Developing Autonomic Properties for Distributed Pattern-Recognition Systems with ASSL: A Distributed MARF Case Study

TL;DR

This paper presents a formal approach using ASSL to develop autonomic properties in DMARF, a distributed pattern recognition system, enabling autonomous operation with minimal human intervention.

Contribution

It introduces a formal specification of autonomic properties for DMARF using ASSL, enhancing its autonomous capabilities for scientific and robotic applications.

Findings

Formal ASSL models for autonomic DMARF properties

Enhanced autonomous behavior in pattern recognition pipeline

Potential for reduced human intervention in applications

Abstract

In this paper, we discuss our research towards developing special properties that introduce autonomic behavior in pattern-recognition systems. In our approach we use ASSL (Autonomic System Specification Language) to formally develop such properties for DMARF (Distributed Modular Audio Recognition Framework). These properties enhance DMARF with an autonomic middleware that manages the four stages of the framework's pattern-recognition pipeline. DMARF is a biologically inspired system employing pattern recognition, signal processing, and natural language processing helping us process audio, textual, or imagery data needed by a variety of scientific applications, e.g., biometric applications. In that context, the notion go autonomic DMARF (ADMARF) can be employed by autonomous and robotic systems that theoretically require less-to-none human intervention other than data collection for pattern analysis and observing the results. In this article, we explain the ASSL specification models for the autonomic properties of DMARF.