We address the relevant issue of managing traffic flows with different priorities in packet switched networks, namely ATM and IP networks. We consider a reference model in which two traffic flows with different priorities are multiplexed within the buffer of a cell-based switch. The solution we propose, based on the fuzzy system theory, is able to guarantee the QoS requirements of high-priority traffic flow, allowing at the same time the exploitation of unused buffer resources to accommodate low-priority traffic flow in order to maximize the total throughput. The performance assessment of the fuzzy scheme demonstrates that our solution outperforms other popular mechanisms, based on conventional logic, such as threshold and push out mechanisms.

We assess the application of artificial intelligence techniques to the complex problem of traffic control in ATM networks. The paper deals with the close link between call admission control and usage parameter control and proposes a simulation-based analysis to demonstrate how inefficiency on the part of policing affects bandwidth allocation. To take this into account, the paper proposes a framework for traffic control in which the CAC and policing functions are both based on artificial intelligence techniques, i.e. neural networks and fuzzy logic. In this way it is possible to train the neural network in such a way as to take into account the real behavior of the policer. As the results obtained show this allows us to implement traffic management strategies which can improve the exploitation of network resources.

Concerns a fuzzy logic-based system which has been purposely designed to achieve real-time traffic control in high-speed networks using the asynchronous transfer mode (ATM) technique. One of the most critical functions is "policing", which has the task of ensuring that each user source complies with the traffic parameters negotiated in the call setup to avoid network congestion. This function is difficult to implement on account of certain conflicting requirements such as selectivity and responsiveness. This is confirmed by the severe limits affecting the most popular mechanisms proposed so far, based on conventional logic. The capacity to formalize approximate reasoning processes offered by fuzzy logic is exploited to derive rules of behavior for a policer starting from the know-how of an expert. We address two key issues related to the implementation of the fuzzy policer. The first focuses on the possibility of hardware implementation of the mechanism using VLSI technology; we present the design of a VLSI fuzzy processor which exhibits a level of performance of over 3 MFLIPS. The second issue concerns the suitability of applying the fuzzy policer to the policing of several classes of sources to reach high levels of cost effectiveness and scalability.

In ATM networks, usage parameter control is required in order to ensure that each source conforms to its negotiated parameters. To this purpose, several policing methods, such as leaky bucket and window mechanisms, have been introduced in literature. However, traditional methods have proved to be inefficient in coping with the conflicting requirements of ideal policing, that is, a low false alarm probability and high responsiveness. This led us to explore alternative solutions based on artificial intelligence techniques, specifically, in the field of fuzzy systems. We propose a policing mechanism based on fuzzy logic that aims at detecting violations of the parameters negotiated. The main characteristics of the proposed fuzzy policer are simplicity and the capacity to combine a high degree of responsiveness with a selectivity close to that of an ideal policer. Moreover, it can easily be implemented in hardware, thus, enhancing both cost and processing performance. The reported simulation results show that the performance of our fuzzy policer is much better than that of conventional policing mechanisms.

Most of the policing techniques proposed so far in high speed networks using the ATM technique are based on conventional approaches which use a crisp decision making logic. They don't meet the selectivity and responsiveness requirements needed to make a policing efficient. In this paper we propose a policing mechanism based on fuzzy logic. The main characteristics of the proposed fuzzy policer are simplicity and the capacity to combine a high degree of responsiveness with a selectivity close to that of an ideal policer. Moreover, it can easily be implemented in hardware, thus enhancing both cost and processing performance. The simulation results reported show that the performance of our fuzzy policer is much better than that of conventional policing mechanisms.

Traffic management in ATM networks aims for the controlled use of network resources to prevent the network from becoming a bottleneck. This is a very complex task due to the random nature of the traffic arrival pattern and contention for network resources. In this paper we deal with one of the most important aspects of traffic control: "the policing". It has the role of ensuring that each source complies with the traffic parameter negotiated, in order to avoid network congestion. We present a policing mechanism based on Fuzzy Logic. As far as selectivity and dynamic response are concerned, it outperforms traditional mechanism thanks to the softness which characterizes Fuzzy Logic. In the paper we also address the design of a VLSI fuzzy processor to implement the mechanism in hardware. The processor is organized as a cascade of pipeline stages in which fuzzy inferences are processed in parallel. A synthesis on CMOS 0.5 /spl mu/m technology has allowed the processor to reach a very high processing speed occupying only a few mm/sup 2/ of silicon area, thus requiring a very low implementation cost.