PROBLEM OF INEFFICIENT INTERNAL HARDWARE OF
PORTABLE MOBILE DEVICES
Solving by Artifacts Prebuffering using Mobile Database Cache
Ondrej Krejcar, Dalibor Janckulik and Leona Motalova
Department of Measurement and Control, VSB Technical University of Ostrava, 17, Listopadu 15, Ostrava, Czech Republic
Keywords: Portable Mobile Device, Prebuffering, SQL Database, Web Service.
Abstract: The paper deals with a problem of inefficient internal hardware like bus, memory or CPU of wireless
connected portable mobile devices and a possibility to solve this problem by a prebuffering of selected
artifacts. The basics are in a model of data prebuffering based system enhancement for locating and tracking
users inside the buildings. The framework uses a WiFi network infrastructure to let a mobile device
determine its indoor position. User location is used for data prebuffering and pushing information from
server to user’s PDA. All server data is saved as artifacts (together) with its position information in building.
The accessing of prebuffered data on mobile device can highly improve response time needed to view large
multimedia data. I tested our solution on created facility management information system with testing
collection of about hundred large size artifacts. On mobile device the SQL Server CE database is used as a
cache. Finally the new way to manage the artifacts throw the framework is described and tested.
1 INTRODUCTION
The using of mobile wireless devices like laptops,
PDA devices or Smartphones with internet
connection is today possible everywhere anytime.
The connection speed varies from a hundreds of
kilobits to several megabits per second in relation of
connection by two most used standard GPRS and
WiFi. In the case of corporate information systems
or some types of facility management, zoological or
botanical gardens, libraries, museums or hospitals
information systems the WiFi infrastructure network
is often used to connect mobile device clients to
server. The theoretical maximal connection speed is
unfortunately usable only on laptops where high-
quality WiFi adapter is present. The rest of mobile
devices like PDAs family or Smartphones has a very
limited space in their case and a lower-quality WiFi
adapter is used. This is a limitation in any case of
such online systems where the large data files
(artifacts) are used and there is no way to preload
these artifacts before use of mobile device. I found
this problem as a very important and the rest of this
paper is about a problem specification and
possibility to solve it in some cases.
Our goal is to complement the data networking
capabilities of RF wireless LANs with accurate user
location and tracking capabilities for user needed
data prebuffering. This property is used as an
information ground for extension of information
system.
Location information is used to determine an
actual user position and his future position. A
number of experiments with the information system
have been performed; focusing on the position
determination is encouraged by the results. The
remainder of this paper describes the conceptual and
technical details.
2 BASIC CONCEPTS
AND TECHNOLOGIES
Why we want to locate the user? We need to know
users position in real time for prebuffering of data
from server to mobile client database. Data are
prebuffered for possible future use of them.
Why we cannot use classical model of user’s
requests and server’s response? Because of some
large amount of data is impossible to download to
PDA device in relatively short time. It is not only
about the artifacts size. In some cases, the tens or
hundreds clients must be served. The serving time
172
Krejcar O., Janckulik D. and Motalova L. (2009).
PROBLEM OF INEFFICIENT INTERNAL HARDWARE OF PORTABLE MOBILE DEVICES - Solving by Artifacts Prebuffering using Mobile Database
Cache.
In Proceedings of the International Conference on Wireless Information Networks and Systems, pages 172-175
DOI: 10.5220/0002227001720175
Copyright
c
 SciTePress

will increase in these cases as the test describes. By
this reason the size of artifacts need to be optimized
for the most effective ways of server connection,
size of data artifacts, access to the mobile database.
Figure 1 describing the schema of data
communication process from server to PDA
memory. I found the worse component in this
network is theoretically the WiFi Adapter on PDA
side.
Figure 1: WiFi adapter connection to internal bus.
Theoretical hypothesis must be documented with
real data transfers rate measurement. The first one
test was executed on transfer speed of large data size
artifacts throw the FTP protocol.
