Summary form only given, substantially as follows. The introduction of real-time network routing (RTNR) into the AT&T switched network was completed in July 1991, and completely replaced dynamic nonhierarchical routing (DNHR). RTNR provides the platform for the dynamic class-of-service routing features for emerging new services, and also a provides an ingress/egress routing arrangement to ensure reliability and flexibility for international and access networks. 10 virtual networks have been established to serve major classes-of-service, which share the facilities of the network but provide individual control and monitoring of traffic as well as new priority service capabilities. RTNR allows a marked improvement in network reliability by providing for the selection of over 135 routes between every pair of cities for every call. RTNR performance improvements are illustrated across various network conditions, which include: a) high day loads on the Monday after Thanksgiving, b) peak day loads on Thanksgiving and Christmas, c) a cable cut near Austin, Indiana, in which the combination of RTNR and automatic facility restoration provided excellent recovery from the failure, and d) the international network performance to Taiwan during the Chinese New Year three-day holiday calling period. We conclude that RTNR improves network performance under all network conditions, that it simplifies the operations environment and lowers operations cost, and that it enables the sharing of voice and data network capacity.

Real-time network routing (RTNR) is a new adaptive routing method. With RTNR, switches have a simple way of exchanging link status bit map information, thereby determining the availability and load conditions of the direct and all two-link paths to the destination. Link busy-idle status is exchanged between the network nodes using a bit map data exchange through the common channel signaling (CCS) network, and calls are set up where there is the most available capacity in the network. To date the analysis of RTNR networks has been limited to simulation models. The present authors develop an analytical model for the AT&T network under RTNR, which is shown to provide good agreement with simulation models. The analytical model for RTNR networks uses an Erlang fixed point method to solve the nonlinear equations describing dynamical network behavior. The equations include the link state probability, network flows, link arrival rates, adaptive trunk reservation level, and adaptive path selection depth. The link state model provides the aggregate link state probabilities through solution of the birth-death equations, and models the adaptive nature of trunk reservation. The network flow model provides a method to calculate the traffic flow using the least busy concept employed in RTNR, and also models the adaptive nature of the path selection depth. The analytical model addresses asymmetrical networks, and computational examples show the differences from the simulation model to be small. The authors also use the analytical model to examine key RTNR parameters over a range of values.>

The authors present traffic restoration design algorithms to attain a robust network for any facility link or node failure. Some of these algorithms were implemented on network models to compute the cost for doing traffic restoration for different traffic restoration level objectives. From their simulation studies, the authors found that with efficient use of trunk group diversity and at a reasonable incremental cost, one can obtain a robust network to respond to a major facility link or a node failure and still meet the network objectives. A similar approach based on the algorithms presented in this work has been proposed for design of the worldwide intelligent network.>

The authors describe the structure of the worldwide intelligent network (WIN), describe methods for its design and planning, investigate the adequacy of decentralized control for problem-free worldwide call completion, explore the feasibility of adaptive routing and control concepts, discuss network robustness/reliability objectives, and describe a strategy for achieving these objectives for all cooperating international carriers. Several decentralized adaptive routing policies that are particularly attractive in the WIN environment and network performance improvements that can be achieved with the introduction of flexible routing capabilities are characterized. It is shown by example that network integration coupled with flexible routing and bandwidth allocation for preferential treatment of new services provides an effective approach for robust and economical new service provisioning.>