THE NODE VECTOR DISTANCE PROBLEM IN EVOLVING COMPLEX NETWORKS

A moving agent in a network may spread news or disease among connected people. The Node Vector Distance (NVD) problem concerns changes in the activity of a moving agent across a complex network. This problem estimates how fast and how far the agent has travelled through the network. The network is observed at two different times, with the aim of estimating changes in the agent's intensity and position. To achieve this, the distance between observed node vectors is calculated. Different families of algorithms exist for this recently studied problem, and all of them assume that the structure of the network is fixed during these observations. However, in real-world use cases, it is possible for the network to change its structure: in online social networks, new users may be added or some old users may be removed from the network, and it is also possible to add new edges. In this paper, we study the node vector distance problem in evolving complex networks and adopt available algorithms using the appropriate temporal data structure to measure travelled distance by agents in networks with dynamic structures. Experiments indicate that measured distances by temporal event labeling are consistent with expectations.

کلیدواژه ها:

social networks ، structural change ، spreading events ، temporal graphs