Event-Triggered Decision Propagation in Proximity Networks - Sarkar, Soumik; Mukherjee, Kushal (Frontiers in Robotics and AI, 2014)
This paper proposes a novel event-triggered formulation as an extension of the recently develo- ped generalized gossip algorithm for decision/awareness propagation in mobile sensor networks modeled as proximity networks. The key idea is to expend energy for communication (message transmission and reception) only when there is any event of interest in the region of surveillance. The idea is implemented by using an agent’s belief about presence of a hotspot as feedback to change its probability of (communication) activity. In the original formulation, the evolution of network topology and the dynamics of decision propagation were completely decoupled which is no longer the case as a consequence of this feedback policy. Analytical results and numeri- cal experiments are presented to show a significant gain in energy savings with no change in the first moment characteristics of decision propagation. However, numerical experiments show that the second moment characteristics may change and theoretical results are provided for upper and lower bounds for second moment characteristics. Effects of false alarms on network formation and communication activity are also investigated.