Full metadata
Title
Mobile cloud application framework and offloading strategies
Description
Mobile Cloud computing has shown its capability to support mobile devices for
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.
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.
Date Created
2016
Contributors
- Wu, Huijun (Author)
- Huang, Dijiang (Thesis advisor)
- Xue, Guoliang (Committee member)
- Dasgupta, Partha (Committee member)
- Mirchandani, Pitu (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
x, 136 pages : illustrations (some color), color map
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.40256
Statement of Responsibility
by Huijun Wu
Description Source
Viewed onNovember 15, 2016
Level of coding
full
Note
thesis
Partial requirement for: Ph.D., Arizona State University, 2016
bibliography
Includes bibliographical references (pages 131-136)
Field of study: Computer science
System Created
- 2016-10-12 02:18:00
System Modified
- 2021-08-30 01:21:33
- 3 years 3 months ago
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