Title page for ETD etd-04122004-170045


Type of Document Dissertation
Author Kuacharoen, Pramote
Author's Email Address pramote@ece.gatech.edu
URN etd-04122004-170045
Title Embedded Software Streaming via Block Streaming
Degree Doctor of Philosophy
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
mooney, Vincent Committee Chair
Ammar, Mostafa Committee Member
Juang, Biing-Hwang Committee Member
Madisetti, Vijay Committee Member
Schwan, Karsten Committee Member
Keywords
  • software streaming
  • block streaming
Date of Defense 2004-04-07
Availability unrestricted
Abstract
Downloading software from a server usually takes a noticeable amount of time, that is, noticeable to the user who wants to run the program. However, this issue can be mitigated by the use of streaming software. Software steaming is a means by which software can begin execution even while transmission of the full software program may still be in progress. Therefore, the application load time (i.e., the amount of time from when an application is selected for download to when the application can be executed) observed by the user can be significantly reduced. Moreover, unneeded software components might not be downloaded to the device, lowering memory and bandwidth usages. As a result, resource utilization such as memory and bandwidth usage may also be more efficient. Using our streaming method, an embedded device can support a wide range of applications which can be run on demand. Software streaming also enables small memory footprint devices to run applications larger than the physical memory by using our memory management technique.

In this dissertation, we present a streaming method we call block streaming to transmit stream-enabled applications, including stream-enabled file I/O. We implemented a tool to partition software into blocks which can be transmitted (streamed) to the embedded device. Our streaming method was implemented and simulated on an MBX860 board and on a hardware/software co-simulation platform in which we used the PowerPC architecture. We show a robotics application that, with our software streaming method, is able to meet its deadline. The application load time for this application also improves by a factor of more than 10X when compared to downloading the entire application before running it. The experimental results also show that our implementation improves file I/O operation latency; in our examples, the performance improves up to 55.83X when compared with direct download. Finally, we show a stream-enabled game application combined with stream-enabled file I/O for which the user can start playing the game 3.18X more quickly than using only the stream-enabled game program file alone.

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