Limits...
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.


Ratio of successful query.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3472822&req=5

f27-sensors-12-10163: Ratio of successful query.

Mentions: Figure 27 shows the ratio of successful query of the two strategies. The figure shows that the ratios of two strategies are all nearly 100%. As the nodes are all deployed randomly in monitored areas, there may be dead nodes exiting. As a consequence, the successful query ratio is not 100%. There is more control on the diffusion of query packets in our strategy, so the ratio is a little lower than that of basic flooding strategy.


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

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

Ratio of successful query.
© Copyright Policy
Related In: Results  -  Collection

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

f27-sensors-12-10163: Ratio of successful query.
Mentions: Figure 27 shows the ratio of successful query of the two strategies. The figure shows that the ratios of two strategies are all nearly 100%. As the nodes are all deployed randomly in monitored areas, there may be dead nodes exiting. As a consequence, the successful query ratio is not 100%. There is more control on the diffusion of query packets in our strategy, so the ratio is a little lower than that of basic flooding strategy.

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.