12.2.2 Neural Networks as Adaptatio

12.2.2 Neural Networks as Adaptation Policies
Various projects have attempted to simplify the process of reconfiguration by mapping application specified QoS requirements to protocol configurations. Work by Box et al. (1992) and Zitterbart (1993) classified applications into service classes according to Table 12.1 and mapped each to a predefined protocol configuration. The DaCaPo project uses a search based heuristic, CoRA (Plagemann et al., 1994), for evaluation and subsequent renegotiation of protocol configuration. The classification of building blocks and measurement of resource usage are combined in a structured search approach enabling CoRA to find suitable configurations. The properties of component functions, described in a proprietry language L, are based on tuples of attribute types such as throughput, delay and loss probability. CoRA configures protocols for new connections at runtime with respect to an applications requirements, the characteristics of the offered transport service and the availability of end system resources. The second approach provides a greater degree of
customisation, but the time permitted to locate a new configuration determines the quality of solution found. Beyond these investigations there is little work on heuristics for the runtime optimisation of protocol configuration.
In the search for a more efficient method of performing this mapping, an approach
similar to that used in Bhatti and Knight (1998) for processing QoS information about
media flows was considered. However, the volume of data required to represent and reason about QoS rendered this solution intractable for fine-grained protocol configuration in an Operating System environment. Although impractical, this served to highlight the highly consistent relationships between conditions, requirements and the actual performance of individual configurations. For example, consider two requirements, bit error tolerance and required throughput, and a protocol with variable error checking schemes. The more comprehensive the error checking, the greater the impact it has on throughput. This is the206 Telecommunications Optimization: Heuristic and Adaptive Techniques case for processing overhead (raw CPU usage) and knock-on effects from the detection of errors (packet retransmission). As emphasis is shifted from correctness to throughput, the
selection of error function should move from complete to non-existent, depending on the level of error in the end-to-end connection.