The process optimization was divided to three
basic parts:
We made a number of such tests with several
types of PDA devices (HTC Athena, HTC
Universal, HTC Blueangel, HTC Roadster). These
PDA devices were connected throw CISCO Wi-Fi
AP. The FTP server holds 3 types of large artifacts
(files) which were downloaded to internal PDA
memory.
Table 1: Transmission speed on large files.
Tran.
speed
[kB/s]
PDA device
Athena Universal Blueangel Roadster
data size
[MB]
Speed
[kB/s]
Speed
[kB/s]
Speed
[kB/s]
Speed
[kB/s]
10 347 123 160 106
20 344 121 157 79
40 314 123 58 43
Unafraid the real transfer rates (see Table 1)
were not achieved. The maximal transfer rate 350
kB/s has HTC Athena, but this device is not a
standard PDA device. Athena is a mini-notebook
with windows mobile 6 operating system. All of
others devices have only a quarter amount of such
speed. This fact is very important for our idea of
using a prebuffered data for increasing of transfer
speed throw WiFi connection on PDA mobile
devices.
This abysmal difference vamooses, when we use
for transfer smaller data files (10KB – 150KB). The
testing of data transfer throw web services was
executed on all of mentioned devices. Firstly the 50
kB and then the 150 kB data file were transferred.
The response time for one access and then for 100
access and finally for 500 access were measured.
The test results are in Table 2 and Table 3.
The third step to determine the optimal artifact
size is testing of database response for buffering.
The test was executed again on all mentioned
devices. The information about SQL server
response of SQL Server 3.5 Compact Edition was
stored.
The general principle states that if a WiFi-
enabled mobile device is close to such a stationary
device – Access Point (AP) it may “ask” the
provider’s location position by setting up a WiFi
connection. If the mobile device knows the position
of the stationary device, it also knows that its own
position is within a 100-meter range of this location
provider. Granularity of location can improve by
triangulation of two or several visible WiFi APs.
The PDA client will support the application in
automatically retrieving location information from
nearby location providers, and in interacting with the
server. Naturally, this principle can be applied to
other wireless technologies. The application
(locator) is now implemented in C# using the MS
Visual Studio .NET 2005 with .NET compact
framework and a special OpenNETCF library
enhancement.
3 PREDICTIVE DATA PUSH
TECHNOLOGY FRAMEWORK
This part of the project is based on a model of
location-aware enhancement, which I have used in
created information system. This technique is useful
in framework to increase the real dataflow from
wireless access point (server side) to PDA (client
side). Primary dataflow is enlarged by data pre-
buffering. These techniques form the basis of
predictive data push technology (PDPT). PDPT
copies data from information server to clients PDA
to be helpful when user comes at desired location.
PROBLEM OF INEFFICIENT INTERNAL HARDWARE OF PORTABLE MOBILE DEVICES - Solving by Artifacts
Prebuffering using Mobile Database Cache
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The benefit of PDPT consists of reduction of time
needed to display desired information requested by a
user command on PDA. Time delay may vary from
a few seconds to number of minutes. It depends on
two aspects.
First one is the quality of wireless Wi-Fi
connection used by client PDA. A theoretic speed of
Wi-Fi connection is max 687 kB/s, because of
protocol cost on physical layer (app. 30-40 %).
However, the test of transfer rate from server to
client’s PDA, which I have carried out within our
Wi-Fi infrastructure provided the result speed only
80 - 160 kB/s (depends on file size and PDA
device). The second aspect is the size of copied data.
Current application records just one set of signal
strength measurements at the time (by Locator unit
in PDPT Client). By this set of values the actual user
position is determined by the PDPT server side.
PDPT core responds to location change by selection
of the artifact to load to PDPT client buffer. The data
transfer speed is widely influenced by the size of
these artifacts. For larger artifact size the speed is
going down.
