Data similarity aware dynamic nodes clustering for supporting management operations

Wireless Sensor Networks (WSNs) are an important interface between physical and computational environments, where nodes clustering is a common technique to organize its traffic. Although current clustering protocols are focused on various kinds of dynamicity on the network, such as mobility or cluster-head rotations, few solutions consider the readings similarity management, which would provide benefits in terms of better use of compression techniques and reactive detection of anomalous events. This paper proposes a dynamic clustering protocol, called DDFC, that manages spatial similarity between nodes readings. Its operation is based on the biological principles of fireflies to ensure distributed synchronization of the cluster´s similar readings aggregations, differentiating thus from the classic use of fireflies. Simulations show that DDFC is capable of maintaining the cluster´s readings aggregation synchronized, hence clustering nodes dynamically according to their similar readings.