Computer Science Colloquia
Wednesday, April 11, 2012
Krasimira Kapitanova
Advisor: Sang Son
Attending Faculty: John A. Stankovic, Chair; Sang H. Son, Kamin Whitehouse; Alfred
Weaver; and Stephen Patek
11:00 AM, Rice Hall, Rm. 242
Ph.D. Dissertation Presentation
Robust Real-Time Event Services in Wireless Sensor Networks
ABSTRACT
Event detection is one of the main components in numerous wireless sensor
network (WSN) applications. Regardless of the specific application, the
network should be able to detect if particular events of interest have
occurred or are about to. WSN events are not binary, but are based on
sensor fusion from many noisy sensors in complicated environments. Sensor
data may be missing, wrong, or out of date. Consequently, event services
must operate in real-time, support data fusion and confidence
calculations, and conserve power. Event services must also fundamentally
recognize location, since sensor network events are a function of where
they occur. Sensor network event services must be highly decentralized in
order to work on the limited capacity devices. The services must also minimize
false alarms. All these features make building event services for WSNs
very challenging. Our research focuses on enabling the design and
development of robust real-time event services. More specifically this work
investigates the following research problems:
*1. Event specification* We have developed a formal event description
language which is an enhanced Petri net and combines features from
Colored, Timed and Stochastic Petri nets. This language, coMpact Event
Detection and Analysis Language (MEDAL), can capture the structural,
spatial, and temporal properties of a complex event detection system.
MEDAL also addresses key aspects of sensor networks, such as
communication, actuation, and feedback control. MEDAL's graphical support,
inherited from Petri nets, makes the application models easy to understand
and accessible to a wide range of users.
*2.Event detection* The majority of current event detection approaches
rely on using precise, also called ~Q~Rcrisp~R~R, values to specify WSN
events. However, we believe that crisp values cannot adequately handle
the often imprecise sensor readings. In this work we have studied how
using fuzzy values could improve the accuracy, timeliness, and resource requirements
of event detection. Our experiments with real-world fire data have shown
that using fuzzy values results in more accurate event detection than when
crisp logic is used, since fuzzy logic is more resilient to imprecise
sensor readings.
*3. Robustness to node failures* Even if an event detection system has
been correctly designed and built, its continuous and reliable operation
is difficult to guarantee due to hardware degradation and environmental
changes. However, not all node failures have the same effect on
applications' behavior. Some node failures are critical and lead to
significant application degradation, while others may not affect the
application at all. We have designed techniques to detect node failures
that affect the application-level behavior of the system and minimize the
number of maintenance dispatches without sacrificing the event detection
accuracy of the application.