A Middleware Architecture for Dynamic Reconfiguration of Agent Collaboration Spaces in Indoor Location-Aware Applications

Recently, indoor location-aware applications that provide interactive capability with the surrounding physical environment are increasingly in demand. These applications include mobile asset management, indoor navigation, and location-based reservation systems. In many cases, these services require...

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Bibliographic Details
Main Authors: Tae Hyon Kim, Hyeong Gon Jo, Seol Young Jeong, Soon Ju Kang
Format: Article
Language:English
Published: Wiley 2014-03-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2014/782928
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Summary:Recently, indoor location-aware applications that provide interactive capability with the surrounding physical environment are increasingly in demand. These applications include mobile asset management, indoor navigation, and location-based reservation systems. In many cases, these services require multiple and dynamic collaborations over a large number of service subscribers with a deterministic, fast response time. However, many studies still function primarily on client/server-based centralized architectures that are inefficient in supporting complex collaboration, due to their static organization and unpredictable network congestion. To address this problem, we propose a middleware architecture named Dynamic Reconfigurable Agent Space (DRAS), based on a collaboration of service agents that can be distributed over the requested service area. A service application can dynamically modify a service area according to the request of the service subscribers under the DRAS. To demonstrate the feasibility and performance of the DRAS, we evaluated the elapsed time for dynamic reconfiguration of the service area. Also, two general collaboration scenarios in indoor location-aware applications called voting and tracking were evaluated in the simulation and in a real environment. The evaluation shows that the proposed middleware is suitable for indoor location-aware applications that require a large number of mobile nodes and complex collaboration by the effective distribution of network traffic and processing around the service agents.
ISSN:1550-1477