Implementation Of An Admission Controller For High ... - IEEE Xplore

WPM 14.8 Implementation of an Admission Controller for High-speed Multimedia Networks Li-Fong Lin*, Zohn-Shiun Eul*, Ray-Guang Cheng+, AND Chung-Ju Chang* * Dept. of Communication Engineering

National Chiao Tung University Hsinchu, TAIWAN, Republic of China

Computer and Communications Research Labs. Industrial Technology Research Institute Chutung, Hsinchu, TAIWAN, Republic of China

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Abstract I n the paper, we use a fuzzy development toolkit to implement a neural fuzzy connection admission (NFCAC) scheme proposed in [ 2 ] . The setting of the fuzzy rule bases and their related parameters can be easily done via the aid of the graphic user interface. The system also provides the function of on-line debugging to monitor and modify (control) the NFCAC scheme on a remote PC through RS-232. The user transmits its call request parameters t o the controller through the standard RS-232 COM ports, and the emulated NFCAC controller returns its decision t o the user according t o the characteristics of the network a n d the new user. Based on our studies, we conclude that the proposed NFCAC scheme would be a promising and realizable approach to the connection admission control issues in high-speed multimedia network.

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Introduction

High-speed network supporting multimedia services has t o be capable of handling bursty traffic and satisfying various quality-of-service &OS)and bandwidth requirements. Therefore, a mu timedia high-speed network must have an appropriate connection admission control (CAC) scheme not only t o guarantee QoS for existing calls but also t o achieve high system utilization. We have proposed a neural fuzzy connection admission control (NFCAC) scheme, which absorbs benefits of the conventional, fuzzy-logic-based, and neural-netbased approaches, while minimizing their drawbacks, for multimedia high-speed networks. In this paper, the implementation of the proposed NFCAC is illustrated by employing a hardware development toolkit and is realized by using the 80C166 microprocessor. In the implementation of the NFCAC scheme, the setting of the fuzzy rule bases and their related parameters can be easily done via the aid of graphic user interface. The proposed NFCAC scheme is then translated t o machine codes of different platforms. On-line debugging mode is provided by the toolkit t o monitor and modify (control) the NFCAC scheme on a remote P C through RS-232. In the demonstration program, the user transmits his call request parameters t o the controller through the standard RS-232 COM ports and the emulated NFCAC controller will return its deci-

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sion t o the user according t o the characteristics of the network and the new user.

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Figure 1: The flow chart of the simulation program. The functional module structure/configuration of the program is illustrated in Fig. 2. For the functions

254 0-7803-4357-31981$10.00 0 1998 IEEE

Implementation of NFCAC

In the implementation of the NFCAC scheme, the first thing is t o train the neural-fuzzy inference engine by a neural network, provided by the toolkit, t o get optimal membership functions. Then we set the optimal membership functions and fuzzy inference rules in the toolkit, and translate them t o a specific assembly code for the evaluation board. Finally, we can verify and fine tune the NFCAC scheme under off-line or on-line debugging mode. A program designed t o simulate the operation of the ATM connection admission control (CAC) is provided. The program contains two parts, one is used to simulate the CAC process of an ATM node, the other acts as the graphical user interface. Fig. 1 depicts the flow chart where the gray blocks indicate that they belong t o the graphical user interface part and the white blocks indicate that they belong to the CAC simulation part.

and subroutines of the COM port, we have adopted the programming algorithm, interrupt service routine (ISR), to implement the 1/0 function as the data receiver and transmitter with the ATM node simulation program. This communication could be realized on RS-232 interface. The input ISR (receiver) is triggered while the simulation program sends the data to be computed by the CAC inference engine, and put the received data in a common buffer. The CAC inference engine then gets these data and performs the computation. The computation result will be returned by the output ISR (transmitter) t o the ATM node simulation program to decide whether to accept or reject the call request. The main body of the program on includes fuzzy inference engine function and RTRCD on-line debugging module. The fuzzy inference engine is based on the fuzzy inference computation kernel of the toolkit. The RTRCD on-line debugging function is generated by the toolkit and is integrated in the program t o support on-line debug.

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Figure 3: Emulation of the NFCAC controller. ted from admitted users, are stored in the queues (12) and (14). The maximum capacity of each queue is 100 cells. At the right hand side of the queues, we can see departing cells (13) also as colored rectangles. The information panel (8) is beneath the queues. It contains information such as the system time, the bandwidth utilization, queue CLR, the number of voice connections, and the video blocking rate. The correspondence between the traffic type and the color is given in (11). When the queue is full, the subsequent arriving cells will be discarded. Two genies (7) are waiting outside the queue to swallow the discarded cells from the queues.

3 Figure 2: Functional modules of the program. As shown in Fig. 3, the program can be running in three modes: the Manual mode, the fT-Link debugging mode, and the On-Line debugging mode. Users are allowed to switch between these operation modes. Under the Manual mode, user acts as a decision maker of the CAC controller. A rejection/acceptance decision is accomplished by pushing the ‘X’/‘O’ button. The controlled performance is depending on user’s knowledge. Under fl-Link mode, the NFCAC is emulated by the toolkit. The rejection/acceptance decision is made by the NFCAC controller. Users can monitor the detail operation of the NFCAC and verify the setting of rules and parameters. The On-line mode works in a similar manner as the fT-Link mode does. However, the NFCAC is downloaded to a microprocessor on an emulation board in this mode. The simulation program exchanges information with the micro-processor through the RS-232 interface. The ‘X’/‘O’ button will be triggered according to the decision of the micro-processor. The CAC controller will automatically switch to the Manual mode when the emulation board is not connected t o the RS232 interface or the chip on the board is not responding. The emulated CAC process is depicted in Fig. 3. As shown in Fig. 3, the NFCAC controller (9) received a call request (1) and responses by the acceptance (2) or rejection (3) decision. Cells (4), (5), (6), transmit-

Concluding Remarks

In the paper, we emulated the NFCAC scheme by a development toolkit and an emulation board. The setting of the rule and parameters of NFCAC are accomplished via the aid of graphic user interface. A program providing the function of on-line debugging is demonstrated. It can be used to monitor and modify the NFCAC scheme manually on a remote P C through RS-232. The process of CAC is emulated where a user transmits his call request parameters t o the controller through RS-232 and the emulated NFCAC controller returns its decision to the user according t o the characteristics of the network and the new user. Based on our studies, we can conclude that the NFCAC scheme would be a realizable approach t o the CAC related issues in high-speed multimedia network.

References [l] R. G. Cheng and C. J. Chang, “Design of a fuzzy traffic controller for ATM networks,” IEEE/ACM Trans. Networking, vol. 4, no. 3, pp. 460-469, June 1996.

[2] R. G. Cheng and C. J . Chang, “A neural-net based fuzzy admission controller for an ATM network,” IEEE INFOCOM ’96, pp. 777-784, SanFancisco, March 1996.

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