Kahn Process Networks and a Reactive Extension

Kahn and MacQueen have introduced a generic class of determinate asynchronous data-flow applications, called Kahn Process Networks (KPNs) with an elegant mathematical model and semantics in terms of Scott-continuous functions on data streams together with an implementation model of independent asynchronous sequential programs communicating through FIFO buffers with blocking read and non-blocking write operations. The two are related by the Kahn Principle which states that a realization according to the implementation model behaves as predicted by the mathematical function. Additional steps are required to arrive at an actual implementation of a KPN to take care of scheduling of independent processes on a single processor and to manage communication buffers. Because of the expressiveness of the KPN model, buffer sizes and schedules cannot be determined at design time in general and require dynamic run-time system support. Constraints are discussed that need to be placed on such system support so as to maintain the Kahn Principle.We then discuss a possible extension of the KPN model to include the possibility for sporadic, reactive behavior which is not possible in the standard model. The extended model is called Reactive Process Networks. We introduce its semantics, look at analyzability and at more constrained data-flow models combined with reactive behavior

DKPN: A Composite Dataflow/Kahn Process Networks Execution Model

International audienceTo address the high level of dynamism and variability in modern streaming applications (e.g. video decoding) as well as the difficulties in programming heterogeneous MPSoCs, we propose a novel execution model based upon both dataflow and Kahn process networks. This paper presents the semantics and properties of this hierarchical and parametric model, called DKPN. Parameters are classified and it is shown that hints can be derived to improve the execution. A scheduler framework and policies to back the model are also exposed. Experiments illustrate the benefits of our approach

Implementing deadlock detection in distributed processing, 1985

Many protocols have been published on the topic of deadlock detection in distributed processing. A survey has been made on four of these varied schemes. The method of 'distributed locking and distributed deadlock detection protocol' has been selected for implementation. Data structures and various routines for this particular protocol have been fully developed, and the resulting program exhaustively tested. In all test cases, results were positive and based on these results, we believe we have succeeded in implementing a deadlock detecting scheme for distributed processing

An evolutionary behavioral model for decision making

For autonomous agents the problem of deciding what to do next becomes increasingly complex when acting in unpredictable and dynamic environments pursuing multiple and possibly conflicting goals. One of the most relevant behavior-based model that tries to deal with this problem is the one proposed by Maes, the Bbehavior Network model. This model proposes a set of behaviors as purposive perception-action units which are linked in a nonhierarchical network, and whose behavior selection process is orchestrated by spreading activation dynamics. In spite of being an adaptive model (in the sense of self-regulating its own behavior selection process), and despite the fact that several extensions have been proposed in order to improve the original model adaptability, there is not a robust model yet that can self-modify adaptively both the topological structure and the functional purpose\ud of the network as a result of the interaction between the agent and its environment. Thus, this work proffers an innovative hybrid model driven by gene expression programming, which makes two main contributions: (1) given an initial set of meaningless and unconnected units, the evolutionary mechanism is able to build well-defined and robust behavior networks which are adapted and specialized to concrete internal agent's needs and goals; and (2)\ud the same evolutionary mechanism is able to assemble quite\ud complex structures such as deliberative plans (which operate in the long-term) and problem-solving strategies

Generalising feature interactions in email

We report on a property-based approach to feature interaction analysis for a client-server email system. The model is based upon Hall's email model presented at FIW'00, but the implementation is at a lower level of abstraction, employing non-determinism and asynchronous communication; it is a challenge to avoid deadlock and race conditions. The analysis is more extensive in two ways: interaction analysis is fully automated, based on model-checking the entire state-space, and results are scalable, that is they generalise to email systems consisting of any number of email clients. Abstraction techniques are used to prove general results. The key idea is to model-check a system consisting of a constant number (m) of client processes, in parallel with a mailer process and an ``abstract'' process which represents the product of any number of other (unfeatured, isomorphic) client processes. We give a lower bound for the value of m. All of the models -- for any specified set of client processes and selected features -- are generated automatically using Perl scripts

Submicron Systems Architecture: Semiannual Technical Report

No abstract available