2. Research On Streaming Media Online Charging System

A. Summary of data accessing methods
The widely used data accessing methods including Open
Database connectivity (ODBC) method, sharing memory
method [11] and the main memory database method [12], etc.
The introductions to them are as follows.
By ODBC method, data updating and inquiry are realized
by Database Management System (DBMS) and the data
needed in applications is accessed from the database through
ODBC. Data management and transaction assurance are
implemented by DBMS, which greatly reduces the difficulty
of application development. Data accessing relies on DBMS
by this method, so the delay of SMOCS’s response to charging
requests will increase and concurrency performance of
SMOCS will be limited by the overall performance of used
database.
By sharing memory method, the data storied in shared
space of main memory is provided for all processes and we
don’t have to save more copies. The relatively stable or readonly
data can be rapidly accessed through shared memory. The
application program does the data updating procedure and
ensures the consistency of the data between shared memory
and database, and thus it increases the difficulty to the
development of application program. By this method we can
access stable data easily, but can’t handle the frequent data
updating procedure effectively in SMOCS.
By main memory database method, almost all data are
stored in main memory to be operated directly. Architecture of
main memory database has been re-designed on the basis of all
data in main memory, and corresponding improvement has
been made in data cache mechanism, fast algorithms, parallel
operations, etc. So the data processing speed of main memory
database is 10 to 100 times that of traditional database. Main
memory database such as TimesTen [13] and eXtremeDB has
been widely used in applications.
B. Performance optimization of Streaming Media Online
Charging System based on Main Memory Database
Through the analysis of data accessing methods above, we
can greatly improve the efficiency of data accessing. It is
realized by adopting main memory database to manage
customers’ basic information, account balance, accumulated
usage and fees, session information, and billing detail
information in SMOCS. This can greatly improve the speed of
online charging, concurrency and real-time performance of
SMOCS. So a main memory database function (MMDB
Function) module is added to SMOCS’s framework to manage
data information, which not only can reduce the difficulty of
developing SMOCS, but also improve overall performance of
the system. Integrated with main memory database, new
framework of SMOCS is shown in Figure 3.
Making use of main memory database, the new SMOCS
has the following additional advantages:
• Data accessing speed of SMOCS can be improved
greatly due to the storage of account balance, the
accumulated usage and fee, and session information in
main memory;
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• The main memory database not only improves the
speed of data accessing, but also ensures the data
integrity and reliability by its own copy mechanism
and security strategy;
• For large-scale concurrent charging requests and
shared data accessing, adopting lock mechanism in
main memory database, SMOCS ensures that multithreads/processes
can access critical data safely, and
thus reduces the difficulty of system development.
Figure 3. Framework of SMOCS based on main memory database
IV. EXPERIMENTAL RESULTS
To verify reasonableness of SMOCS’s framework and
performance optimization results of the system, the functions
and performance of the system are tested, with the emphasis
on the average online charging response time. Description of
the test is as follows.
• Oracle9i and Oracle Times Ten In-Memory Database
7.0.5 as database were used respectively. The database
and SMOCS were deployed on two different servers in
the LAN.
• The online charging process of VoD service was
tested. There were 10,000 videos charged by times,
each video was charged differently and every
customer’s ceiling charges are less than��10 within
an account cycle.
• A condition of 100,000 customers sending 100,000
charging requests in all was simulated, and the
customers’ basic information and account balance
were stored in database. The session information and
billing details produced during the online charging
process were saved into database.
• The online charging process was simplified as
initializing a session, accessing customer’s account
balance and accumulated usage, rating, deducting
service fees and generating billing details, the
processing time of online charging was recorded in the
test and the average processing time was computed.
The test includes the following two groups:
• Shared memory scheme. The SMOCS loaded the
customers’ basic information and account balance,
price information of videos and other data at startup,