Using novel distributed heuristics on hexagonal connected dominating sets to model routing dissemination

Network-centric Future Force must support a large and diverse group of communication nodes. Despite the fact that there is ample scope for network design in networks such as Future Combat Systems (FCS) and Warfighter Information Network-Tactical (WIN-T), there are important performance limits when network conditions become more extreme (highly mobile or dense). In previous work, we modeled and analyzed the expected user performance of a number of novel approaches to flooding link state routing information in wireless ad hoc networks for routing update. We compared routing dissemination schemes such as this of Flat Flooding and Multi-Point Relays (MPRs), with our own variations on Connected Dominating Sets (CDSs), assuming other parts of the routing protocol were taken from standard Link State Routing protocol (OLSR) or Open Shortest Path First protocol (OSPF), widely used in the Internet and WIN-T. Although the existing literature provides a variety of models for Flat Flooding and MPRs, it lacks similar analytical work for relays placement under a CDS approach. Towards the latter, we selected one representative from our novel CDS-based models—the CDS Hexagon, as it provides the lowest routing overhead among other properties. Our analysis demonstrates the difference in the impact of conditions on key performance metrics, such as this of network density on routing overhead as well as a tradeoff between routing overhead and routing stretch. We then advance CDS-HEX dissemination from the limited-scope centralized scenarios with strictly symmetrical relay placement to dynamic scenarios with totally random relay placement. We use novel heuristics to adapt the analytical CDS-HEX to dynamic environments. We show that: (a) although the distributed scheme naturally operates sub-optimally compared to its centralized ancestor, it is still superior to MPRs over certain metrics of interest, (b) the set-up overhead of CDS-HEX is not significantly higher than this of MPRs, while at the same time, the steady state overhead of CDS-HEX appears adequately lower than this of MPR, and (c) all the closed analytical formulae and asymptotic results derived in our previous analysis are verified by our simulations which also provide additional insight on metrics that cannot be analytically measured. Our scheme on one hand is not overly expensive to set up despite the more complex generation process, and on the other hand has a superior performance for the majority of network conditions, and close to the optimal one anticipated by the corresponding centralized model.