Model-based Design of Self-adapting Networked Signal Processing Systems

The paper describes a model based approach for architecture design of runtime reconfigurable, large-scale, networked signal processing applications. A graph based modeling formalism is introduced to describe all relevant aspects of the design (functional, concurrency, hardware, communication, energy, etc.). The formalism can be used to evaluate and suggest architectural patterns for signal processing type of applications. Moreover, an architecture design evaluation tool according to the modeling formalism is described, which can place the system design under various execution scenarios (e.g. node mobility, node failure, communication link deterioration, etc.) and determine emerging system properties (such as expected lifetime, availability of services, throughput, response times, etc.). Distinguishing feature of the tool is that it allows for modeling runtime reconfiguration solutions (e.g. distributed optimization, constraint solvers) and making changes in the underlying system architecture and thus evaluate the effects of the reconfiguration. The evaluation tool can be embedded into a design optimizer, which allows an optimal trade-off between design-time and runtime configuration to be determined. The effectiveness of the approach and the tool is demonstrated via two application cases (structural integrity monitoring, greenhouse temperature distribution estimation).