Any complex system may potentially exhibit unpredicted and undesirable behaviour as a
result of certain combinations of input stimuli. An Active Network, being a
communication network in which user requested operations are undertaken in the
netwOIk nodes themselves, is a candidate to exhibit such behaviour. For example,
resource utilisation will be influenced by the specific combination of activities triggered
by the users and may develop undesirable characteristics such as a self-sustaining
profile. Conventional simulation tools do not detect such characteristics.
This thesis proposes a solution based on a Petri-Net model in which the resource
utilisation of the Active Network is abstracted above the link level communication
element. It is then suggested that a certain type of Emergence in resource utilisation may
manifest itself as Self-Similarity. The Hurst Parameter (H) of the resource utilisation
profile for each node in the network can then be used to identify the presence of this
characteristic. The RlS Statistic is used to estimate sets of H values for a range of
different Active Application scenarios. It is subsequently seen that a self-sustaining
resource utilisation profile (termed a "Cascading Effect") occurs when a significant
subset of the nodes display high values of H.
This thesis takes the view that Emergence in Active Networks is a problem that has to
be approached with a global comprehension of the system as opposed to the
conventional approach of a piecemeal development of solutions. This view is reinforced
by the hypothesis that an Active Network is a Complex System and Emergence is noncomplex
self-organisation within it. It proposes that the high-level abstraction of the
Active Network forms a view by which global comprehension can be obtained and is
used for the detection of anomalous behaviour (Le. Emergence). The key enabler for
self-organisation is proposed to be 'the resources' within the Active Network nodes and
hence the detection technique was focused on the utilisation characteristics of these.
A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.