In this paper we deal with energy-efficient data collection in sparse sensor networks with data mules. We analyze the problem of optimal data transfer from sensors to data mules, and derive an upper bound for the performance of ARQ-based data-transfer protocols. This analysis shows that protocols currently used have low performance, which results in unnecessary energy consumption. Based on these results we define and evaluate an Adaptive Data Transfer (ADT) protocol that is able to combine efficiency and adaptability to external conditions. Simulation results show that ADT not only reduces significantly the average data-transfer time in comparison with previous protocols, but also provides quasi-optimal performance. In addition, it is able to react quickly to variations in the external conditions and adapt to new conditions in a limited time. 1.

An Adaptive Data-transfer Protocol for Sensor Networks with Data Mules

Conti M;Passarella A;
2007

Abstract

In this paper we deal with energy-efficient data collection in sparse sensor networks with data mules. We analyze the problem of optimal data transfer from sensors to data mules, and derive an upper bound for the performance of ARQ-based data-transfer protocols. This analysis shows that protocols currently used have low performance, which results in unnecessary energy consumption. Based on these results we define and evaluate an Adaptive Data Transfer (ADT) protocol that is able to combine efficiency and adaptability to external conditions. Simulation results show that ADT not only reduces significantly the average data-transfer time in comparison with previous protocols, but also provides quasi-optimal performance. In addition, it is able to react quickly to variations in the external conditions and adapt to new conditions in a limited time. 1.
2007
Istituto di informatica e telematica - IIT
978-1-4244-0992-1
Condition monitoring
Data engineering
Pervasive computing
Wireless sensor networks
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/75867
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