  Research into active networking has provided the incentive to re-visit what
has traditionally been classified as distinct properties and characteristics of
information transfer such as protocol versus service; at a more fundamental
level this paper considers the blending of computation and communication by
means of complexity. The specific service examined in this paper is network
self-prediction enabled by Active Virtual Network Management Prediction.
Computation/communication is analyzed via Kolmogorov Complexity. The result is
a mechanism to understand and improve the performance of active networking and
Active Virtual Network Management Prediction in particular. The Active Virtual
Network Management Prediction mechanism allows information, in various states
of algorithmic and static form, to be transported in the service of prediction
for network management. The results are generally applicable to algorithmic
transmission of information. Kolmogorov Complexity is used and experimentally
validated as a theory describing the relationship among algorithmic
compression, complexity, and prediction accuracy within an active network.
Finally, the paper concludes with a complexity-based framework for Information
Assurance that attempts to take a holistic view of vulnerability analysis.
