Marc Chiarini

Dynamics of Resource Closure Operators

We propose a framework for managing resources via convergent operators. Operators represent their need for a resource to a designated resource closure operator that manages the resource. We evaluate a specific design for a resource closure operator by simulation and demonstrate that the operator achieves a near-optimal balance between cost and value without using any model of the relationship between resources and behavior. Instead, the resource operator relies upon its control of the resource to perform experiments and react to their results. These experiments allow the operator to be highly adaptive to change and unexpected contingencies.

A Theory of Closure Operators

We explore how fixed-point operators can be designed to interact and be composed to form autonomic control mechanisms. We depart from the idea that an operator is idempotent only for the states that it assures, and define a more general concept in which acceptable states are a superset of assurable states. This modified definition permits operators to make arbitrary choices that are later changed by other operators, easing their composition and allowing them to maintain aspects of a configuration. The result is that operators can be used to implement closures, which can in turn be used to build self-managing systems.

Dynamic Consistency Analysis for Convergent Operators

It has been shown that sets of convergent operators with a shared fixed point can simulate autonomic control mechanisms, but many questions remain about this management technique. We discuss how an autonomous agent can reason about whether its convergent operators share a fixed point with the operators of other agents. Using a concept of time based upon operator repetition, we show that a failure to achieve convergence within specific time limits can be used as a probabilistic indicator of inconsistencies in local policy. We describe a statistical inference technique that determines if an agents promise strategy is feasible. The strengths of this technique are that it is both scale-invariant and exterior to the operators whose consistency is being evaluated.

Modeling Change Without Breaking Promises

Promise theory defines a method by which static service bindings are made in a network, but little work has been done on handling the dynamic case in which bindings must change over time due to both contingencies and changes in policy. We define two new kinds of promises that provide temporal scope for a conditional promise. We show that simple temporally-scoped promises can describe common network behaviors such as leasing and failover, and allow an agent to completely control the sequence of sets of promises to which it commits with another agent, over time. This allows agents to adapt to changing conditions by making short-term bilateral agreements rather than the long-term unilateral agreements provided by previous promise constructions.

Estimating Reliability of Conditional Promises

Using conditional promises, the reliability of promises can be measured without reference to the reliability of the issuing agent, by defining notions of when conditions operate and when promises are expected to be fulfilled. This inspires an analytical method that attributes promise failures to incomplete knowledge rather than agent unreliability. This analysis allows agents to choose between conditional offers of service based upon statistical measures of the completeness of stated conditions.