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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.


Average load of each node in Scenario 3.
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f22-sensors-12-10163: Average load of each node in Scenario 3.

Mentions: Figures 21 and 22 are the simulation results of average load of each node to find all targets in LBF. The query packet is broadcast from nodes near the sink node to nodes far away from the sink node. If nodes are closer to the sink node, the average load is heavier, because they have to transmit more packets. From the two figures, we also can know the average load of each node is decreased with the increase of network scale.


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

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

Average load of each node in Scenario 3.
© Copyright Policy
Related In: Results  -  Collection

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

f22-sensors-12-10163: Average load of each node in Scenario 3.
Mentions: Figures 21 and 22 are the simulation results of average load of each node to find all targets in LBF. The query packet is broadcast from nodes near the sink node to nodes far away from the sink node. If nodes are closer to the sink node, the average load is heavier, because they have to transmit more packets. From the two figures, we also can know the average load of each node is decreased with the increase of network scale.

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.