To the best of my knowledge attleast in tinyos-1.x the default radio model (not sure how you can replace this in 1.x) the input is link PRR's. That is you can use experimental data or use an analytical model to generate link PRR's for your topology (for e.g. use lossy builder) and give this as an input to to TOSSIM-1.x. Hence the simulation has no notion of power.
However in TOSSIM-2.x the radio model uses the notion of link gains to emulate packet losses and hence 2.x might actually might be able to get singal strength as part of the message.
-Avinash
On 5/10/06, Robert Szewczyk <
[EMAIL PROTECTED]> wrote:
Perhaps one of the TOSSIM experts will weigh in here; I believe this
is totally dependent on the radio model used by TOSSIM. I am not be
suprised that the default radio model produces 0 RSSI. Doing this
analysis on the motes will give you real data, otherwise you're
basically munging through someone else's experiments that generated
the TOSSIM models.
Rob
On 5/10/06, Venkat Manoj <[EMAIL PROTECTED]> wrote:
>
>
> Hey Rob,
>
> Can't I get the RSSI value too in TOSSIM? When I try to access the RSSI
> value (strength) in TOSSIM, I get a 0 everytime. Is doing the analysis on
> the motes the only way to get the RSSI and packet loss curve?
>
> Thanks,
> Venkat.
>
>
> ----- Original Message ----
> From: Robert Szewczyk <[EMAIL PROTECTED]>
> To: Venkat Manoj <[EMAIL PROTECTED]>
> Cc: Prabal Dutta < [EMAIL PROTECTED]>; tos
> <[email protected]>
> Sent: Wednesday, May 10, 2006 2:04:09 AM
> Subject: Re: [Tinyos-help] Re: LQI and probability of packet loss
>
>
>
> lqi exists only on certain platforms (I believe it applies to Telos
> and Tmote Sky, and probably MicaZ). lqi will not exists in TOSSIM or
> in mica/mica2 motes.
>
> Note that RSSI value can be accessed via
> Msg->strength
>
> Cheers
>
> Rob
>
> On 5/9/06, Venkat Manoj < [EMAIL PROTECTED]> wrote:
> >
> >
> > Guys,
> >
> > How can I get the LQI values? When I use this line in the code...
> >
> > TOS_MsgPtr Msg;
> > a_variable = Msg->lqi;
> >
> > I get an error saying that there is no member named lqi. So how is it
> > possible for me to get the LQI and RSSI values?
> >
> > Thanks,
> > Venkat.
> >
> >
> > ----- Original Message ----
> > From: Prabal Dutta <[EMAIL PROTECTED]>
> > To: [EMAIL PROTECTED]
> > Cc: tos <[email protected]>
> > Sent: Wednesday, May 10, 2006 1:35:51 AM
> > Subject: [Tinyos-help] Re: LQI and probability of packet loss
> >
> >
> >
> > Joe,
> >
> > There's nothing that I claim in this thread which you can't divine
> > from the data in your Telos paper, although it's not presented in that
> > paper in way that clearly conveys it, or by reading Levis and
> > student's paper. Or, talk with Rob, he appears to agree. The
> > compelling data is out there already. Just look at.
> >
> > I'm sure you can think of a couple of reasons why we might not be
> > ready to release our data/results yet. Use your imagination.
> >
> > - Prabal
> >
> > On 5/9/06, Joe Polastre < [EMAIL PROTECTED]> wrote:
> > > What is preventing the release of your data? Levis and his student
> > > have a paper already available in emnets, my paper was out last year,
> > > so why can't you release your data? they're called technical reports
> > > for a reason.
> > >
> > > bottom line--you need to show compelling data to be taken seriously.
> > >
> > > -Joe
> > >
> > > On 5/9/06, Prabal Dutta <[EMAIL PROTECTED]> wrote:
> > > > Joe,
> > > >
> > > > This discussion isn't about translating the paper's results to an open
> > > > air environment. It's about what PRR vs RSSI and PRR vs LQI looks
> > > > like. The mental exercise is visualizing that from the PRR vs
> > > > Distance, RSSI vs Distance, and LQI vs Distance data in the paper.
> > > > It's not impossible but its not immediately obvious to the casual
> > > > observer.
> > > >
> > > > As I wrote in my earlier e-mail, we're not yet ready to release our
> > > > findings, but we will in due time.
