NUI Galway – UL Alliance First Annual ENGINEERING AND - ARAN ...

Multi-Level Enterprise Energy Management
Linked Data for Semantic Complex Event Processing
Souleiman Hasan, Edward Curry, Joao de Oliveira Alves, Sean O'Riain
The Digital Enterprise Research Institute (DERI), NUI Galway
{souleiman.hasan, ed.curry, joao.deoliveira, sean.oriain}@deri.org
Abstract
Energy consumption management has become a very
crucial topic for enterprises due to energy cost and
environmental impacts. Energy monitoring usually
takes place on a very low level in enterprises such as
sensors. However, different people in an enterprise
would be interested in different conceptual levels and
granularities of activities and thus energy monitoring in
its current state-of-the-art lacks the ability to bridge the
vertical information gap between hierarchical levels
(e.g. maintenance, operational, upper management) in
an enterprise. Our research is aimed at exploiting
semantic web technologies and complex event
processing technology to strengthen energy monitoring
task and associate energy aspects with activities and
business processes in different operational and
management levels of an enterprise. This will allow
organizations to understand accurately the
relationships between its activities and energy
consumption and thus being able to find possible
opportunities for energy saving or business process
development.
1. Introduction
Monitoring technology has evolved in a slower
manner than business information systems [1]. This
difference has created a gap between different layers of
an enterprise. For example, energy sensors data is very
low level and can be understood by maintenance
personnel but doesn’t make sense to upper management
which might be interested in a business objective such
as reducing energy consumption by 10% throughout the
next two years.
2. Complex Event Processing for Energy
Event-driven systems have attracted much interest
recently because of its nature of low-coupling and
asynchronous communication. This nature makes events
a good choice for real time monitoring in highly
dynamic systems.
CEP addresses the aforementioned information gap
with vertical causality between events and abstraction
hierarchies to reflect multi-layered enterprises [1].
3. Linked Data for CEP
Linked Data technology [2] provides an approach for
systems integration and interoperability. The selfcontained
semantics in Linked Data improves its
suitability for sharing and gives it a potential to be
reused with significantly lower cost.
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We suggest the use of Semantic Web technology to
model energy and events concepts and environments.
We also propose the use of linked data as a rich context
for CEP systems in order to make CEP engines more
effective in a high-scale, real time energy monitoring
scenario.
4. Current Results
Sustainable DERI [3] and DERI Energy (figure 1) are
in-progress projects to investigate the potential of our
approach in a typical SME with a medium size data
center and other office energy consumption equipments.
Figure 1, Architecture of DERI Energy Platform
5. References
[1] Luckham, D., The Power of Events. An Introduction to
Complex Event Processing in Distributed Enterprise Systems.
Addison-Wesley, Reading, April 2002.
[2] Berners-Lee T, Hendler J, Lassila O, The Semantic Web.
Scientific American 284(5):34–43, 2001.
[3] Edward Curry, Souleiman Hasan, Umair ul-Hassan,
Micah Herstand and Sean O’Rian, An Entity-Centric
Approach to Green Information Systems, European
Conference on Information Systems (ECIS 2011) {to
appear}.