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Energy-aware topology control strategy for human-centric wireless sensor networks.

Meseguer R, Molina C, Ochoa SF, Santos R - Sensors (Basel) (2014)

Bottom Line: The obtained results help identify suitable mobile computing scenarios where the prediction of topology control messages can be used to save energy of the network nodes.These results also allow estimating the percentage of energy saving that can be expected, according to the features of the work scenario and the participants behavior.Designers of mobile collaborative applications that involve participatory or opportunistic sensing, can take advantage of these findings to increase the autonomy of their solutions.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Architecture, Universitat Polit├Ęcnica de Catalunya, Barcelona 08034, Spain. meseguer@ac.upc.edu.

ABSTRACT
The adoption of mobile and ubiquitous solutions that involve participatory or opportunistic sensing increases every day. This situation has highlighted the relevance of optimizing the energy consumption of these solutions, because their operation depends on the devices' battery lifetimes. This article presents a study that intends to understand how the prediction of topology control messages in human-centric wireless sensor networks can be used to help reduce the energy consumption of the participating devices. In order to do that, five research questions have been defined and a study based on simulations was conducted to answer these questions. The obtained results help identify suitable mobile computing scenarios where the prediction of topology control messages can be used to save energy of the network nodes. These results also allow estimating the percentage of energy saving that can be expected, according to the features of the work scenario and the participants behavior. Designers of mobile collaborative applications that involve participatory or opportunistic sensing, can take advantage of these findings to increase the autonomy of their solutions.

No MeSH data available.


Related in: MedlinePlus

Energy consumption versus network degree when nodes follow a SLAW model.
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f7-sensors-14-02619: Energy consumption versus network degree when nodes follow a SLAW model.

Mentions: Figures 6 and 7 indicate how the network degree affects the average energy consumption of the nodes in the previously presented interaction scenarios. This uncertainty was specified as RQ4. The results show that the network degree seems to be related to the number of nodes deployed in the area, which is not surprising due to the fact that we are considering a square area. Moreover, energy consumption behaves slightly different when considering Random Walk model and SLAW model. On the one hand, the average energy consumption increases linearly with the network degree when nodes move following a SLAW model. On the other hand, the average consumption grows exponentially when nodes assume a Random Walk model.


Energy-aware topology control strategy for human-centric wireless sensor networks.

Meseguer R, Molina C, Ochoa SF, Santos R - Sensors (Basel) (2014)

Energy consumption versus network degree when nodes follow a SLAW model.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3958264&req=5

f7-sensors-14-02619: Energy consumption versus network degree when nodes follow a SLAW model.
Mentions: Figures 6 and 7 indicate how the network degree affects the average energy consumption of the nodes in the previously presented interaction scenarios. This uncertainty was specified as RQ4. The results show that the network degree seems to be related to the number of nodes deployed in the area, which is not surprising due to the fact that we are considering a square area. Moreover, energy consumption behaves slightly different when considering Random Walk model and SLAW model. On the one hand, the average energy consumption increases linearly with the network degree when nodes move following a SLAW model. On the other hand, the average consumption grows exponentially when nodes assume a Random Walk model.

Bottom Line: The obtained results help identify suitable mobile computing scenarios where the prediction of topology control messages can be used to save energy of the network nodes.These results also allow estimating the percentage of energy saving that can be expected, according to the features of the work scenario and the participants behavior.Designers of mobile collaborative applications that involve participatory or opportunistic sensing, can take advantage of these findings to increase the autonomy of their solutions.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Architecture, Universitat Polit├Ęcnica de Catalunya, Barcelona 08034, Spain. meseguer@ac.upc.edu.

ABSTRACT
The adoption of mobile and ubiquitous solutions that involve participatory or opportunistic sensing increases every day. This situation has highlighted the relevance of optimizing the energy consumption of these solutions, because their operation depends on the devices' battery lifetimes. This article presents a study that intends to understand how the prediction of topology control messages in human-centric wireless sensor networks can be used to help reduce the energy consumption of the participating devices. In order to do that, five research questions have been defined and a study based on simulations was conducted to answer these questions. The obtained results help identify suitable mobile computing scenarios where the prediction of topology control messages can be used to save energy of the network nodes. These results also allow estimating the percentage of energy saving that can be expected, according to the features of the work scenario and the participants behavior. Designers of mobile collaborative applications that involve participatory or opportunistic sensing, can take advantage of these findings to increase the autonomy of their solutions.

No MeSH data available.


Related in: MedlinePlus