Fuzzy Logic Control Techniques and Structures for Asynchronous Transfer Mode (ATM) Based Multimedia Networks

The research presented in this thesis aims to demonstrate that fuzzy logic is a useful tool for developing mechanisms for controlling traffic flows in ATM based multimedia networks to maintain quality of service (QoS) requirements and maximize resource utilization. The study first proposes a hierarchical, multilevel control structure for ATM networks to exploit the reported strengths of fuzzy logic at various control levels. Then, an extensive development and evaluation is presented for a subset of the proposed control architecture at the congestion control level. An ATM based multimedia network must have quite sophisticated traffic control capabilities to effectively handle the requirements of a dynamically varying mixture of voice, video and data services while meeting the required levels of performance. Feedback control techniques have an essential role for the effective and efficient management of the resources of ATM networks. However, development of conventional feedback control techniques relies on the availability of analytical system models. The characteristics of ATM networks and the complexity of service requirements cause the analytical modeling to be very difficult, if not impossible. The lack of realistic dynamic explicit models leads to substantial problems in developing control solutions for B-ISDN networks. This limits the ability of conventional techniques to directly address the control objectives for ATM networks. In the literature, several connection admission and congestion control methods for B-ISDN networks have been reported, and these have achieved mixed success. Usually they either assume heavily simplified models, or they are too complicated to implement, mainly derived using probabilistic (steady-state) models. Fuzzy logic controllers, on the other hand, have been applied successfully to the task of controlling systems for which analytical models are not easily obtainable. Fuzzy logic control is a knowledge-based control strategy that can be utilized when an explicit model of a system is not available or, the model itself, if available, is highly complex and nonlinear. In this case, the problem of control system design is based on qualitative and/or empirically acquired knowledge regarding the operation of the system. Representation of qualitative or empirically acquired knowledge in a fuzzy logic controller is achieved by linguistic expressions in the form of fuzzy relational equations. By using fuzzy relational equations, classifications related to system parameters can be derived without explicit description. The thesis presents a new predictive congestion control scheme, Fuzzy Explicit Rate Marking (FERM), which aims to avoid congestion, and by doing so