> > > >
> > > > - Prabal
> > > >
> > > > On 5/9/06, Joe Polastre <[EMAIL PROTECTED]> wrote:
> > > > > all of the variables were measured at the same time--lqi and rssi.
> it
> > > > > does not take a mental leap to understand the findings in an open
> air
> > > > > environment.
> > > > >
> > > > > prabal, I would be extremely enthusiastic to review your real world
> > > > > data on this topic. please send your studies to the list as I
> believe
> > > > > we all could profoundly benefit from the data behind your opinions.
> > > > >
> > > > > -Joe
> > > > >
> > > > > On 5/9/06, Prabal Dutta <[EMAIL PROTECTED]> wrote:
> > > > > > The Telos graphs are nice in that they show the relationship
> between
> > > > > > some of these variables but some mental gymnastics are required to
> > > > > > make the leap from what's shown to PRR vs RSSI and PRR vs LQI.
> And,
> > > > > > given the variances involved, I'm not sure that everyone would
> come
> > to
> > > > > > the same conclusion.
> > > > > >
> > > > > > I would argue that from a PRR, RSSI, and LQI perspective, distance
> > is
> > > > > > a largely unnecessary nuisance variable. Distance (and position)
> > > > > > ultimately affect RSSI and LQI, and perhaps knowing the distance
> > helps
> > > > > > in some way to determine PRR, but at the physical level, RSSI to
> > > > > > interference and noise largely determine whether packets are
> > received.
> > > > > >
> > > > > > So, if you can directly measure and correlate PRR, RSSI, and LQI,
> > then
> > > > > > it would make sense to do so and ignore any intermediate
> > > > > > parameterization (like distance).
> > > > > >
> > > > > > - Prabal
> > > > > >
> > > > > > On 5/9/06, Robert Szewczyk <[EMAIL PROTECTED] > wrote:
> > > > > > > There is a graph that shows a dependence between distance and
> PRR,
> > > > > > > LQI, and RSSI in the paper about Telos design (figure 5 in
> > > > > > >
> http://www.polastre.com/papers/spots05-telos.pdf)
> > > > > > > While it does not actually show the regression, and distance is
> > made
> > > > > > > explicit, it should at least give you a flavor of what to expect
> > out
> > > > > > > of each type of measurement
> > > > > > >
> > > > > > > Rob
> > > > > > >
> > > > > > > On 5/9/06, Prabal Dutta <[EMAIL PROTECTED]> wrote:
> > > > > > > > Yes, there is *some* relation: they're positively correlated.
> > But
> > > > on
> > > > > > > > the CC2420 radio, LQI shows significant variance for a given
> > packet
> > > > > > > > reception rate (PRR). You may be much better off using RSSI,
> > which
> > > > > > > > shows far less variance for a given PRR.
> > > > > > > >
> > > > > > > > You can use (logistic) regression to determine the
> relationship
> > the
> > > > > > variables:
> > > > > > > > - send a lot of packets between a lot of motes
> > > > > > > > - compute the PRR as the fraction of packets received over the
> > > > number
> > > > > > > > sent for each tx, rx link pair
> > > > > > > > - note the RSSI and LQI values
> > > > > > > > - Plot (and regress) PRR vs RSSI and PRR vs LQI
> > > > > > > >
> > > > > > > > Hope that helps.
> > > > > > > >
> > > > > > > > - Prabal
> > > > > > > >
> > > > > > > > On 5/9/06, Venkat Manoj <[EMAIL PROTECTED]> wrote:
> > > > > > > > >
> > > > > > > > > Hi all,
> > > > > > > > >
> > > > > > > > > Can anybody tell me if there is some relation between the
> link
> > > > quality
> > > > > > > > > indiactor (LQI) and the probability of packet loss, between
> > two
> > > > motes?
> > > > > > Or is
> > > > > > > > > there some method to find out the relation?
> > > > > > > > >
> > > > > > > > > Thanks,
> > > > > > > > > Venkat.
> > > > > > > > >
> > _______________________________________________
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> > > > > > > > >
> > > > > >
> > > >
> >
> https://mail.millennium.berkeley.edu/cgi-bin/mailman/listinfo/tinyos-help
> > > > > > > > >
> > > > > > > > >
> > > > > > > > >
> > > > > > > >
> > > > > > > >
> _______________________________________________
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> >
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> > > > > > >
> > > > > >
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