Distributed Connectivity Restoration Strategy for Movable Sensor Networks

Failure of one or multiple critical nodes may partition wireless sensor networks into disjoint segments, and thus brings negative effect on the applications. We propose DCRS, a Distributed Connectivity Restoration Strategy to tolerate the failure of one critical node. Because of the energy restriction of sensor nodes, the energy overhead of the recovery process should be minimized to extend the lifetime of the network. To achieve it, we first design a novel algorithm to identify 2-critical nodes only relying on the positional information of 1-hop neighbors and some 2-hop neighbors, and then we present the criteria to select an appropriate backup for each critical node. Finally, we improve the cascaded node movement algorithm by determining whether a node can move to another non-adjacent node directly or not to reduce the number of nodes moved. The effectiveness of DCRS is validated through extensive simulation experiments.

Fault-tolerant finite-time dynamical consensus of double-integrator multi-agent systems with partial agents subject to synchronous self-sensing function failure

This paper investigates fault-tolerant finite-time dynamical consensus problems of double-integrator multi-agent systems(MASs)with partial agents subject to synchronous self-sensing function failure(SSFF).A strategy of recovering the connectivity of network topology among normal agents based on multi-hop communication and a fault-tolerant finitetime dynamical consensus protocol with time-varying gains are proposed to resist synchronous SSFF.It is proved that double-integrator MASs with partial agents subject to synchronous SSFF using the proposed strategy of network topology connectivity recovery and fault-tolerant finite-time dynamical consensus protocol with the proper time-varying gains can achieve finite-time dynamical consensus.Numerical simulations are given to illustrate the effectiveness of the theoretical results.

Fault-Tolerant Dynamical Consensus of Double-Integrator Multi-Agent Systems in the Presence of Asynchronous Self-Sensing Function Failures

Double-integrator multi-agent systems(MASs)might not achieve dynamical consensus,even if only partial agents suffer from self-sensing function failures(SSFFs).SSFFs might be asynchronous in real engineering application.The existing fault-tolerant dynamical consensus protocol suitable for synchronous SSFFs cannot be directly used to tackle fault-tolerant dynamical consensus of double-integrator MASs with partial agents subject to asynchronous SSFFs.Motivated by these facts,this paper explores a new fault-tolerant dynamical consensus protocol suitable for asynchronous SSFFs.First,multi-hop communication together with the idea of treating asynchronous SSFFs as multiple piecewise synchronous SSFFs is used for recovering the connectivity of network topology among all normal agents.Second,a fault-tolerant dynamical consensus protocol is designed for double-integrator MASs by utilizing the history information of an agent subject to SSFF for computing its own state information at the instants when its minimum-hop normal neighbor set changes.Then,it is theoretically proved that if the strategy of network topology connectivity recovery and the fault-tolerant dynamical consensus protocol with proper time-varying gains are used simultaneously,double-integrator MASs with all normal agents and all agents subject to SSFFs can reach dynamical consensus.Finally,comparison numerical simulations are given to illustrate the effectiveness of the theoretical results.