#!/usr/bin/env python
#
# NEPI, a framework to manage network experiments
# Copyright (C) 2013 INRIA
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 2 as
# published by the Free Software Foundation;
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
# Author: Alina Quereilhac
from nepi.execution.ec import ExperimentController
from nepi.execution.runner import ExperimentRunner
from nepi.util.netgraph import TopologyType
import nepi.data.processing.ccn.parser as ccn_parser
import networkx
import socket
import os
import numpy
from scipy import stats
from matplotlib import pyplot
import math
import random
def avg_interest_rtt(ec, run):
logs_dir = ec.run_dir
# Parse downloaded CCND logs
(graph,
content_names,
interest_expiry_count,
interest_dupnonce_count,
interest_count,
content_count) = ccn_parser.process_content_history_logs(
logs_dir, ec.netgraph.topology)
# statistics on RTT
rtts = [content_names[content_name]["rtt"] \
for content_name in content_names]
# sample mean and standard deviation
sample = numpy.array(rtts)
n, min_max, mean, var, skew, kurt = stats.describe(sample)
std = math.sqrt(var)
ci = stats.t.interval(0.95, n-1, loc = mean,
scale = std/math.sqrt(n))
global metrics
metrics.append((mean, ci[0], ci[1]))
return mean
def normal_law(ec, run, sample):
x = numpy.array(sample)
n = len(sample)
std = x.std()
se = std / math.sqrt(n)
m = x.mean()
se95 = se * 2
return m * 0.05 >= se95
def post_process(ec, runs):
global metrics
# plot convergence graph
y = numpy.array([float(m[0]) for m in metrics])
low = numpy.array([float(m[1]) for m in metrics])
high = numpy.array([float(m[2]) for m in metrics])
error = [y - low, high - y]
x = range(1,runs + 1)
# plot average RTT and confidence interval for each iteration
pyplot.errorbar(x, y, yerr = error, fmt='o')
pyplot.plot(x, y, 'r-')
pyplot.xlim([0.5, runs + 0.5])
pyplot.xticks(numpy.arange(1, len(y)+1, 1))
pyplot.xlabel('Iteration')
pyplot.ylabel('Average RTT')
pyplot.grid()
pyplot.savefig("plot.png")
pyplot.show()
content_name = "ccnx:/test/bunny.ts"
STOP_TIME = "5000s"
repofile = os.path.join(
os.path.dirname(os.path.realpath(__file__)),
"repoFile1.0.8.2")
def get_simulator(ec):
simulator = ec.filter_resources("linux::ns3::Simulation")
if not simulator:
node = ec.register_resource("linux::Node")
ec.set(node, "hostname", "localhost")
simu = ec.register_resource("linux::ns3::Simulation")
ec.register_connection(simu, node)
return simu
return simulator[0]
def add_collector(ec, trace_name, subdir, newname = None):
collector = ec.register_resource("Collector")
ec.set(collector, "traceName", trace_name)
ec.set(collector, "subDir", subdir)
if newname:
ec.set(collector, "rename", newname)
return collector
def add_dce_host(ec, nid):
simu = get_simulator(ec)
host = ec.register_resource("ns3::Node")
ec.set(host, "enableStack", True)
ec.register_connection(host, simu)
# Annotate the graph
ec.netgraph.annotate_node(nid, "host", host)
def add_dce_ccnd(ec, nid):
# Retrieve annotation from netgraph
host = ec.netgraph.node_annotation(nid, "host")
# Add dce ccnd to the dce node
ccnd = ec.register_resource("linux::ns3::dce::CCND")
ec.set (ccnd, "stackSize", 1<<20)
ec.set (ccnd, "debug", 7)
ec.set (ccnd, "capacity", 50000)
ec.set (ccnd, "StartTime", "1s")
ec.set (ccnd, "StopTime", STOP_TIME)
ec.register_connection(ccnd, host)
