A policy-definition language and prototype implementation library for policy-based autonomic systems

This paper presents work towards generic policy toolkit support for autonomic computing systems in which the policies themselves can be adapted dynamically and automatically. The work is motivated by three needs: the need for longer-term policy-based adaptation where the policy itself is dynamically adapted to continually maintain or improve its effectiveness despite changing environmental conditions; the need to enable non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk; and the need for adaptive policy mechanisms that are easy to deploy into legacy code. A policy definition language is presented; designed to permit powerful expression of self-managing behaviours. The language is very flexible through the use of simple yet expressive syntax and semantics, and facilitates a very diverse policy behaviour space through both hierarchical and recursive uses of language elements. A prototype library implementation of the policy support mechanisms is described. The library reads and writes policies in well-formed XML script. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and meta-policies to dynamically select between policy instances and templates. Most significantly, the scheme supports hot-swapping between policy instances. To illustrate the feasibility and generalised applicability of these tools, two dissimilar example deployment scenarios are examined. The first is taken from an exploratory implementation of self-managing parallel processing, and is used to demonstrate the simple and efficient use of the tools. The second example demonstrates more-advanced functionality, in the context of an envisioned multi-policy stock trading scheme which is sensitive to environmental volatility

The AGILE policy expression language for autonomic systems

This paper presents the AGILE policy expression language. The language enables powerful expression of self-managing behaviours and facilitates policy-based autonomic computing in which the policies themselves can be adapted dynamically and automatically. The language is generic so as to be deployable across a wide spectrum of application domains, and is very flexible through the use of simple yet expressive syntax and semantics. The development of AGILE is motivated by the need for adaptive policy mechanisms that are easy to deploy into legacy code and can be used by non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk. A library implementation of the policy language is described. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and higher-level ‘meta-policies’ to dynamically select between differently configured business-logic policy instances and templates. Two dissimilar example deployment scenarios are examined.

A sensitive bioassay for the mycotoxin aflatoxin B1, which also responds to the mycotoxins aflatoxin G1 and T-2 toxin, using engineered baker's yeast

A novel aflatoxin B(1) bioassay was created by introducing a Lipomyces kononenkoae alpha-amylase gene into a strain of S. cerevisiae capable of expressing the human cytochrome P450 3A4 (CYP3A4), and the cognate human CYP450 reductase. This strain and a dextranase-expressing strain were used in the development of a microtitre plate mycotoxin bioassay, which employed methanol as the solvent and polymyxin B nonapeptide as a permeation enhancer. Stable co-expression of the CYP3A4 gene system and of the dextranase and amylase genes in the two bioassay strains was demonstrated. The bioassay signalled toxicity as inhibition of secreted carbohydrase activity, using sensitive fluorimetric assays. The amylase-expressing strain could detect aflatoxin B(1) at 2 ng/ml, and was more sensitive than the dextranase-expressing strain. Aflatoxin G(1) could be detected at 2 microg/ml, and the trichothecene mycotoxin T-2 toxin was detectable at 100 ng/ml.