Towards reconfiguration and self-adaptivity in S-Net

Stream processing is a well-suited model for parallel programming, as it allows the programmer to design parallel algorithms intuitively by arranging computational tasks into a data-flow graph and consecutively constructing a streaming network from it. However, a network that was designed with a specific workload in mind will not work optimally if anticipated parameters, as for example data rates or computational costs per data item, change over time. To nonetheless achieve optimal performance, a restructuring of the network and re-implementation of computational components is inevitable.
As the deployment of a revised network usually causes service disruption, we present a system that supports reconfiguration of streaming networks at runtime. The reconfiguration of networks can either be triggered externally, i.e. initiated by the user, or from within the network itself (self-adaptation) by, for example, monitoring certain runtime parameters.
Our system is based on S-Net, a coordination language for asynchronous stream processing systems. S-Net supports the simultaneous use of computational components implemented in a range of programming languages and it offers network combinators to construct streaming networks from these components. We will introduce S-Net and extensions of the language that allow for reconfiguration and self-adaptation of networks at runtime. The extensions are designed as network combinators and integrate seamlessly into the existing language.