From: scipio Date: Fri, 20 Apr 2007 18:58:29 +0000 (+0000) Subject: MOre TOSIM X-Git-Tag: tinyos/2.0.1~12 X-Git-Url: https://oss.titaniummirror.com/gitweb/?p=tinyos-2.x.git;a=commitdiff_plain;h=fe6dea63c85c083e893dccf388735a52d7405de6 MOre TOSIM --- diff --git a/doc/html/tutorial/lesson11.html b/doc/html/tutorial/lesson11.html index a495f6a6..c8925457 100644 --- a/doc/html/tutorial/lesson11.html +++ b/doc/html/tutorial/lesson11.html @@ -523,32 +523,76 @@ DEBUG (32): Application booted a third time.
  • gain(src, dest): Return the gain value of the link from src to dest.
    • -
  • remove(src, dest): Remove the link from - src to dest.
    • +
  • threshold(): Return the CCA threshold.
    • +
  • setThreshold(val): Set the CCA threshold value in + dBm. The default is -72dbM.
    • + + -
  • setNoise(node, mean, variance): Set the noise - floor at node to be a gaussian distribution with - mean and variance.
    • +

    The default values for TOSSIM's radio model are based on the CC2420 radio, + used in the micaZ, telos family, and imote2. It uses an SNR curve derived + from experimental data collected using two micaZ nodes, RF shielding, and + a variable attenuator.

    + +

    In addition to the radio propagation above, TOSSIM + also simulates the RF noise and interference a node hears, both from other + nodes as well as outside sources. It uses the Closest Pattern Matching (CPM) + algorithm. CPM takes a noise trace as input and generates a statistical model + from it. This model can capture bursts of interference and other correlated + phenomena, such that it greatly improves the quality of the RF simulation. + It is not perfect (there are several things it does not handle, such as + correlated interference at nodes that are close to one another), but + it is much better than traditional, independent packet loss models. For + more details, please refer to the paper "Improving Wireless Simulation through + Noise Modeling," by Lee et al.

    + -
  • sensitivity(): Return the receive sensitivity of - the nodes.
    • +

    To configure CPM, you need to feed it a noise trace. You accomplish this + by calling addNoiseTraceReading on a Mote object. Once you + have fed the entire noise trace, you must call createNoiseModel + on the node. The directory tos/lib/tossim/noise contains + sample noise traces, which are a series of noise readings, one per line. + For example, these are the first 10 lines of meyer-heavy.txt, + which is a noise trace taken from Meyer Library at Stanford University:

    -
  • setSensitivity(val): Set the receive sensitivity - of nodes to be val. The sensitivity is how much - stronger a signal must be for it to be received - uncorrupted. E.g., a sensitivity of 3.0 (the default value) - means that a packet must be 3dBm greater than the sum of - noise and concurrent transmissions for it to be received - uncorrupted.
    • + 
    +-97
+-98
+-98
+-86
+-90
+-91
+-87
+-87
+-98
+-98
+
    -
  • threshold(): Return the CCA threshold.
    • +

    As you can see, the hardware noise floor is around -98 dBm, + but there are spikes of interference around -86dBm and -87dBm.

    -
  • setThreshold(val): Set the CCA threshold value in - dBm.The default is -95.
    • - - +

    This piece of code will give a node a noise model from a noise trace + file. It works for nodes 0-7: you can change the range appropriately:

    + 
    +noise = open("meyer-heavy.txt", "r")
+lines = noise.readlines()
+for line in lines:
+    str = line.strip()
+    if (str != ""):
+        val = int(str)
+        for i in range(0, 7):
+            t.getNode(i).addNoiseTraceReading(val)
+
+for i in range(0, 7):
+    t.getNode(i).createNoiseModel()
    + + +

    CPM can use a good deal of RAM: using the entire meyer-heavy trace as + input has a cost of approximately 10MB. You can reduce this overhead + by using a shorter trace; this will of course reduce simulation fidelity.

    +

    The Radio object only deals with physical layer propagation. The MAC object deals with the data link layer, packet lengths, and radio bandwidth. The default TOSSIM MAC @@ -664,14 +708,22 @@ for line in lines: t.addChannel("RadioCountToLedsC", sys.stdout) t.addChannel("Boot", sys.stdout) +noise = open("meyer-heavy.txt", "r") +lines = noise.readlines() +for line in lines: + str = line.strip() + if (str != ""): + val = int(str) + for i in range(1, 4): + t.getNode(i).addNoiseTraceReading(val) + +for i in range(1, 4): + t.getNode(i).createNoiseModel() + t.getNode(1).bootAtTime(100001); t.getNode(2).bootAtTime(800008); t.getNode(3).bootAtTime(1800009); -r.setNoise(1, -100.0, 5.0) -r.setNoise(2, -100.0, 5.0) -r.setNoise(3, -100.0, 5.0) - for i in range(0, 100): t.runNextEvent() @@ -713,10 +765,9 @@ DEBUG (3): RadioCountToLedsC: packet sent. DEBUG (1): Received packet of length 2. -

    If you set the noise to be 30 plus or minus 5 dBm instead - of 80 plus or minus 5 dBm, then nodes will never transmit, as - the default CCA threshold is -95 dBm. You'll see something - like this:

    +

    If you set node's clear channel assessment to be at -110dBm, + then nodes will never transmit, as noise and interference never + drop this low. You'll see something like this:

     1  2 -54.0
 2  1 -55.0
@@ -769,14 +820,11 @@ while (time + 50000000000 > t.time()):
         file format is
 
           
    -noise n avg std
 gain src dest g
           
    
 
-          where each statement is on a separate line. The noise
-          statement defines the noise observed at node n with
-          an average of avg and a standard deviation of
-          std.  The gain statement defines a propagation
+          where each statement is on a separate line.
+	The gain statement defines a propagation
           gain g when src transmits to dest. This
           is a snippet of python code that will parse this file
           format:
@@ -790,8 +838,6 @@ for line in lines:
   if (len(s) > 0):
     if (s[0] == "gain"):
       r.add(int(s[1]), int(s[2]), float(s[3]))
-    elif (s[0] == "noise"):
-      r.setNoise(int(s[1]), float(s[2]), float(s[3]))

    TOSSIM has a tool for the second option of generating a