This paper addresses the optimization and performability of survivability strategies used in the next generation of high-capacity optical transport networks based on wavelength division multiplexing (WDM) technology. The framework of survivability presented is based on the self-healing mechanism used in SONET/SDH. The key issue addressed is how to determine the number of redundant components and wavelength units necessary to achieve a guaranteed level of survivability. A multi-modal failure probability model is developed and used in the reliability model of optical components. The multi-modal reliability analysis is used in conjunction with a reliability optimization technique to determine the optimum number of redundant components and wavelengths necessary in a SONET/WDM network to achieve a given degree of survivability.

IP has emerged as the internetworking protocol of choice. IP is a best-effort protocol which provides no guarantee of delivery or ordering of packets at their destination. IP is designed to be transparent to the topology of the underlying transport network. This transparency is provided by a framing protocol operating over the data link or MAC layer. Due to the popularity of IP, attempts are underway to transport IP traffic over transport networks such as ADSL, HFC, ATM, SONET/SDH, and WDM. This paper examines the dynamics of IP traffic over SONET/SDH using PPP in HDLC-like framing. Although IP in ATM framing (IP/ATM/SONET) is also presented, the main focus of this paper is on IP/PPP/SONET and its extensions, such as PPP multilink, and PPP tunneling protocol. A discussion on the applicability of these PPP extensions to wavelength division multiplexing (WDM) networks is also presented in the conclusion.

We present a distributed fuzzy agent architecture with applications to network management and control. Each agent is designed to mimic human problem solving abilities in a network environment with monitoring and control objectives. In this fuzzy agent framework, each agent is equipped with a fuzzy micro-expert system, consisting of a fuzzy knowledge-base and an inference engine. The knowledge-base is a collection of fuzzy rules derived from an expert and represented as fuzzy conditional statements. Each agent is configured to react to precepts from its local environment and also to commands decoded in messages received from other fuzzy agents. The agents' actions have local or external behaviors. Local behaviors are mainly due to environmental sensors while external behaviors consist of collaborative control messages forwarded to other fuzzy agents.

In this article, we present a formalism for embedding fuzzy logic into object-oriented methodology in order to deal with the uncertainty and vagueness that pervade knowledge and object descriptions in the real world. We show how fuzzy logic can be used to represent knowledge in conventional objects, while still preserving the essential features of object-oriented methodology. Fuzzy object attributes and relationships are defined and the framework for obtaining fuzzy generalizations and aggregations are formulated. Object's attributes in this formalism are viewed as hybrids of crisp and fuzzy characterizations. Attributes with vague descriptions are fuzzified and manipulated with fuzzy rules and fuzzy set operations, while others are treated as crisp sets. In addition to the fuzzification of the object's attributes, each object is provided with a fuzzy knowledge base and an inference engine. The fuzzy knowledge base consists of a set of fuzzy rules and fuzzy set operators. Objects with a knowledge base and an inference engine are referred to as intelligent objects. © 1997 John Wiley & Sons, Inc.

This paper presents the design of a fuzzy controller for managing cells generated by voice sources in asynchronous transfer mode (ATM) networks. Typical voice cells, characterized by a high degree of burstiness, complicate any attempt to use classical control theory in the design of an ATM cell rate controller. The fuzzy control approach presented in this paper overcomes this limitation by appealing to the linguistic ability of fuzzy set theory and logic to handle the complexity. Specifically, the cell rate control problem is linguistically stated but treated mathematically via fuzzy set manipulation. In particular, the ATM voice cell controller being proposed is an improved and intelligent implementation of the leaky bucket cell rate control mechanism extensively studied in the literature. This intelligent implementation of the leaky bucket mechanism uses a channel utilization feedback via the QoS parameters to improve its performance. This ATM fuzzy controller takes the form of an organized set of linguistic rules quantitatively expressed and manipulated by means of fuzzy set theory and fuzzy logic. The fuzzy control rules are stored in fuzzy associative memory to permit parallel executions.>