A versatile policy toolkit supporting run-time policy reconfiguration

This paper describes an autonomics development tool which serves as both a powerful and flexible policy-expression language and a policy-based framework that supports the integration and dynamic composition of several autonomic computing techniques including signal processing, automated trend analysis and utility functions. Each of these technologies has specific advantages and applicability to different types of dynamic adaptation. The AGILE platform enables seamless interoperability of the different technologies to each perform various aspects of self-management within a single application. Self-management behaviour is specified using the policy language semantics to bind the various technologies together as required. Since the policy semantics support run-time re-configuration, the self-management architecture is dynamically composable. The policy language and implementation library have integrated support for self-stabilising behaviour, enabling oscillation and other forms of instability to be handled at the policy level with very little effort on the part of the application developer. Example applications are presented to illustrate the integration of different autonomics techniques, and the achievement of dynamic composition.

Model-based pilot and data power adaptation in psam with periodic delayed feedback

We consider the optimum design of pilot-symbol-assisted modulation (PSAM) schemes with feedback. The received signal is periodically fed back to the transmitter through a noiseless delayed link and the time-varying channel is modeled as a Gauss-Markov process. We optimize a lower bound on the channel capacity which incorporates the PSAM parameters and Kalman-based channel estimation and prediction. The parameters available for the capacity optimization are the data power adaptation strategy, pilot spacing and pilot power ratio, subject to an average power constraint. Compared to the optimized open-loop PSAM (i.e., the case where no feedback is provided from the receiver), our results show that even in the presence of feedback delay, the optimized power adaptation provides higher information rates at low signal-to-noise ratios (SNR) in medium-rate fading channels. However, in fast fading channels, even the presence of modest feedback delay dissipates the advantages of power adaptation.