Abstract.A scheduler is an algorithm that assigns at any time a set of processes to a set of processors. Processes usually interact with each other, which introduces dependencies amongst them. Typically, such dependencies induce extra delays that the scheduler needs to avoid. Specific types of applications, like streaming applications, synthesize a scheduler from a formal model that is aware of these interactions. However, such interaction-specific information is not available for general types of applications. In this paper, we propose an interaction aware scheduling framework for generic concurrent applications. We formalize the amount of work performed by an application as constraints. We use these constraints to generate a graph, and view scheduler synthesis as solving a game on this graph that is played between the scheduler and the application. We illustrate that our framework is expressive enough to subsume an established scheduling framework for streaming programs.

Coordination languages simplify design and development of concurrent systems. Particularly, exogenous coordination languages, like BIP and Reo, enable system designers to express the interactions among components in a system explicitly. In this paper we establish a formal relation between BI(P) (i.e., BIP without the priority layer) and Reo, by defining transformations between their semantic models. We show that these transformations preserve all properties expressible in a common semantics. This formal relation comprises the basis for a solid comparison and consolidation of the fundamental coordination concepts behind these two languages. Moreover, this basis offers translations that enable users of either language to benefit from the toolchains of the other.

Constraint automata specify protocols as labeled transition systems that preserve synchronization under composition. They have been used as a basis for tools, such as compilers and model checkers. Unfortunately, composition of transition systems suffers from state space and transition space explosions, which limits scalability of the tools based on constraint automata. In this work, we propose stream constraints as an alternative to constraint automata that avoids state space explosions. We introduce a rule-based form for stream constraints that can avoid transition space explosions. We provide sufficient conditions under which our approach avoids transition space explosions.

Abstract.A concurrent application consists of a set of concurrently executing interacting processes. Although earlier we proposed work automata to specify both computation and interaction of such a set of executing processes, a detailed formal semantics for them was left implicit. In this paper, we provide a formal semantics for work automata, based on which we introduce equivalences such as weak simulation and weak language inclusion. Subsequently, we define operations on work automata that simplify them while preserving these equivalences. Where applicable, these operations simplify a work automaton by merging its different states into a state with a 'more inclusive' state-invariant. The resulting state-invariant defines a region in a multidimensional real vector space that potentially contains holes, which in turn expose mutual exclusion among processes. Such exposed dependencies provide additional insight in the behavior of an application, which can enhance scheduling. Our operations, therefore, potentially expose implicit dependencies among processes that otherwise may not be evident to exploit.

Coordination languages simplify design and development of concurrent systems. Particularly, exogenous coordination languages, like BIP and Reo, enable system designers to express the interactions among components in a system explicitly. A formal relation between exogenous coordination languages comprises the basis for a solid comparison and consolidation of their fundamental concepts. In this paper we establish a formal relation between BI(P) (i.e., BIP without the priority layer) and Reo, by defining transformations between their semantic models. We show that these transformations preserve all properties expressible in a common semantics. We use these transformations to define data-sensitive BIP architectures and their composition.