Multi-dimensional clustering and network monitoring system for aeronautical ad hoc networks

Network partition is an inevitable phenomena that prohibits existence of unified robust networks. Partition in static networks occur mainly due to uneven traffic. In mobile networks, a member of the network can be defined using n-dimensions. These dimensions account for the member profile and properties. A multi-dimensional profile can partition the network in multiple ways. Aeronautical ad hoc network (AANET) is a multi-dimensional network. It has a 3D topology spread across the airspace. The high ground speed of the airborne elements changes the network topology rapidly. In this paper, we present an `in-air´ network monitoring system for the dynamic AANET environment. The monitoring system deals with the problem of network partitions in AANET by observing the network in n-dimensions. The partitions in the network are identified using multi-dimensional clustering. Multi-dimensional clustering spots the directional behavior in the mobility plane and congestion in the data plane of the network. The dynamic partition detection mitigates the effect of network disruption and accounts for isolated members in the network. The system uses a mixed network design and a quasi-stationary network of higher altitude platforms for achieving ubiquitous network monitoring in the AANET.