Models of High-Level Computation

Classical models of computation have been successful in capturing the very essence of individual computing devices. Although they are useful to understand computability power and limitations in the small, such models are not suitable to study large-scale complex computations. Accordingly, plenty of formalisms have been proposed in the last half century as an attempt to raise the level of abstraction, with the aim of describing not only a single computing device but interactions among a collection of them. In this paper, we encompass such formalisms into a common framework which we refer to as Models of High-Level Computation. We particularly discuss the semantics, some of the key properties, paradigms and future directions of such models

Are there new models of computation? Reply to Wegner and Eberbach

Wegner and Eberbach[Weg04b] have argued that there are fundamental limitations to Turing Machines as a foundation of computability and that these can be overcome by so-called superTuring models such as interaction machines, the [pi]calculus and the $-calculus. In this paper we contest Weger and Eberbach claims

A Formal Framework for Interactive Agents

AbstractThis paper proposes a formal framework and architecture for specification and analysis of interactive agents. The framework can be used to explore the design space, study features of different points in the design space, and to develop executable specifications of specific agents and study their interactions with the environment. A long term goal is development of reasoning principles specialized to different regions of the design space

Modeling and Simulation of Spark Streaming

As more and more devices connect to Internet of Things, unbounded streams of data will be generated, which have to be processed "on the fly" in order to trigger automated actions and deliver real-time services. Spark Streaming is a popular realtime stream processing framework. To make efficient use of Spark Streaming and achieve stable stream processing, it requires a careful interplay between different parameter configurations. Mistakes may lead to significant resource overprovisioning and bad performance. To alleviate such issues, this paper develops an executable and configurable model named SSP (stands for Spark Streaming Processing) to model and simulate Spark Streaming. SSP is written in ABS, which is a formal, executable, and object-oriented language for modeling distributed systems by means of concurrent object groups. SSP allows users to rapidly evaluate and compare different parameter configurations without deploying their applications on a cluster/cloud. The simulation results show that SSP is able to mimic Spark Streaming in different scenarios.Comment: 7 pages and 13 figures. This paper is published in IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA 2018

On the evolution of conceptual modeling

Since the 1980s the need increased for overcoming idiosyncrasies of approaches to modeling in the various sub-disciplines of computing. The theoretical model of evolution is used in this paper for analyzing how computing and conceptual modeling have changed. It is concluded that computing has changed into a social phenomenon with a technical core and that therefore relying on (formal) model semantics as the sole tool for the discussion of conceptual modeling is no more adequate. A number of language games of computing is identified and the task set to describe these language games to the extent necessary for deciding whether or not they can serve as the foundation of computing

Reactive Turing Machines

We propose reactive Turing machines (RTMs), extending classical Turing machines with a process-theoretical notion of interaction, and use it to define a notion of executable transition system. We show that every computable transition system with a bounded branching degree is simulated modulo divergence-preserving branching bisimilarity by an RTM, and that every effective transition system is simulated modulo the variant of branching bisimilarity that does not require divergence preservation. We conclude from these results that the parallel composition of (communicating) RTMs can be simulated by a single RTM. We prove that there exist universal RTMs modulo branching bisimilarity, but these essentially employ divergence to be able to simulate an RTM of arbitrary branching degree. We also prove that modulo divergence-preserving branching bisimilarity there are RTMs that are universal up to their own branching degree. Finally, we establish a correspondence between executability and finite definability in a simple process calculus

Interactive Small-Step Algorithms I: Axiomatization

In earlier work, the Abstract State Machine Thesis -- that arbitrary algorithms are behaviorally equivalent to abstract state machines -- was established for several classes of algorithms, including ordinary, interactive, small-step algorithms. This was accomplished on the basis of axiomatizations of these classes of algorithms. Here we extend the axiomatization and, in a companion paper, the proof, to cover interactive small-step algorithms that are not necessarily ordinary. This means that the algorithms (1) can complete a step without necessarily waiting for replies to all queries from that step and (2) can use not only the environment's replies but also the order in which the replies were received