Why Computer-Based Systems Should be Autonomic

The objective of this paper is to discuss why computer-based systems should be autonomic, where autonomicity implies self-managing, often conceptualized in terms of being self-configuring, self-healing, self-optimizing, self-protecting and self-aware. We look at motivations for autonomicity, examine how more and more systems are exhibiting autonomic behavior, and finally look at future directions

Autonomous and Autonomic Swarms

A watershed in systems engineering is represented by the advent of swarm-based systems that accomplish missions through cooperative action by a (large) group of autonomous individuals each having simple capabilities and no global knowledge of the group s objective. Such systems, with individuals capable of surviving in hostile environments, pose unprecedented challenges to system developers. Design and testing and verification at much higher levels will be required, together with the corresponding tools, to bring such systems to fruition. Concepts for possible future NASA space exploration missions include autonomous, autonomic swarms. Engineering swarm-based missions begins with understanding autonomy and autonomicity and how to design, test, and verify systems that have those properties and, simultaneously, the capability to accomplish prescribed mission goals. Formal methods-based technologies, both projected and in development, are described in terms of their potential utility to swarm-based system developers

Next generation system and software architectures Challenges from future NASA exploration missions

AbstractThe four key objective properties of a system that are required of it in order for it to qualify as “autonomic” are now well-accepted—self-configuring, self-healing, self-protecting, and self-optimizing—together with the attribute properties—viz. self-aware, environment-aware, self-monitoring and self-adjusting. This paper describes the need for next generation system software architectures, where components are agents, rather than objects masquerading as agents, and where support is provided for self-* properties (both existing self-chop and emerging self-* properties). These are discussed as exhibited in NASA missions, and in particular with reference to a NASA concept mission, ANTS, which is illustrative of future NASA exploration missions based on the technology of intelligent swarms

Towards Specifying Swarm-based Systems Using Categorical Modeling Language: A Case Study

One of the solutions to the software complexity crisis of this era is the proposition of self-managing systems like autonomous and autonomic systems. The idea has gained wide acceptance in the IT industry but it has also introduced the challenge of specification and development of such systems. Swarm intelligence is finding its applications in research and design of self-managing systems because of the coincidental resemblance between the two domains. However, specification of a swarm-based self-managing system is faced with the difficulty of specifying the complex evolving behavior. This thesis presents an adaptation of a mathematical technique known as Category Theory to serve as a ‘reasoning and modeling’ paradigm for specifying high-level behavioral patterns of a swarm-based self-managing systems. The crux of this paradigm is the formal categorical modeling language (CML). CML syntax and semantics have been defined using an EBNF-based context-free grammar. The language helps to generate a formal specification of different scenarios/behavioral patterns of a swarm-based system. Moreover, a prototype tool has been implemented as part of this research work to serve as a modeling tool based on CML. In this thesis, NASA’s ANTS-based Prospecting Asteroid Mission (PAM) serves as a case study to analyze the applicability and usability of CML as a formal method of choice