ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- Creators: Huang, Dijiang
By taking into consideration of the WebRTC solution for data transferring, we propose a new Cloud based interactive multimedia which enables virtual lab learning environment. Three modules were proposed along with an efficient solution for achieving optimized network bandwidth. The One-to-Many communication was introduced in the video conferencing and scalability was tested for the application. The key technical contribution is to establish a sufficient system that designed to utilize the WebRTC in its best way in educational world in the Vlab platform and reduces the tool cost and improves online learning experience.
provisioning computing, storage and communication resources. A distributed mobile
cloud service system called "POEM" is presented to manage the mobile cloud resource
and compose mobile cloud applications. POEM considers resource management not
only between mobile devices and clouds, but also among mobile devices. It implements
both computation offloading and service composition features. The proposed POEM
solution is demonstrated by using OSGi and XMPP techniques.
Offloading is one major type of collaborations between mobile device and cloud
to achieve less execution time and less energy consumption. Offloading decisions for
mobile cloud collaboration involve many decision factors. One of important decision
factors is the network unavailability. This report presents an offloading decision model
that takes network unavailability into consideration. The application execution time
and energy consumption in both ideal network and network with some unavailability
are analyzed. Based on the presented theoretical model, an application partition
algorithm and a decision module are presented to produce an offloading decision that
is resistant to network unavailability.
Existing offloading models mainly focus on the one-to-one offloading relation. To
address the multi-factor and multi-site offloading mobile cloud application scenarios,
a multi-factor multi-site risk-based offloading model is presented, which abstracts the
offloading impact factors as for offloading benefit and offloading risk. The offloading
decision is made based on a comprehensive offloading risk evaluation. This presented
model is generic and expendable. Four offloading impact factors are presented to show
the construction and operation of the presented offloading model, which can be easily
extended to incorporate more factors to make offloading decision more comprehensive.
The overall offloading benefits and risks are aggregated based on the mobile cloud
users' preference.
The offloading topology may change during the whole application life. A set of
algorithms are presented to address the service topology reconfiguration problem in
several mobile cloud representative application scenarios, i.e., they are modeled as
finite horizon scenarios, infinite horizon scenarios, and large state space scenarios to
represent ad hoc, long-term, and large-scale mobile cloud service composition scenarios,
respectively.