Hi Tal,
The LinkLayerModel application generates two files, topology.out and
linkgain.out.
I don't know exactly what to do with the values.
1) The snippet of Python code create nodes:
f = open("topology.out", "r")
lines = f.readlines()
for line in lines:
s = line.split()
if (len(s) > 0):
m = t.getNode(s[0])
Here I create nodes with the IDs in the file, but where should I set
the dimension x/y? Which method should I use for this?
2) The snippet of Python code add a link from src to dest with gain.:
f = open("linkgain.out", "r")
lines = f.readlines()
for line in lines:
s = line.split()
if (len(s) > 0):
if (s[0] == "gain"):
r.add(int(s[1]), int(s[2]), float(s[3]))
Here I understood.
3) The snippet of Python code to create the noise model. Is it correct?
f = open("linkgain.out", "r")
lines = f.readlines()
for line in lines:
s = line.split()
if (len(s) > 0):
if (s[0] == "noise"):
t.getNode(int(s[1])).addNoiseTraceReading(int(s[2])l)
t.getNode(int(s[1])).addNoiseTraceReading(int(s[3])l)
for i in range(0, 16):
t.getNode(i).createNoiseModel()
Thanks and best regards
On Fri, Jun 6, 2008 at 3:12 PM, Tal Rusak <[EMAIL PROTECTED]> wrote:
> Here is an example of importing a topology file from the tutorials:
> f = open("15-15-tight-mica2-grid.txt", "r")
>
> lines = f.readlines()
> for line in lines:
> s = line.split()
> if (len(s) > 0):
> if (s[0] == "gain"):
> r.add(int(s[1]), int(s[2]), float(s[3]))
> (http://docs.tinyos.net/index.php/TOSSIM)
>
> Tal
>
>> I understood how to generate the topology file, my doubt now is:
>> Which command should I use to input these values?
>>
>>
>> On Fri, Jun 6, 2008 at 11:21 AM, Daniel Pereira <[EMAIL PROTECTED]>
>> wrote:
>>> I didn't understand how to configure the network topology for TOSSIM.
>>> The snippet of Python code create seven nodes.
>>> for i in range(0, 7):
>>> t.getNode(i).createNoiseModel()
>>>
>>> How can I relate this nodes with the network topology?
>>> Should I set the Channel, Radio and Topology parameters in the Python?
>>>
>>> Thanks all
>>>
>>>
>>>
>>>
>>> On Thu, Jun 5, 2008 at 12:14 PM, Tal Rusak <[EMAIL PROTECTED]> wrote:
>>>> Hi,
>>>> There are two components to the link model in TOSSIM 2.0.2: noise
>>>> and
>>>> gain. Noise is the external interference and noise from sources other
>>>> than the TinyOS network, which gain is the strength at which nodes in
>>>> the network can hear packets that other nodes send. The probability
>>>> of receiving a packet is given by the signal to noise ratio, which is
>>>> gain - noise in the dB scale considered here. This is explained in
>>>> http://sing.stanford.edu/pubs/ipsn07-noise.pdf
>>>> TOSSIM currently considers that gain is constant per node pair, and
>>>> network topologies can be constructed using the tool discussed at
>>>> http://www.tinyos.net/tinyos-2.x/doc/html/tutorial/usc-topologies.html
>>>> The TOSSIM tutorial shows how to use python to parse this tool's output
>>>> and to input the gain values to the simulator. Search for "topo.txt" in
>>>> this entry:
>>>> http://docs.tinyos.net/index.php/TOSSIM#Configuring_a_Network
>>>> Regarding the noise values, you can collect noise samples from your
>>>> environment using
>>>> tinyos-2.x-contrib/stanford-sing/apps/RssiSample
>>>> To create an artificial "low noise" environment, you can create a
>>>> text file with very low values. If your values in the noise file are
>>>> all at least 14 below the values used for gain, then all packets are
>>>> received. Just be sure to have at least 100 entries in the file.
>>>>
>>>> Thanks,
>>>> Tal
>>>>
>>>>> Hello
>>>>>
>>>>> How can I use a topology file in TOSSIM
>>>>> (http://www.tinyos.net/dist-2.0.0/tinyos-2.x/doc/html/tutorial/usc-topologies.html)
>>>>> once I have the .out
>>>>> files?
>>>>>
>>>>> The Tossim wiki show how to integrate a text file noise model like
>>>>> heavy-meyer but I didn't find how to use this outpouts.
>>>>>
>>>>> best regards
>>>>>
>>>>> _______________________________________________
>>>>> Tinyos-help mailing list
>>>>> [email protected]
>>>>> https://www.millennium.berkeley.edu/cgi-bin/mailman/listinfo/tinyos-help
>>>>>
>>>>
>>>>
>>>> _______________________________________________
>>>> Tinyos-help mailing list
>>>> [email protected]
>>>> https://www.millennium.berkeley.edu/cgi-bin/mailman/listinfo/tinyos-help
>>>>
>>>
>>
>
>
>
nk
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