Paper
31 March 2011 Resource-efficient wireless monitoring based on mobile agent migration
Kay Smarsly, Kincho H. Law, Markus König
Author Affiliations +
Abstract
Wireless sensor networks are increasingly adopted in many engineering applications such as environmental and structural monitoring. Having proven to be low-cost, easy to install and accurate, wireless sensor networks serve as a powerful alternative to traditional tethered monitoring systems. However, due to the limited resources of a wireless sensor node, critical problems are the power-consuming transmission of the collected sensor data and the usage of onboard memory of the sensor nodes. This paper presents a new approach towards resource-efficient wireless sensor networks based on a multi-agent paradigm. In order to efficiently use the restricted computing resources, software agents are embedded in the wireless sensor nodes. On-board agents are designed to autonomously collect, analyze and condense the data sets using relatively simple yet resource-efficient algorithms. If having detected (potential) anomalies in the observed structural system, the on-board agents explicitly request specialized software agents. These specialized agents physically migrate from connected computer systems, or adjacent nodes, to the respective sensor node in order to perform more complex damage detection analyses based on their inherent expert knowledge. A prototype system is designed and implemented, deploying multi-agent technology and dynamic code migration, in a wireless sensor network for structural health monitoring. Laboratory tests are conducted to validate the performance of the agent-based wireless structural health monitoring system and to verify its autonomous damage detection capabilities.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kay Smarsly, Kincho H. Law, and Markus König "Resource-efficient wireless monitoring based on mobile agent migration", Proc. SPIE 7984, Health Monitoring of Structural and Biological Systems 2011, 798426 (31 March 2011); https://doi.org/10.1117/12.880016
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Cited by 17 scholarly publications.
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KEYWORDS
Sensors

Structural health monitoring

Sensor networks

Java

Aluminum

Computing systems

Prototyping

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