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Compared to previous proposals, we were pioneer at actually implementing and testing our solution in a real testbed.
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"And of course like any other security related company we have had independent security companies penetration test our solution and look at our architecture design".
To show the difference, we tested our solution on a second network, denoted as the sparse network, consisting of 100 randomly placed sensors.
We extensively tested our solution in different scenarios and we evaluated the different design trade-offs, showing the cost, performance and reliability gain compared to state-of-the-art static solutions.
To test our solution, we simulated a Chord network in which non-malicious peers maximize expected utility by adapting their relative use of their neighbors according to Equation 30.
We tested our solutions with multiple simulations that have globally shown that our MILP gives better results than local optimization.
Therefore, we test our solutions to the state-of-the-art MIML approaches, i.e., MIMLSVM [27] and MIMLfast, on the real operational data.
The rest of the paper is organised as follows: Section 2 is presenting the general architecture of the wireless networks structure we used for our research and where we tested our solutions.
We tested our solutions on simulated datasets then extended to experimental data from Pseudomonas syringae and ferret.
Looking at TI's Keystone 2, SoC is a logical next step, allowing us to test our tracing solution from scratch on a more complex and powerful device.
In order to confirm the results obtained from theoretical studies and simulations, we also tested our proposed solution in a real environment.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com