Computing In Cause Effect Structures
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Computing in Cause-Effect Structures
This book focuses on numerous examples of tasks represented by c-e structure. Cause–effect (c-e) structures are dynamic objects devised for algebraic and graphic description of realistic tasks. They constitute a formal system providing means to specify or implement (depending on degree of description generality) the tasks. They can be transformed, thus come under simplification, in accordance with rules-axioms of their algebra. Also, their properties can be inferred from the axioms. One objective of this book is presentation, by many realistic examples, of computing capability of c-e structures, without entering into mathematical details of their algebra. In particular, how computing with natural numbers and in propositional calculus can be performed by c-e structures and how to specify behavior of data structures. But also demonstration of many other tasks taken from the area of parallel processing, specified as c-e structures. Another objective is modelling or simulation by means of c-e structures, of other descriptive systems, devised for tasks from various fields. Also without formalizing by usage of functions between the systems. This concerns formalisms such as reaction systems, rough sets, Petri nets and CSP-like languages. Also on such, where temporal interdependence between actions matters. The presentation of examples is prevalently graphic, in the form of peculiar nets, but accompanied by their algebraic and set-theoretic expressions. A fairly complete exposition of concepts and properties of the algebra of cause-effect structures is in the previous book appeared in the Lecture Notes in Networks and Systems series. But basic notions of c-e structures are here provided for understanding the examples.
Cellular Cause-Effect Structures
This book presents the adaptation of cause-effect structures to the formal description of phenomena such as the behaviour of living objects, the mutual communication of living cells, but also such as the growth of crystals and other natural processes. The system of cause-effect structures has been designed for the description and analysis of objects with dispersed components, acting concurrently and synchronizing and communicating one another. This adaptation consists in customizing generic semantics of cause-effect structures to semantics specific to the behaviour of natural objects. That is creating evolution rules for the formal models of these objects. However, the structural, algebraic properties of cause-effect structures are retained. The activity of cellular cause-effect structures is supposed to imitate the activity of cellular automata, the formal system intended for the above-mentioned aims. But operations on syntactic constructions, in particular their transformations and simplification, are the same as for the general cause-effect structures. These algebraic operations are also used to perform certain geometric/topological conversions of location bases for the cellular cause-effect structures, like flat surfaces into cylindrical or toroidal. This is depicted by numerous illustrations. An adaptation of cause-effect structures to other formal descriptions of some natural phenomena, such as reaction systems, is provided in book 331 of the “Lecture Notes in Networks and Systems” series, whereas the complete description of cause-effect structures, in book 45.
Introduction to Distributed Computer Systems
This book introduces readers to selected issues in distributed systems, and primarily focuses on principles, not on technical details. Though the systems discussed are based on existing (von Neumann) computer architectures, the book also touches on emerging processing paradigms. Uniquely, it approaches system components not only as static constructs, but also “in action,” exploring the different states they pass through. The author’s teaching experience shows that newcomers to the field, students and even IT professionals can far more readily grasp the essence of distributed algorithmic structures in action, than on the basis of static descriptions.