An energy-efficient context management framework for ubiquitous systems - Archive ouverte HAL
Communication Dans Un Congrès Année : 2013

An energy-efficient context management framework for ubiquitous systems

Vinicius L. Bezerra
  • Fonction : Auteur
Misael C. Junior
  • Fonction : Auteur
Olga Valeria
  • Fonction : Auteur
Constantino D. Neto
  • Fonction : Auteur
Liliam B. Leal
  • Fonction : Auteur
Marcus Vinicius Lemos
  • Fonction : Auteur
Carlos Giovanni Carvalho
  • Fonction : Auteur
José Filho
  • Fonction : Auteur

Résumé

Sensor-rich Context Management Frameworks (CMF) for Ubiquitous Systems should be able to continuosly gather raw data from observed entities (e.g., people, surround enviroment) in order to characterize the current situation (i.e., context). However, the energy of sensors can end up, which reduce the ability of CMF for detecting the current situation, directly affecting the availability of context-aware applications/services. This paper propose a data reduction approach to lower the amount of data sent to CMF over the network, minimising the energy consumption and the network traffic of sensor-rich CMF. The proposed data reduction approach rebuilds data that are not intentionally sent from sensors by prediction based on simple linear regression. The gathered raw data is modeled by linear equations and its parameters are sent to the CMF, instead of a set of readings. Thus, it reduces the communication overhead between sensors and CMF, enhancing the lifetime of sensors. Experimental results show that is possible to reduce the amount of packets sent over the network to 3% in ECG monitoring service, and 12.15% in beehive monitoring service with mean square error of 0.0009 and 0.0981, respectively.
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Dates et versions

hal-00954663 , version 1 (03-03-2014)

Identifiants

Citer

Vinicius L. Bezerra, Misael C. Junior, Olga Valeria, Constantino D. Neto, Liliam B. Leal, et al.. An energy-efficient context management framework for ubiquitous systems. 10th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2013) and 10th IEEE International Conference on Autonomic and Trusted Computing (ATC 2013), Dec 2013, Vietri sul Mare, Italy. pp.697--702, ⟨10.1109/UIC-ATC.2013.56⟩. ⟨hal-00954663⟩
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