The number of sensors deployed for a myriad of applications is expected
to increase dramatically in the coming few years. This is spurred by
advances in wireless communications and the growing interest in
wireless sensor networks. This growth will not only simplify the access
to information sources but also will motivate the creation of numerous
new ones. Paradoxically, this growth will make the task of getting a
meaningful information obtained from disparate sensor nodes not a
trivial one. On the one hand, traffic overheads and the increased
probabilities of hardware failures makes it very difficult to maintain
an always-on, ubiquitous service. On the other hand, the heterogeneity
of the sensor nodes makes finding, extracting, and aggregating data at
the processing elements and sink nodes much more harder.
These two issues (away from distribution, dynamicity, accuracy, and
reliability issues) impose the need for a more efficient and reliable
techniques for information integration of data collected from sensor
nodes.
The personalized, continuously running, and semi-autonomous properties
of software agents make them well suited for data integration in
wireless sensor nodes applications.
In this talk, we first address the issues related to data integration
in wireless sensor networks with respect to heterogeneity, dynamicity,
and distribution at both the technology and application levels. Second,
we study the roles agents can perform to reduce network traffic
overheads, improve scalability and extensibility of wireless networks
and increase the stability and reliability of networks against hardware
and software failures. Third, we discuss a scenario of what we believe
a uniform interface to data collected from sensor nodes that will map
sensor specific data to the global information source based on a
context exported by software agents to the data integration system.