Identifying Topological Variations From Network Dynamics
Identifying Topological Variations From Network Dynamics
Human circulatory system is one of the largest logistics systems
Indicator for many ailments and diseases
A number of illnesses may be mapped to the degradation in the circulatory network.
Degradation in network structures can be mapped to :
Variation of coupling across the nodes in time
Addition or removal of nodes/edges
Derivation of indicators for structural degradation may not be easy owing to their:
large and complex structure (may not be accurate at finer levels)
Limited availability of state measurements (physical and technical limitations)
Motivated by this, our project aims to study network dynamics in general, trying to asnwer:
How do the topological deviations affect the network dynamics
How does the information about topogical change gets transmitted in the network
What are the time constants associated with the information propogation
What are the indicators of this change which can be calcuated from sparse measurements
Setup
We consider a network of nodes with arbitrary connectivity with:
Regular Node: Standard node evolving based on prescribed dynamics.
Root Node: Can be influenced by external inputs to guide the network.
Observable Node: Node whose activity can be measured for monitoring.
Defective Node: Node with weakened or broken connections affecting performance.
Node dynamics follow the well-studied Kuramoto dynamics