|
Addis Ababa University Libraries Electronic Thesis and Dissertations: AAU-ETD! >
Faculty of Technology >
Thesis - Electrical Engineering >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/2227
|
| Title: | Optimality Analysis and Middleware Design for Heterogeneous Cloud HPC in Mobile Devices |
| Authors: | Naod, Duga |
| Advisors: | Prof. Dr. Heiko Schr ̈der |
| Keywords: | service-oriented architecture
Android
GPGPU
parallel algorithms and programming
middleware
commodity supercomputing
energy-response time optimality
mobile cloud computing
hetero- geneous HPC |
| Copyright: | Jul-2011 |
| Date Added: | 3-May-2012 |
| Publisher: | AAU |
| Abstract: | Mobile and embedded devices such as smartphones, wireless sensor nodes, and
other ubiquitous consumer and industrial electronic systems play increasingly sig-
nificant roles in our lives. Those devices provision a range of functionalities despite
their limitations in terms of size, processing capacity and power constraints. The
advent of ubiquitous systems like those finds itself in par with another emerging
trend – cloud computing, wherein computational resources like storage, processing
hardware and software systems are provisioned to clients as services via the Inter-
net. Mobile cloud computing and the cloud in general could allow for yet more
use cases while saving the otherwise limited battery power and augmenting the
comparatively small computational workhorse available in mobile devices.
Such a scenario of cloud HPC in mobile devices needs supporting middleware for
transparent end-to-end (i.e. mobile-to/from-cloud) service oriented communica-
tion. In so doing the middleware abstracts and exposes heterogeneous cloud re-
sources like general-purpose CPUs; GPU and FPGA clusters; raw and relational
datastores; et cetera. In addition, such middleware should be able to provide run-
time support and brokerage mechanism for the mobile devices in order to consume
an abstract cloud HPC service.
In this thesis, a number of novel and existing techniques are explored towards
lightweight middleware architecture and an end-to-end mobile-cloud infrastruc-
ture is introduced. A case study is done with Android powered mobile devices, a
GPU-accelerated algorithm, a Wi-Fi network and said infrastructure towards an
experimental evaluation and model driven optimality analysis of the envisioned
system. Results showed that middleware-supported cloud HPC in mobile devices
is indeed promising and results in significant energy savings, faster response times
and paves way for more mobile computing use cases. |
| URI: | http://hdl.handle.net/123456789/2227 |
| Appears in: | Thesis - Electrical Engineering
|
Items in the AAUL Digital Library are protected by copyright, with all rights reserved, unless otherwise indicated.
|
