An Event-based Diffusion LMS Strategy

We consider a wireless sensor network consists of cooperative nodes, each of them keep adapting to streaming data to perform a least-mean-squares estimation, and also maintain information exchange among neighboring nodes in order to improve performance. For the sake of reducing communication overhead, prolonging batter life while preserving the benefits of diffusion cooperation, we propose an energy-efficient diffusion strategy that adopts an event-based communication mechanism, which allow nodes to cooperate with neighbors only when necessary. We also study the performance of the proposed algorithm, and show that its network mean error and MSD are bounded in steady state. Numerical results demonstrate that the proposed method can effectively reduce the network energy consumption without sacrificing steady-state network MSD performance significantly

Secure Information Sharing in Adversarial Adaptive Diffusion Networks

In this paper, information sharing over adversarial adaptive networks is considered. Defense against adversarial attacks is enforced by an attack detection mechanism that guides the diffusion strategy in the parameter estimation task and the transmission decisions of agents. The latter are taken to maximize long-term rewards, expressed in terms of estimation performance, communication cost, and illegal gains in a nonzero sum repeated game with imperfect action monitoring. In order to track agents' behavior and stimulate cooperation, a reputation protocol is designed, along with the deployment of a set of honest nodes whose behavior is consistent with the reputation protocol. An algorithm that promotes cooperation and can achieve secure parameter estimation is described and illustrated by simulations. © 2015 IEEE