Memristor-based information gathering approaches, both ant-inspired and hypothetical

Novel gatherer allocation methods based on both memristor function and ant behaviour are tested in both resource rich and poor environments by simulating the non-linear aspects of gathering using memristor models. In the All Sites method gatherers are allocated according to the voltage drop across the memristor simulating each food site. This performs better in environments of a similar quality by depleting the worse sites first and then using the freed-up gatherers to make up for declining productivity elsewhere. The Leafcutter allocation method, based on ant behaviour, first depletes the best resource and then allocates gatherers as for All Sites. This method functions best in environments with a wide distribution in site quality. These models suggest approaches for dealing with data transfer between nanomachines while also demonstrating useful behaviour of memristor-based nanonetwork-on-chips. An example of information transfer under these gathering approaches is given and shows the clear superiority of the Leafcutter approach once the system contains more than small numbers of memristors. Taking the Leafcutter approach to the extreme whereby each site is depleted in turn, the Sequential allocation method, is the worst performer in all tests.