Stable Metrics in Amorphous Computing: An Application to Validate Operation and Monitor Behavior

A recurring theme in intelligent environments is the intelligent surface composed of nanoscale processing units (smart dust). Such a surface (iSurface) can be considered an amorphous computer composed of a large array of identical processing units (iCells) each with its own sensor/effectors. Whilst nano-sized particles interconnecting in an ad hoc way may just be a dream, there are more practical approaches that could have short term applications in intelligent environments. One such approach is a structured array of iCells constructed at more modest scales perhaps making use of new printing methods onto paper. An important requirement of such a surface is the need for a fast, reliable method to determine iCell operation, performance and code integrity. This paper describes a method to create long (>=32 bit) stable, robust metrics using a profiling technique that represents the current operational state of an iCell and thus enabling the quick exchange of diagnostics between iCells along with data traffic. This paper looks at how stable diagnostic metrics and in particular a metric of code integrity can be created even when external events affect program flow within the iCell. Key requirements in the development of this system were fast acquisition of diagnostic variables, minimal affect on normal operation and the possibility of a hardware implementation which could be completely non intrusive in operation. The described method can create several types of metrics, allowing quick determination of for example, code validation, abnormal operation and unusual behavior.