:
This module utilize the ability of the android application and
cloud to run the Content Based Image Retrieval(CBIR) for
the image taken.
CBIR algorithm takes so much CPU resource if it is executed
in smart- phone ,which in turn effects battery life.
Offloading CBIR operations to cloud infrastructure proves
efficiency of application and power consumption of android
system.This can be analyzed using a graph
which produce the power consumption of
Computation Offloading is used in android applications
where low data transfer rate and huge computation is
Open source IaaS cloud technology(back-end) called “Open
Stack” provides different virtualized instances for hosting the
and Reliability Module
Cloud level security layer is implemented using user-level
enceyption for virtual machines network traffic and storage
offered by Openstack IaaS cloud technology.
The web service level data security is implemented using
Two users in the system -Admin & User
Admin maintains a web based image repository.
User takes a snap and loads the image.
Match found comparing RGB cross product
Performance evaluation of both obtained.
We described the state of the art of mobile cloud
computing ,from the brewing offloading technology.
We unveil the major challenges in mobile cloud
computing and potential solutions.
Mobile devices geared toward cloud computing will
undoubtedly change technology trends as well as our
Many practical problems remain to be resolved to
structure a full fledged mobile cloud system.
IEEE 2013 paper “Gearing resource-poor mobile
devices with powerful clouds:architectures,challenges
and applications” by Fangming liu and Hai jin.
IEEE 2009 Reference paper “Energy Efficient
Content-Based Image Retrieval For Mobile Systems” by
Yu-Ju Hong and Karthik Kumar
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