Topology adaptation for robust ad hoc cyberphysical networks under puncture-style attacks

Topology adaptation for robust ad hoc cyberphysical networks under puncture-style attacks Many cyber physical networks will involve ad hoc deployments utilizing peer-to-peer communications. Examples include transportation systems where a group of moving cars communicate in order to avoid collisions, teams of robotic agents that work together in support of disaster recovery, and sensornetworks deployed for health-care monitoring, monitoring the operation of a factory plant or tocoordinate and actuate mechanisms for energy conservation in a building. These networks may face a variety of threats that puncture their connectivity and, should their performance degrade, the result could be catastrophic. Consider, for example, a vehicular ad hoc network where communication assists collision avoidance. In such a case, degradation could lead to vehicle accidents. Therefore, in order toovercome network performance degradations and the puncture of a network (such as blackhole or jamming) which is under attack, we propose an algorithm called the Fiedler Value Power Adjustment Topology Adaption (FVPATA).

FVPATA aims to dynamically adapt an ad hoc network???s topology, even if the attacker varies its location and in the case of an interference-style attack by increasing the interference power. The algorithm utilizes the formulation from the graph theory which works with the Fiedler value to guide each node in wireless ad hoc network utilizing power adjustments to enhance thenetwork???s overall robustness. The advantage of the proposed mechanism is that it is a light-weight approach which is totally distributed, based on topology updates inherent in the Optimized Link State Routing (OLSR) protocol and, hence, it is unnecessary to introduce additional messages. Additionally, an algorithm was developed to resolve problems involving asymmetric links that arise in ad hocnetworks by eliminating unnecessary energy consumption of Fiedler nodes. Simulation results using NS3 show that the proposed mechanism successfully decreases the average amount of hops used by 50% and – he delay of flows when nodes are migrating at a modest rate below 60 m/min.