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A search strategy of Level-Based Flooding for the Internet of Things.

Qiu T, Ding Y, Xia F, Ma H - Sensors (Basel) (2012)

Bottom Line: Query packets are broadcast in the network according to the levels of nodes.Upon receiving a query packet, sensor nodes decide how to process it according to the percentage of neighbors that have processed it.We show by extensive simulations that the performance of LBF in terms of cost and latency is much better than that of original flooding, and LBF can be used in IoT of different scales.

View Article: PubMed Central - PubMed

Affiliation: School of Software, Dalian University of Technology, Dalian 116620, China. qiutie@dlut.edu.cn

ABSTRACT
This paper deals with the query problem in the Internet of Things (IoT). Flooding is an important query strategy. However, original flooding is prone to cause heavy network loads. To address this problem, we propose a variant of flooding, called Level-Based Flooding (LBF). With LBF, the whole network is divided into several levels according to the distances (i.e., hops) between the sensor nodes and the sink node. The sink node knows the level information of each node. Query packets are broadcast in the network according to the levels of nodes. Upon receiving a query packet, sensor nodes decide how to process it according to the percentage of neighbors that have processed it. When the target node receives the query packet, it sends its data back to the sink node via random walk. We show by extensive simulations that the performance of LBF in terms of cost and latency is much better than that of original flooding, and LBF can be used in IoT of different scales.

No MeSH data available.


Related in: MedlinePlus

Average energy cost for finding all targets.
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f25-sensors-12-10163: Average energy cost for finding all targets.

Mentions: From Figures 24 and 25, we can know that the searching cost and energy consumption all increase with the improvement of network scale for each searching strategy. But the increase of LBF is much more slowly than that of basic flooding. Figure 24 shows the average cost of finding target nodes. We can observe that the average cost of search is much lower for LBF compared to that of basic flooding. The cost search is reduced about 54.5%. In basic flooding, every node nearly has to process a search packet at least once, which means a search packet needs to go through the whole network to find each target node. But in LBF, the average cost of search is nearly half. With the increase of nodes' number, the effect is much better.


A search strategy of Level-Based Flooding for the Internet of Things.

Qiu T, Ding Y, Xia F, Ma H - Sensors (Basel) (2012)

Average energy cost for finding all targets.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472822&req=5

f25-sensors-12-10163: Average energy cost for finding all targets.
Mentions: From Figures 24 and 25, we can know that the searching cost and energy consumption all increase with the improvement of network scale for each searching strategy. But the increase of LBF is much more slowly than that of basic flooding. Figure 24 shows the average cost of finding target nodes. We can observe that the average cost of search is much lower for LBF compared to that of basic flooding. The cost search is reduced about 54.5%. In basic flooding, every node nearly has to process a search packet at least once, which means a search packet needs to go through the whole network to find each target node. But in LBF, the average cost of search is nearly half. With the increase of nodes' number, the effect is much better.

Bottom Line: Query packets are broadcast in the network according to the levels of nodes.Upon receiving a query packet, sensor nodes decide how to process it according to the percentage of neighbors that have processed it.We show by extensive simulations that the performance of LBF in terms of cost and latency is much better than that of original flooding, and LBF can be used in IoT of different scales.

View Article: PubMed Central - PubMed

Affiliation: School of Software, Dalian University of Technology, Dalian 116620, China. qiutie@dlut.edu.cn

ABSTRACT
This paper deals with the query problem in the Internet of Things (IoT). Flooding is an important query strategy. However, original flooding is prone to cause heavy network loads. To address this problem, we propose a variant of flooding, called Level-Based Flooding (LBF). With LBF, the whole network is divided into several levels according to the distances (i.e., hops) between the sensor nodes and the sink node. The sink node knows the level information of each node. Query packets are broadcast in the network according to the levels of nodes. Upon receiving a query packet, sensor nodes decide how to process it according to the percentage of neighbors that have processed it. When the target node receives the query packet, it sends its data back to the sink node via random walk. We show by extensive simulations that the performance of LBF in terms of cost and latency is much better than that of original flooding, and LBF can be used in IoT of different scales.

No MeSH data available.


Related in: MedlinePlus