Accession Number:

ADA582906

Title:

An Advanced Computational Approach to System of Systems Analysis & Architecting Using Agent-Based Behavioral Model

Descriptive Note:

Final technical rept.

Corporate Author:

SYSTEMS ENGINEERING RESEARCH CENTER HOBOKEN NJ

Personal Author(s):

Report Date:

2012-09-30

Pagination or Media Count:

51.0

Abstract:

A major challenge to the successful planning and evolution of an acknowledged System of Systems SoS is the current lack of understanding of the impact that the presence or absence of a set of constituent systems has on the overall SoS capability. Since the candidate elements of an SoS are fully functioning, stand-alone Systems in their own right, they have goals and objectives of their own to satisfy, some of which may compete with those of the overarching SoS. These system-level concerns drive decisions to participate or not in the SoS. Individual systems typically must be requested to join the SoS construct, and persuaded to interface and cooperate with other Systems to create the new capability of the proposed SoS. Current SoS evolution strategies lack a means for modeling the impact of decisions concerning participation. The goal of this research is to model the evolution of the architecture of an acknowledged SoS that accounts for the ability and willingness of constituent systems to support the SoS capability development. Since DoD Systems of Systems SoS development efforts do not typically follow the normal program acquisition process described in DoDI 5000.02, the Wave Model proposed by Dahmann and Rebovich is used as the basis for this research on SoS capability evolution. The Wave Process Model provides a framework for an agent-based modeling methodology, which is used to abstract the non-utopian behavioral aspects of the constituent systems and their interactions with the SoS. In particular, the research focuses on the impact of individual system behavior on the SoS capability and architecture evolution processes. A proof of concept agent-based model ABM of the system interactions is developed and integrated with a genetic algorithm GA to explore the potential architectural design space, using a fuzzy associative memory FAM to evaluate candidate architectures for simulating SoS creation and evolution.

Subject Categories:

  • Administration and Management
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE