TY - GEN

T1 - MWM

T2 - A map-based world model for wireless sensor networks

AU - Khelil, A.

AU - Shaikh, F.K.

AU - Ayari, B.

AU - Suri, Neeraj

PY - 2011/9/23

Y1 - 2011/9/23

N2 - A prominent functionality of a Wireless Sensor Network (WSN) is environmental monitoring. For this purpose the WSN creates a model for the real world by using abstractions to parse the collected data. Being cross-layer and application-oriented, most of WSN research does not allow for a widely accepted abstraction. A few approaches such as database-oriented and publish/subscribe provide acceptable abstractions by reducing application dependency and hiding communication details. Unfortunately, these approaches ignore the spatial correlation of sensor readings and still address single sensor nodes. In this work we present a novel approach based on a \world model" that exploits the spatial correlation of sensor readings and represents them as a collection of regions called maps. Maps are a natural way for the presentation of the physical world and its physical phenomena over space and time. Our Map-based World Model (MWM) abstracts from low-level communication issues and supports general applications by allowing for efficient event detection, prediction and queries. In addition our MWM unifies the monitoring of physical phenomena with network monitoring which maximizes its generality. Using two case studies we highlight the simplicity and also the versatility of the proposed architecture. From our approach we deduce a general modeling and design methodology for WSNs. Copyright © 2008 ICST.

AB - A prominent functionality of a Wireless Sensor Network (WSN) is environmental monitoring. For this purpose the WSN creates a model for the real world by using abstractions to parse the collected data. Being cross-layer and application-oriented, most of WSN research does not allow for a widely accepted abstraction. A few approaches such as database-oriented and publish/subscribe provide acceptable abstractions by reducing application dependency and hiding communication details. Unfortunately, these approaches ignore the spatial correlation of sensor readings and still address single sensor nodes. In this work we present a novel approach based on a \world model" that exploits the spatial correlation of sensor readings and represents them as a collection of regions called maps. Maps are a natural way for the presentation of the physical world and its physical phenomena over space and time. Our Map-based World Model (MWM) abstracts from low-level communication issues and supports general applications by allowing for efficient event detection, prediction and queries. In addition our MWM unifies the monitoring of physical phenomena with network monitoring which maximizes its generality. Using two case studies we highlight the simplicity and also the versatility of the proposed architecture. From our approach we deduce a general modeling and design methodology for WSNs. Copyright © 2008 ICST.

KW - Event Detection

KW - Monitoring

KW - Wireless Sensor Networks

KW - Sensor nodes

KW - Wireless sensor networks

KW - Application-oriented

KW - Environmental Monitoring

KW - Event detection

KW - General applications

KW - Network Monitoring

KW - Physical phenomena

KW - Proposed architectures

KW - Spatial correlations

KW - Abstracting

U2 - 10.4108/ICST.AUTONOMICS2008.4523

DO - 10.4108/ICST.AUTONOMICS2008.4523

M3 - Conference contribution/Paper

SN - 9789639799349

BT - Autonomics

PB - EUDL

ER -