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In this paper, we propose a distributed algorithm that aims to minimize aggregation latency under the physical interference model in wireless sensor networks of arbitrary topologies.
It is a challenge to derive a distributed solution to latency-minimizing data aggregation under the physical interference model because of the simple fact that global-scale information to compute the cumulative interference is needed at any node.
On the other hand, under the physical interference model, if and otherwise.
The use of our method under the physical interference model is another possible future work.
We obtain the successful transmission probabilities of the primary and the secondary network under the physical interference model.
Huang et al. [7] propose the first approximation algorithm for the MLBS problem under the physical interference model assuming each node is aware of its geographical location.
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There are only handful works that have considered the MLBS problem with the physical interference model.
To this end, the physical interference model, also called SINR-based interference model, is more realistic, where the cumulative interference of many nodes outside the interference range is not neglected.
The white counterattack consisted of physical interference with black riders on the track, owners refusing to hire black jockeys and the exclusionary practices of the newly formed Jockey Club.
In the function and the physical role interference comparisons, only the comparison of MPI interference with SF-36 social functioning showed moderate correlations (up 0.50).
Whether a transmission is successful or not is also influenced by the physical signal power, so the equivalent bandwidth of link i under logical inter-flow interference and physical interference can be calculated as follows: B Inter, i = ( 1 - CBT i ) × B bas × IR i (12).
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