Many biological systems are composed of unreliable components which self-organize effectively into systems that achieve a balance between efficiency and robustness. One such example is the true slime mold Physarum polycephalum which is an amoeba-like organism that seeks and connects food sources and efficiently distributes nutrients throughout its cell body. The distribution of nutrients is accomplished by a self-assembled resource distribution network of small tubes with varying diameter which can evolve with changing environmental conditions without any global control. In this paper, we exploit two different mechanisms of the slime mold's tubular network formation process via laboratory experiments and mathematical behavior modeling to design two corresponding localized routing protocols for wireless sensor networks (WSNs) that take both efficiency and robustness into account. In the first mechanism of path growth, slime mold explores its immediate surroundings to discover and connect new food sources during its growth cycle. We adapt this mechanism for a path growth routing protocol by treating data sources and sinks as singular potentials to establish routes from the sinks to all the data sources. The second mechanism of path evolution is the temporal evolution of existing tubes through nonlinear feedback in order to distribute nutrients efficiently throughout the organism. Specifically, the diameters of tubes carrying large fluxes of nutrients grow to expand their capacities, and tubes that are not used decline and disappear entirely. We adapt the tube dynamics of the slime mold for a path evolution routing protocol. In our protocol, we identify one key adaptation parameter to adjust the tradeoff between efficiency and robustness of network routes. Through extensive realistic network simulations and ideal closed form or numerical computations, we validate the effectiveness of both protocols, as well as the efficiency and robustness of the resulting network connectivity.

Many biological systems are composed of unreliable components which self-organize efficiently into systems that can tackle complex problems. One such example is the true slime mold Physarum polycephalum which is an amoeba-like organism that seeks food sources and efficiently distributes nutrients throughout its cell body. The distribution of nutrients is accomplished by a self-assembled resource distribution network of small tubes with varying diameter which can evolve with changing environmental conditions without any global control. In this paper, we use a phenomenological model for the tube evolution in slime mold and map it to a path formation protocol for wireless sensor networks. By selecting certain evolution parameters in the protocol, the network may evolve toward single paths connecting data sources to a data sink. In other parameter regimes, the protocol may evolve toward multiple redundant paths. We present detailed analysis of a small model network. A thorough understanding of the simple network leads to design insights into appropriate parameter selection. We also validate the design via simulation of large-scale realistic wireless sensor networks using the QualNet network simulator.

Many biological systems are composed of unreliable and noisy components self-organizing efficiently into systems that can solve complex problems. One such example is the true slime mold {\em Physarum polycephalum} which is an amoeba-like organism that seeks food sources and efficiently distributes nutrients throughout the cell body.The cell body can grow to be centimeters in size.The distribution of nutrients is accomplished by a self-assembled resource distribution network of small tubes of varying diameter which can evolve with changing environmental conditions without any global control.In this paper, we use a phenomenological model for tube evolution in slime mold and map it to a path formation protocol for wireless sensor networks. By selecting certain evolution parameters in the protocol, the network will evolve toward single paths connecting data sources to a data sink.In other parameter regimes, the protocol will evolve toward multiple redundant paths. We present detailed analysis of a small model network.A thorough understanding of a simple network leads to design insights into appropriate parameter selection, and also validates the design via large-scale simulation of realistic wireless sensor networks using the QualNet network simulator.

The phenomenon of self-organization is pervasive in nature,where biological organisms efficiently self-organize unreliable and dynamically changing components to develop a wide diversity of functions. In addition, these biological organisms enjoy the desirable properties of robustness to the failure of individual components, adaptivity to changing conditions, and the lack of reliance on explicit central coordination. In this work, we seek inspiration from the study of the tubular network formation behavior of slime mold to design a localized protocol to connect sensors to sink(s) that balances efficiency and robustness in wireless sensor networks (WSN). Extensive simulations have been conducted to validate the effectiveness of the protocol, as well as the efficiency and robustness of the resulting network connectivity.