Theoretical background and tests were needed to
determine an average artifact size. First of all the
maximum response time of an application (PDPT
Client) for user was needed to be specified. A
special book (Nielsen J., 1994) of „Usability
Engineering” specified the maximum response time
for an application to 10 seconds (Haklay, M. and
Zafiri, A., 2008). During this time the user was
focused on the application and was willing to wait
for an answer. I used this time period (10 second) to
calculate the maximum possible data size of a file
transferred from server to client (during this period).
If transfer speed was from 80 to 160 kB/s the result
file size was from 800 to 1600 kB.
Table 2: Response time - 50KB artefacts [ms].
1 Artefact 100 Artefacts 500 Artefacts
Mode 101,82 5208,62 16036,61
Median 101,86 5228,54 16024,24
Average 102,00 5229,81 16022,67
Table 3: Response time - 150KB artefacts [ms].
1 Artefact 100 Artefacts 500 Artefacts
Mode 304,82 20208,93 61029,73
Median 301,85 20227,71 61026,08
Average 302,00 20229,99 61022,86
From the executed test over the web service is
evident; the artifacts of size from 50 to 150 kB are
more suitable for transfer. It is because the transfer
speed of them is relatively affordable in compare to
transferred data amount.
In this case is only a higher starter costs which
going to fall after first executed query. The SQL
server response results are better in case of 50 to 150
kB artifacts.
Graph 1: Web service reaction times.
The large artifacts are better in compare to 1Byte
transferred data, but the response is not optimal.
Unfortunately another one problem is here. The
problem is the time, which is needed for displaying
them. In case of Autocad file type I measured this
time to average 45 seconds. This time consumption
is certainly not acceptable, for this reason I am
looking for a better solution. We need to use some
basic data format, which can be displayed by PDA
natively (BMP, JPG, GIF) without any additional
striking time consumption
Such large artefact size is not only with slow
transfer speed, but they also allow move with steps,
which are not affordable for quicker move or more
accurately presentation of position in artefact. The
most of tests and problems passes from the size of
artefacts. Therefore we made a change to data
artefact size to maximal size of 150 kB and we
change also the access to these artefacts to new way.
1,00
10,00
100,00
1000,00
10000,00
100000,00
Responsetime[ms]
MODE MEDIAN AVERAGE
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PDPT framework design is based on the most
commonly used server-client architecture. To
process data the server has online connection to the
information system. Technology data are continually
saved to SQL Server database (Arikan E., Jenq J.,
2007), (Jewett M., Lasker S., Swigart S., 2006).
Figure 2: Old application buffering.
The active presented area was divided to more
partial artefacts. This new modified system is now
implemented to our other projects, where the
position of user is needed. One of these projects is a
Guardian II. This project is for hospitals areas for
patients and physicians monitoring. In such
implemented the new possibilities of biomedical e-
health systems are discovered for increasing of
interactivity. Based on position of patient, the server
can select the nearest physician or nurse to act on
discovered problem. By this way the response on
problem can be reduced and it can help to save more
human life. One of next steps is testing of accessible
technologies for accessing of SQL server buffer and
the selection of better one. In this time the testing of
technologies like LINQ, ADO.NET and the direct
access using SQL queries is being realized.
4 CONCLUSIONS
The main objective of this paper is in the
enhancement of information system for locating and
tracking of users inside a building. It is possible to
locate and track the users inside buildings. In this
paper I have presented the information system
framework that uses and handles location
information and information system functionality.
The indoor location of a mobile user is obtained
through an infrastructure of WiFi access points. This
mechanism measures the quality of the link of
nearby location provider access points to determine
actual user position. User location is used in the core
of server application of PDPT framework to data
prebuffering and pushing information from server to
user’s PDA. Data prebuffering is the most important
technique to reduce time from user request to system
response. It is important to give a high importance to
final optimalization of application.
The experiments show that the location
determination mechanism results with sufficient
quality of the actual location of the user in most
cases. Some minor inaccuracy does not major effect
on PDPT core decision making.
ACKNOWLEDGEMENTS
This work was supported by the Ministry of
Education of the Czech Republic under Project
1M0567.
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Prebuffering using Mobile Database Cache
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