# Collector to retrieve ccnd log
collector = add_collector(ec, "stderr", str(nid), "log")
ec.register_connection(collector, ccnd)
# Annotate the graph
ec.netgraph.annotate_node(nid, "ccnd", ccnd)
def add_dce_ccnr(ec, nid):
# Retrieve annotation from netgraph
host = ec.netgraph.node_annotation(nid, "host")
# Add a CCN content repository to the dce node
ccnr = ec.register_resource("linux::ns3::dce::CCNR")
ec.set (ccnr, "repoFile1", repofile)
ec.set (ccnr, "stackSize", 1<<20)
ec.set (ccnr, "StartTime", "2s")
ec.set (ccnr, "StopTime", STOP_TIME)
ec.register_connection(ccnr, host)
def add_dce_ccncat(ec, nid):
# Retrieve annotation from netgraph
host = ec.netgraph.node_annotation(nid, "host")
# Add a ccncat application to the dce host
ccncat = ec.register_resource("linux::ns3::dce::CCNCat")
ec.set (ccncat, "contentName", content_name)
ec.set (ccncat, "stackSize", 1<<20)
ec.set (ccncat, "StartTime", "8s")
ec.set (ccncat, "StopTime", STOP_TIME)
ec.register_connection(ccncat, host)
def add_dce_fib_entry(ec, nid1, nid2):
# Retrieve annotations from netgraph
host1 = ec.netgraph.node_annotation(nid1, "host")
net = ec.netgraph.edge_net_annotation(nid1, nid2)
ip2 = net[nid2]
# Add FIB entry between peer hosts
ccndc = ec.register_resource("linux::ns3::dce::FIBEntry")
ec.set (ccndc, "protocol", "udp")
ec.set (ccndc, "uri", "ccnx:/")
ec.set (ccndc, "host", ip2)
ec.set (ccndc, "stackSize", 1<<20)
ec.set (ccndc, "StartTime", "2s")
ec.set (ccndc, "StopTime", STOP_TIME)
ec.register_connection(ccndc, host1)
def add_dce_net_iface(ec, nid1, nid2):
# Retrieve annotations from netgraph
host = ec.netgraph.node_annotation(nid1, "host")
net = ec.netgraph.edge_net_annotation(nid1, nid2)
ip1 = net[nid1]
prefix = net["prefix"]
dev = ec.register_resource("ns3::PointToPointNetDevice")
ec.set(dev,"DataRate", "5Mbps")
ec.set(dev, "ip", ip1)
ec.set(dev, "prefix", prefix)
ec.register_connection(host, dev)
queue = ec.register_resource("ns3::DropTailQueue")
ec.register_connection(dev, queue)
return dev
def add_edge(ec, nid1, nid2):
### Add network interfaces to hosts
p2p1 = add_dce_net_iface(ec, nid1, nid2)
p2p2 = add_dce_net_iface(ec, nid2, nid1)
# Create point to point link between interfaces
chan = ec.register_resource("ns3::PointToPointChannel")
ec.set(chan, "Delay", "0ms")
ec.register_connection(chan, p2p1)
ec.register_connection(chan, p2p2)
#### Add routing between CCN nodes
add_dce_fib_entry(ec, nid1, nid2)
add_dce_fib_entry(ec, nid2, nid1)
def add_node(ec, nid):
### Add CCN nodes (ec.netgraph holds the topology graph)
add_dce_host(ec, nid)
add_dce_ccnd(ec, nid)
if nid == ec.netgraph.targets()[0]:
add_dce_ccnr(ec, nid)
if nid == ec.netgraph.sources()[0]:
add_dce_ccncat(ec, nid)
def wait_guids(ec):
return ec.filter_resources("linux::ns3::dce::CCNCat")
if __name__ == '__main__':
metrics = []
# topology translation to NEPI model
ec = ExperimentController("dce_4n_linear",
topo_type = TopologyType.LINEAR,
node_count = 4,
assign_st = True,
assign_ips = True,
add_node_callback = add_node,
add_edge_callback = add_edge)
#### Run experiment until metric convergence
rnr = ExperimentRunner()
runs = rnr.run(ec,
min_runs = 10,
max_runs = 100,
compute_metric_callback = avg_interest_rtt,
evaluate_convergence_callback = normal_law,
wait_guids = wait_guids(ec))
### post processing
post_process(ec, runs)