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Random and directed walk-based top-(k) queries in wireless sensor networks.

Fu JS, Liu Y - Sensors (Basel) (2015)

Bottom Line: A strategy of choosing the "right" way in DWTQ is carefully designed for the token(s) to arrive at the high-value regions as soon as possible.When designing the walking strategy for DWTQ, the spatial correlations of the readings are also considered.Theoretical analysis and simulation results indicate that RWTQ and DWTQ both are very robust against these parameters discussed previously.

View Article: PubMed Central - PubMed

Affiliation: School of Electronic and Information Engineering, Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing Jiaotong University, Beijing 100044, China. 14111005@bjtu.edu.cn.

ABSTRACT
In wireless sensor networks, filter-based top-  query approaches are the state-of-the-art solutions and have been extensively researched in the literature, however, they are very sensitive to the network parameters, including the size of the network, dynamics of the sensors' readings and declines in the overall range of all the readings. In this work, a random walk-based top-  query approach called RWTQ and a directed walk-based top-  query approach called DWTQ are proposed. At the beginning of a top-  query, one or several tokens are sent to the specific node(s) in the network by the base station. Then, each token walks in the network independently to record and process the readings in a random or directed way. A strategy of choosing the "right" way in DWTQ is carefully designed for the token(s) to arrive at the high-value regions as soon as possible. When designing the walking strategy for DWTQ, the spatial correlations of the readings are also considered. Theoretical analysis and simulation results indicate that RWTQ and DWTQ both are very robust against these parameters discussed previously. In addition, DWTQ outperforms TAG, FILA and EXTOK in transmission cost, energy consumption and network lifetime.

No MeSH data available.


Related in: MedlinePlus

The token trapped by a high-density region.
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sensors-15-12273-f001: The token trapped by a high-density region.

Mentions: On the contrary, when a node finds that the pedometer is beyond a threshold , it realizes that the token should be sent to the BS by GPSR and then selects the next hop with the rules in [13]. Using the full list of neighbors to decide the next hop comes with one attendant drawback named Density-Trap (D-T): it is most likely that in a high-density region (H-R) the token will walks around and around, and it is hard to walk out. A simple example of such situation is shown in Figure 1. Here, the six black dots comprise an H-R and they can communicate with each other directly, i.e., each pair of them are neighbors. In addition, there are five stars and each star connects with the H-R by a “narrow bridge”, i.e., each star can only communicate with one black dot. Considering that a token randomly walks in the H-R, in each step, the probability that the token is sent to the stars is smaller than 1/5, because for a black dot located at the border of H-R, it sends the token to a star with a probability of 1/5, for the black dot locating at the center, it can’t send the token to the stars. As the H-R’s density increases, the probability that a token will walk out of H-R decreases, which would consume lots of energy and does not help get the top- readings in the network.


Random and directed walk-based top-(k) queries in wireless sensor networks.

Fu JS, Liu Y - Sensors (Basel) (2015)

The token trapped by a high-density region.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507629&req=5

sensors-15-12273-f001: The token trapped by a high-density region.
Mentions: On the contrary, when a node finds that the pedometer is beyond a threshold , it realizes that the token should be sent to the BS by GPSR and then selects the next hop with the rules in [13]. Using the full list of neighbors to decide the next hop comes with one attendant drawback named Density-Trap (D-T): it is most likely that in a high-density region (H-R) the token will walks around and around, and it is hard to walk out. A simple example of such situation is shown in Figure 1. Here, the six black dots comprise an H-R and they can communicate with each other directly, i.e., each pair of them are neighbors. In addition, there are five stars and each star connects with the H-R by a “narrow bridge”, i.e., each star can only communicate with one black dot. Considering that a token randomly walks in the H-R, in each step, the probability that the token is sent to the stars is smaller than 1/5, because for a black dot located at the border of H-R, it sends the token to a star with a probability of 1/5, for the black dot locating at the center, it can’t send the token to the stars. As the H-R’s density increases, the probability that a token will walk out of H-R decreases, which would consume lots of energy and does not help get the top- readings in the network.

Bottom Line: A strategy of choosing the "right" way in DWTQ is carefully designed for the token(s) to arrive at the high-value regions as soon as possible.When designing the walking strategy for DWTQ, the spatial correlations of the readings are also considered.Theoretical analysis and simulation results indicate that RWTQ and DWTQ both are very robust against these parameters discussed previously.

View Article: PubMed Central - PubMed

Affiliation: School of Electronic and Information Engineering, Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing Jiaotong University, Beijing 100044, China. 14111005@bjtu.edu.cn.

ABSTRACT
In wireless sensor networks, filter-based top-  query approaches are the state-of-the-art solutions and have been extensively researched in the literature, however, they are very sensitive to the network parameters, including the size of the network, dynamics of the sensors' readings and declines in the overall range of all the readings. In this work, a random walk-based top-  query approach called RWTQ and a directed walk-based top-  query approach called DWTQ are proposed. At the beginning of a top-  query, one or several tokens are sent to the specific node(s) in the network by the base station. Then, each token walks in the network independently to record and process the readings in a random or directed way. A strategy of choosing the "right" way in DWTQ is carefully designed for the token(s) to arrive at the high-value regions as soon as possible. When designing the walking strategy for DWTQ, the spatial correlations of the readings are also considered. Theoretical analysis and simulation results indicate that RWTQ and DWTQ both are very robust against these parameters discussed previously. In addition, DWTQ outperforms TAG, FILA and EXTOK in transmission cost, energy consumption and network lifetime.

No MeSH data available.


Related in: MedlinePlus