Design of divergence-free protocol converters using supervisory control techniques

Hallal, Hicham; Negulescu, R.; Petrenko, Alexandre

doi:10.1109/icecs.2000.912975

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…An important application from discrete control theory is the model matching problem: design a controller whose composition with a plant matches a given specification (see [2,16]). Another significant application of the quotient computation has been the protocol design problem, and in particular, the protocol conversion problem (see [27,18,35,33,25,20,41,11]). Protocol converter synthesis has been studied also over a variant of Input/Output Automata (IOA, [29]), called Interface Automata (IA, [15,14]), yielding a similar quotient equation A ⋄ IA x ⊆ B and closed-form solution A ⋄ IA B ⊥ ⊥ , where ⋄ IA is an appropriate interleaving composition defined for interface automata, and (•) ⊥ is again a unary operation [6].…”

Section: Introductionmentioning

confidence: 99%

The Quotient in Preorder Theories

Romeo

Mangeruca

Villa

et al. 2020

Electron. Proc. Theor. Comput. Sci.

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Seeking the largest solution to an expression of the form Ax ≤ B is a common task in several domains of engineering and computer science. This largest solution is commonly called quotient. Across domains, the meanings of the binary operation and the preorder are quite different, yet the syntax for computing the largest solution is remarkably similar. This paper is about finding a common framework to reason about quotients. We only assume we operate on a preorder endowed with an abstract monotonic multiplication and an involution. We provide a condition, called admissibility, which guarantees the existence of the quotient, and which yields its closed form. We call preordered heaps those structures satisfying the admissibility condition. We show that many existing theories in computer science are preordered heaps, and we are thus able to derive a quotient for them, subsuming existing solutions when available in the literature. We introduce the concept of sieved heaps to deal with structures which are given over multiple domains of definition. We show that sieved heaps also have well-defined quotients.

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Section: Introductionmentioning

confidence: 99%

The Quotient in Preorder Theories

Romeo

Mangeruca

Villa

et al. 2020

Electron. Proc. Theor. Comput. Sci.

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“…and those of the channel and the user services. The problem was addressed in [5,2] with supervisory control techniques. We were able to derive the largest solution, and the largest compositionally progressive solution, which were not previously reported in the literature.…”

Section: Discussionmentioning

confidence: 99%

Solution of parallel language equations for logic synthesis

Yevtushenko¹,

Villa²,

Brayton³

et al.

IEEE/ACM International Conference on Computer Aided Design. ICCAD 2001. IEEE/ACM Digest of Technical Papers (Cat. No.01CH37281)

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The problem of designing a component that combined with a known part of a system, conforms to a given overall specification arises in several applications ranging from logic synthesis to the design of discrete controllers. We cast the problem as solving abstract equations over languages. Language equations can be defined with respect to several language composition operators such as synchronous composition, ¤, and parallel composition, ¥; conformity can be checked by language containment. In this paper we address parallel language equations.Parallel composition arises in the context of modeling delayinsensitive processes and their environments. The parallel composition operator models an exchange protocol by which an input is followed by an output after a finite exchange of internal signals. It abstracts a system with two components with a single message in transit, such that at each instance either the components exchange messages or one of them communicates with its environment, which submits the next external input to the system only after the system has produced an external output in response to the previous input.We study the most general solutions of the language equation ¦ § ¥ ©, and define the language operators needed to express them. Then we specialize such equations to languages associated with important classes of automata used for modeling systems, e.g., regular languages and FSM languages. In particular, for ¦ ¥ , we give algorithms for computing: the largest FSM language solution, the largest complete solution, and the largest solution whose composition with ¦ yields a complete FSM language. We solve also FSM equations under bounded parallel composition.In this paper, we give concrete algorithms for computing such solutions, and state and prove their correctness.

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