Pattern of Diffusion Recognition in a Molecular Communication Model A nanomachine is the basic functional unit in nanotechnology that can perform simple tasks, like sensing and actuation. A set of nanomachines can perform more complex tasks through communicating and sharing information, and by that, they form a nanonetwork. Different communication techniques are proposed for information exchange among nanomachines. Molecular communication is one of these techniques, which is a bioinspired communication mechanism. In this paper a time slotted model consist of n nanomachines in a bounded environment is considered. These nanomachines are communicate according to diffusion based molecular communication. Information molecules are encoded based on the variation in the concentration of molecules in the communication medium. Thus, the receiver nanomachine decode the sensed information molecules during a certain time slot as xe2x80x981xe2x80x99, if its concentration exceeds a certain threshold xcfx84, and xe2x80x980xe2x80x99 otherwise. The main objective is to study the performance of diffusion based molecular communication model, the pattern of diffusion was explored, by inspecting how a receiver nanomachine could distinguish a message from one transmitter nanomachine at a distance d or two transmitter nanomachines at different distances. The information molecules were represented as 2bits by using 22 different values with 22 xe2x88x92 1 thresholds. In the implemented experiments the effects of distance, time, sensed molecular concentration and interference are considered.

A Generalized Cellular Automata Approach to Modelling Contagion and Monitoring for Emergent Events in Sensor Networks In order to improve the invulnerability and adaptability in sensor networks, we propose a cellular automata (CA) based propagation control mechanism (CACM) to inhibit and monitor emergentevent contagion. The cellular evolving rules of CACM are figured in multidimension convolution operations and cell state transform, which can be utilized to model the complex behavior of sensor nodes by separating the intrinsic and extrinsic states for each network cell. Furthermore, inspired by burning pain for Wireworld based monitoring model, network entropy theory is introduced into layered states on CACM to construct particlebased information communication process by efficient distribution of eventrelated messages on network routers, thus an invulnerable and energyefficient diffusion and monitoring being achieved. Experiment results prove that CACM can outperform traditional propagation models in adaptive invulnerability and selfrecovery scalability on sensor networks for propagation control on malicious events.