Semantic Logging in a Distributed Multi-Agent System
Sorin Ilie, Mihnea Scafes ¸, Costin B˘ adic˘ a
University of Craiova, Software Engineering Dept.
Bvd.Decebal 107, Craiova, 200440, Romania
{sorin.ilie,mihnea.scafes,costin.badica}@software.ucv.ro
Thomas Neidhart, Rani Pinchuk
Space Applications Services NV
Leuvensesteenweg 325, 1932, Zaventem, Belgium
{thomas.neidhart,rani.pinchuk}@spaceapplications.com
Abstract
The paper presents a semantic logging framework which
allows structured information logging in an agent-based dis-
tributed system for chemical incident response. The logging
framework is “semantic” because it allows semantic inter-
pretation of logs according to relationships defined between
logging events. For example, this approach could help the
reconstruction of the order of events that occurred during
the response to an incident, thus giving a detailed view of
system execution trace, as well as of agents’ decisions taken
at various decision points during the incident management
workflow. We intend to use semantic logs (i) for helping
experts to analyze and explain system actions and thus
improving system response to future incidents, as well as (ii)
for training stakeholders by setting the system to run replay-
like simulations of past incident management workflows.
1. Introduction
The work reported in this paper was carried out in the
context of the development of an agent-based distributed
collaborative system intended to support and help coordi-
nation of human experts, population and specialized insti-
tutions that are collectively involved in response to disaster
situations – the DIADEM project
1
. More specifically, DIA-
DEM project targets potential disasters caused by chemical
incidents in industrial and urban areas. DIADEM is based on
Dynamic Process Integration Framework – DPIF [10] multi-
agent platform, which in turn is built on top of Cougaar
agent platform [1]. DPIF allows integration of software
components of the DIADEM system: gas monitoring and
distribution modeling; electronic emergency response guide;
multi criteria decision analysis; scenario based reasoning and
decision support workbench. Each component applies only
local knowledge to achieve its function. Agents in DIADEM
support humans that participate in the process of responding
to a chemical incident. During the incident response, agents
Sorin Ilie, Mihnea Scafes ¸, Costin B˘ adic˘ a, Thomas Neidhart, and Rani
Pinchuk were supported by DIADEM project. Diadem project is funded
by European Union under Information and Communication Technologies
(ICT) theme of the 7th Framework Programme for R&D, ref. no: 224318.
1. DIADEM project – Distributed information acquisition and decision-
making for environmental management: http://www.ist-diadem.eu/
connect together through service invocations and create a
complex incident management workflow [10], [13].
Usually, after an incident response, experts are interested
to analyze the complete system activity during the incident
to see how stakeholders handled the various situations that
occurred during the incident management process. In par-
ticular, they are interested in explaining, at least in some
situations, what where the causes of the incident. Therefore,
assuming that suitable log information was generated by
logging agents’ interactions and major decision points of
their reasoning processes, experts will be able to analyze
log information in order to reconstruct the workflow exe-
cution trace. Difficulties of performing this analysis are: (i)
log information is distributed throughout the system, and
collection and integration of this information is not trivial;
(ii) as DIADEM is a distributed system, the use of local time
recorded with the log events is not enough for workflow
reconstruction and additional causal and domain-dependent
“semantic” information must also be logged.
The contribution of this paper is represented by proposal
of semantic logging framework which allows structured
information logging in agent-based distributed systems for
management of the response to an incident. The logging
framework is “semantic” because it allows causal interpre-
tation of logs according to a caused-by relation between
logging events. This approach helps the reconstruction of the
order of events happened during the response to an incident,
thus giving a detailed view of system execution trace, as
well as of agents’ decisions taken at various decision points
during the incident management workflow. Semantic logs
captured during system execution are intended (i) to help
experts analyze and explain system actions through an after-
action analysis process and thus to improve system response
to future incidents, as well as (ii) to train experts by allowing
the system to run replay-like simulations of past incident
management workflows.
Relevant works addressing distributed logging are [4] and
[12]. [4] introduces a framework for distributed logging in
JADE multi-agent systems [9]. However, semantic aspects
of the logs are not considered. [12] considers only semantic
aspects of logging in distributed workflows that address
business and inter-organizational needs.
The rest of the paper is structured as follows. In Section
2 we define logging principles, such as when and what to
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