IS_SDM: an in-network semantic sensor data model

ABSTRACT

Sensor nodes have been always acting only as a data collector inside wireless sensor networks. They usually perform energy-aware routing independently from the properties of collected sensed data. Such sensed data is interpreted into useful context information at the gateway after a great time lag and the sensors cannot respond to sudden events very rapidly. In this paper, we introduce the In-network Semantic Sensor Data Model (IS_SDM) which can provide sensor nodes with context-awareness and also energy consumption consideration. Sensor nodes can be more intelligent in adapting to ambient changes while data collection can be achieved more efficiently.

REFERENCES

• 1: Guanling Chen , David Kotz, A Survey of Context-Aware Mobile Computing Research, Dartmouth College, Hanover, NH, 2000
• 2: Anind Kumar Dey , Gregory D. Abowd, Providing architectural support for building context-aware applications, Georgia Institute of Technology, Atlanta, GA, 2000
• 3: TinyDB. http://telegraph.cs.berkeley.edu/tinydb/
• 4: TinyOS. http://www.tinyos.net

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods
          Subjects: Semantic networks

General Terms:
Design

Keywords:
data model, semantic, wireless sensor networks