4.5 Article

Communication Model and Protocol based on Multiple Static Sinks for Supporting Mobile Users in Wireless Sensor Networks

Journal

IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
Volume 56, Issue 3, Pages 1652-1660

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCE.2010.5606309

Keywords

Wireless sensor networks; Remote user; Mobile user; Multiple static sinks; Information sharing

Funding

  1. National Research Foundation of Korea [2010-0013335]
  2. National Research Foundation of Korea [과C6B1620] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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Typical communication model of wireless sensor networks consists of users, sinks, and a number of sensor nodes. The users are remote from wireless sensor networks and they gather data from the sinks via legacy networks. However, in practical sensor network applications, there are two types of users: traditional remote users and mobile users such as firefighters and soldiers. The mobile users may move around sensor fields and they communicate with the sinks only via the sensor networks in order to gather data like location information of victims in disaster areas. In this paper, in order to effectively support both the remote users and the mobile users, we propose a novel communication model relying on the typical sensor network model. In the model, multiple static sinks connect with legacy networks and divide a sensor field into the number of the multiple sinks. Through sharing queries and data via the legacy networks, the multiple static sinks provide high throughput through distributed data gathering and low latency through short-hops data delivery. Multiple static sinks deliver the aggregated data to the remote users via the legacy networks. In case of the mobile users, when a mobile user moves around, it receives the aggregated data from the nearest static sink. Simulation results show that the proposed model is more efficient in terms of energy consumption, data delivery ratio, and delay than the existing models(1).

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