Difference between revisions of "Probabilistic Coverage and Connectivity"
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− | being updated ... | + | being be updated .... for now see http://nsl.cs.sfu.ca/projects/wsn/ |
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+ | In this project, we consider probabilistic sensing and radio communication models in designing protocols for large-scale sensor networks. Probabilistic models are more realistic in capturing the characteristics of actual sensors than the over-simplified regular disk model. | ||
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+ | We first develop a probabilistic coverage protocol that employs probabilistic sensing models. | ||
+ | It is expected that different sensor types will require different sensing models. Designing, implementing, and testing a different coverage protocol for each sensing model is indeed an extremely costly process. We designed our protocol with limited dependence on the sensing model: Our protocol requires the computation of a single parameter from the adopted sensing model, while everything else remains the same. We showed how this parameter can be derived in general, and we did the calculations for two common sensing models. Our simulations showed that our protocol outperforms all other protocols in the literature in several aspects, including the number of activated sensors and total energy consumed. |
Revision as of 15:09, 7 March 2008
being be updated .... for now see http://nsl.cs.sfu.ca/projects/wsn/
In this project, we consider probabilistic sensing and radio communication models in designing protocols for large-scale sensor networks. Probabilistic models are more realistic in capturing the characteristics of actual sensors than the over-simplified regular disk model.
We first develop a probabilistic coverage protocol that employs probabilistic sensing models. It is expected that different sensor types will require different sensing models. Designing, implementing, and testing a different coverage protocol for each sensing model is indeed an extremely costly process. We designed our protocol with limited dependence on the sensing model: Our protocol requires the computation of a single parameter from the adopted sensing model, while everything else remains the same. We showed how this parameter can be derived in general, and we did the calculations for two common sensing models. Our simulations showed that our protocol outperforms all other protocols in the literature in several aspects, including the number of activated sensors and total energy consumed.