similar to: how to do probabilistic packet loss in kernel?

Hi, I am trying to install a proprietary qdisc made for research, it is not publically released yet, however its been used several times so i know it works. The files included are: q_xcp.c: static int xcp_parse_opt() static int xcp_print_opt() static int xcp_print_xstats() struct qdisc_util xcp_util = { "NULL", "xcp" ..... }; sch_xcp.c: static int

hi i tried the example given on the examples page to duplicate selected traffic like tc qdisc add dev eth0 root handle 1: prio tc qdisc add dev eth0 parent 1:3 handle 3: netem duplicate 40% tc filter add dev eth0 protocol ip parent 1:0 prio 3 u32 match ip dst 11.0.2.2 flowid 1:3 when i ping from 11.0.2.2 to this interface my machine hangs. the same thing works for drop or delay. i would

Hi, I am using netem to add loss and then adding another qdisc within netem according to the wiki. Then i want to change the netem drop probability without having to delete the qdisc and recreate it. I try it but I get invalid argument: thorium-ini hedpe # tc qdisc add dev ath0 root handle 1:0 netem drop 1% thorium-ini hedpe # tc qdisc add dev ath0 parent 1:1 handle 10: xcp capacity 54Mbit

Hey, I am getting an invalid argument trying to insert a qdisc: [root@emu-5 iproute2]# tc qdisc add dev eth0 root xcp capacity 50Mbit limit 500 RTNETLINK answers: Invalid argument I''m not sure whats wrong here, because i can successfully insert this qdisc on other computers of mine. How can i debug this? Thanks! George

Hi, I'm working on a classification problem and one of the methods I'd like to use are neural networks. I've been using nnet to build a classification network. However I would like to have the probabilities associated with the prediction. Are there any implementations of probabilistic neural networks available in R? thanks,

The following (occuring on debian/testing with kernel-image-2.6.8-2-386 version 2.6.8-13 and iproute version 20041019-3) confuses me: # tc qdisc add dev eth0 root handle 1: prio # tc filter add dev eth0 parent 1: proto ip pref 1 handle 1 fw classid 1:2 # tc filter ls dev eth0 filter parent 1: protocol ip pref 1 fw filter parent 1: protocol ip pref 1 fw handle 0x1 classid 1:2 # tc filter del dev

Dear R Community, I first apoligize to ask statistical questions of general domain, probably beyond the mere use of R. I want to analyze the following type of data with R . Total annual fisheries landings have been reported during 1950-2007 from a given fishery area. I am dealing with annual fisheries landings proportions (LP) estimated for trophic level (TL) classes of 0.1increment, i.e. each

Hello, I'm a new user to R and need some help coding a mathmatically simple aggregation of normal distributions. I have three normal distributions: A ~ N(8.51, 4.24^2) B ~ N(7.57, 3.62^2) C ~ N(10.84, 6.59^2) with correlation coefficients of: rho(AB) = 0.710 rho(AC) = 0.263 rho(BC) = 0.503 and I want to simulate Z = A + B + C, showing the results on a plot and fitting a distribution to the

Hi all, public-inbox allows searching for git blob names (e.g. "badc0ffee") in patches. Initially, I chose to use add_prefix for probabilistic terms, since I assumed it could be a superset of what boolean searching offered. Unfortunately, it doesn't seem to be the case because stemming is interfering. So switching to boolean filtering seems to work; and it is fine for mechanical

Dear useRs, I am pleased to announce the release of the new package PNN. PNN implements the algorithm proposed by Specht (1990). It is written in the R statistical language. It solves a common problem in automatic learning. Knowing a set of observations described by a vector of quantitative variables, we classify them in a given number of groups. Then, the algorithm is trained with this datasets

Dear useRs, I am pleased to announce the release of the new package PNN. PNN implements the algorithm proposed by Specht (1990). It is written in the R statistical language. It solves a common problem in automatic learning. Knowing a set of observations described by a vector of quantitative variables, we classify them in a given number of groups. Then, the algorithm is trained with this datasets

Hello, I'm using an SVM for predicting a model, but I'm most interested in the probability output. This is easy enough to calculate. My challenge is how to measure the relative performance of the SVM for different settings/parameters/etc. An AUC curve comes to mind, but I'm NOT interested in predicting true vs false. I am interested in finding the most accurate probability

I''m trying to setup a netem delay with no luck (using iproute2-2.6.8, compilation broke during arpd compile, so I use the tc binary in the tc/ subdir, there''s also a q_netem.so there). kernel is 2.6.8.1, compile with CPU cycle counter as time reference. I was using sch_delay of 2.6.7 happily with something like: tc qdisc add dev eth0 root 1: delay latency 1ms rate 35M now I use:

I''m trying to use tc and netem to delay packets from several different machines as they exit via eth0. Assume two source IPs, 10.0.0.122 and 10.0.0.133. I''d like to delay packets from the first one by 200ms, and packets from the second one by 300 ms. Any other traffic should be sent out normally. Here''s what I tried: # make three classes, 1:1, 1:2, and 1:3: tc qdisc add

Sorry this may well be defined as Off Topic. I apologize in advance. I am interested in performing what I think would be a probabilistic sensitivity simulation. I've done some crude ones before in excel but I'm wondering if R can help me do it more effectively? I have a set of theoretical variables for simplicity lets use (what I think) is an easier example: I have a peg and a hole

Hi! We want to run TCP streams to several port numbers through one interface, each with a different delay set by Netem. E.g. TCP streams to port 80 could have 50ms delay, while TCP streams to port 81 could have 100 ms delay and so on. We have tried to solve this by using a combination of tc filter and netem rules, but we can''t get it quite right. We are considering one class per port,

Hi I have two processes which take with a certain probability (p1 and p2) x number of years to complete (age1 and age2). As soon as thge first process is completed, the second one begins. I want to calculate the time it takes for the both processes to be completed. I have the following script which gives me the answer, butI think there must be a more elegant way of doing the calculations

Hello, thank You, this solution worked too. But had to do same thing for those files: test-http-client-errors.c:388 test-http-client-errors.c:484 test-http-client-errors.c:556 test-http-client-errors.c:636 test-http-server-errors.c:594 main.c:63 director.c:1445 director.c:1448 imap-client.c:253 director.c:1445 director.c:1448 mail-stats.c:56 Is this an old compiler issue or something else?

Hi all, I''m running some tests with netem and I noticed some strange behaviour that looks like a bug: I''m pinging another machine and adding delay with netem. When I tell netem to give me a 10ms delay, it works fine. The problem is that when I ask for a 11ms delay, it gives me 20ms! It happens for any value between 11ms an 20ms, and it repeats for values over 20ms, now

Hi all, I am trying to solve a tiny problem that is trivial to solve using dummynet (FreeBSD). I just want to add a delay of 50ms to each outgoing packet from an interface. This is to simulate a large pool of multiple modem users so I also need to add b/w limits etc (which seems to be easy to do). From the mailing list I could fine 2 qdiscs that can simulate latency : "delay" &