Using Autonomics to Exercise Command and Control of Networks in Degraded Environments

Abstract : Autonomic approaches enable large, complex systems to exhibit self-adaptation in response to attack or rapid degradation of the environment. This paper applies one such autonomics approach, the Rainbow autonomics framework, to Naval command and control systems. Rainbow employs an abstraction language that models a managed system, discovery probes that read data from the managed system, discovery gauges that interpret data from the probes, strategies that adapt the managed system to changes, and actuators that effect the desired strategic changes to the managed system. Because Rainbow represents managed systems as architectural abstractions, varied systems can be modeled, including such naval systems as the Command and Control Rapid Prototyping Continuum (C2RPC), simulated groups of operational forces that include autonomous vehicles, and navy data centers. All three can be described in the abstraction models of Rainbow and all can be managed by an autonomics framework. The focus of this paper is on the effects of Disconnected, Intermittent, and Limited (DIL) connectivity environments on the capability of autonomics to manage a system in such environments. The results show that DIL environments have a negative effect on centralized autonomics' capability, such as Rainbow, in managing target systems.