From f56d62ef5b6575a1ae186b01b9260c489c17f593 Mon Sep 17 00:00:00 2001
From: MJB <mjb@it-innovation.soton.ac.uk>
Date: Sun, 21 Jan 2018 17:23:29 +0000
Subject: [PATCH] fixed simulation error as the timestamps where converted
incorrectly to mS when the precision in influx expects nS, the queries now()
- <time> work in Chronograf
---
src/mediaServiceSim/LineProtocolGenerator.py | 4 +-
src/mediaServiceSim/simulator_v2.py | 46 ++++++++++++--------
2 files changed, 30 insertions(+), 20 deletions(-)
diff --git a/src/mediaServiceSim/LineProtocolGenerator.py b/src/mediaServiceSim/LineProtocolGenerator.py
index 5f1c763..a8ccb92 100644
--- a/src/mediaServiceSim/LineProtocolGenerator.py
+++ b/src/mediaServiceSim/LineProtocolGenerator.py
@@ -83,7 +83,9 @@ def quote_wrap(str):
# InfluxDB likes to have time-stamps in nanoseconds
def _getNSTime(time):
# Convert to nano-seconds
- return 1000000 * time
+ timestamp = int(1000000000*time)
+ print("timestamp", timestamp)
+ return timestamp
# DEPRICATED
# ____________________________________________________________________________
diff --git a/src/mediaServiceSim/simulator_v2.py b/src/mediaServiceSim/simulator_v2.py
index f9ca86c..8cf7a9e 100644
--- a/src/mediaServiceSim/simulator_v2.py
+++ b/src/mediaServiceSim/simulator_v2.py
@@ -8,7 +8,7 @@ import random
# Simulation parameters
TICK_TIME = 1
DEFAULT_REQUEST_RATE_INCREMENT = 5
-SIMULATION_TIME_SEC = 10
+SIMULATION_TIME_SEC = 180
# CLMC parameters
INFLUX_DB_URL = 'http://192.168.50.10:8086'
@@ -25,8 +25,8 @@ class sim:
def run(self, simulation_length_seconds):
- start_time = time.time()
- current_time = int(time.time())
+ start_time = time.time()-SIMULATION_TIME_SEC
+ sim_time = start_time
ip_endpoints = [{'agent_url': 'http://192.168.50.11:8186', 'location': 'DC1', 'cpu': 16,
'mem': '8GB', 'storage': '1TB', 'request_queue': 0, 'request_arrival_rate': 0},
@@ -35,36 +35,44 @@ class sim:
]
# Simulate configuration of the ipendpoints
- # endpoint state->mu, sigma, mS normal distribution
- config_delay_dist = {"placed": [5000, 0.68], "booted": [10000, 0.68],"connected": [1000, 0.68]}
+ # endpoint state->mu, sigma, secs normal distribution
+ config_delay_dist = {"placed": [5, 0.68], "booted": [10, 0.68],"connected": [10, 0.68]}
# Place the endpoints
max_delay = 0
for ip_endpoint in ip_endpoints:
- delay_time = int(random.normalvariate(config_delay_dist['placed'][0], config_delay_dist['placed'][0]*config_delay_dist['placed'][1]))
- self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_vm_config('placed', ip_endpoint['cpu'], ip_endpoint['mem'], ip_endpoint['storage'], current_time+delay_time))
+ delay_time = random.normalvariate(config_delay_dist['placed'][0], config_delay_dist['placed'][0]*config_delay_dist['placed'][1])
+
+ # print('sim_time: ', sim_time)
+ # print('delay_time: ', delay_time)
+ # timestamp = sim_time+delay_time
+ # print('timestamp: ', timestamp)
+ # ns_time = int(timestamp*1000000)
+ # print('ns_time: ', ns_time)
+
+ self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_vm_config('placed', ip_endpoint['cpu'], ip_endpoint['mem'], ip_endpoint['storage'], sim_time+delay_time))
if delay_time > max_delay:
max_delay = delay_time
- current_time +=max_delay
+ sim_time +=max_delay
max_delay = 0
# Boot the endpoints
for ip_endpoint in ip_endpoints:
- delay_time = int(random.normalvariate(config_delay_dist['booted'][0], config_delay_dist['booted'][0]*config_delay_dist['booted'][1]))
- self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_vm_config('booted', ip_endpoint['cpu'], ip_endpoint['mem'], ip_endpoint['storage'], current_time+delay_time))
+ delay_time = random.normalvariate(config_delay_dist['booted'][0], config_delay_dist['booted'][0]*config_delay_dist['booted'][1])
+ self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_vm_config('booted', ip_endpoint['cpu'], ip_endpoint['mem'], ip_endpoint['storage'], sim_time+delay_time))
if delay_time > max_delay:
max_delay = delay_time
- current_time +=max_delay
+ sim_time +=max_delay
max_delay = 0
# Connect the endpoints
for ip_endpoint in ip_endpoints:
- delay_time = int(random.normalvariate(config_delay_dist['connected'][0], config_delay_dist['connected'][0]*config_delay_dist['connected'][1]))
- self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_vm_config('connected', ip_endpoint['cpu'], ip_endpoint['mem'], ip_endpoint['storage'], current_time+delay_time))
+ delay_time = random.normalvariate(config_delay_dist['connected'][0], config_delay_dist['connected'][0]*config_delay_dist['connected'][1])
+ self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_vm_config('connected', ip_endpoint['cpu'], ip_endpoint['mem'], ip_endpoint['storage'], sim_time+delay_time))
if delay_time > max_delay:
max_delay = delay_time
- current_time +=max_delay
+ sim_time +=max_delay
request_arrival_rate_inc = DEFAULT_REQUEST_RATE_INCREMENT
request_queue = 0
@@ -104,24 +112,24 @@ class sim:
cpu_active_time = int(requests_processed*request_processing_time)
cpu_idle_time = int(cpu_time_available-cpu_active_time)
cpu_usage = cpu_active_time/cpu_time_available
- self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_cpu_report(cpu_usage, cpu_active_time, cpu_idle_time, current_time))
+ self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_cpu_report(cpu_usage, cpu_active_time, cpu_idle_time, sim_time))
# calc network usage metrics with no constraints.
bytes_sent = 1024*requests_processed
bytes_rec = 32*requests_processed
- self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_network_report(bytes_rec, bytes_sent, current_time))
+ self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_network_report(bytes_rec, bytes_sent, sim_time))
# time to process all of the requests in the queue
peak_response_time = ip_endpoint['request_queue']*request_processing_time/ip_endpoint['cpu']
# mid-range
avg_response_time = (peak_response_time+request_processing_time)/2
- self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_mpegdash_report('https://Netflix.com/scream', ip_endpoint['request_arrival_rate'], avg_response_time, peak_response_time, current_time))
+ self._sendInfluxData(ip_endpoint['agent_url'], lp.generate_mpegdash_report('https://Netflix.com/scream', ip_endpoint['request_arrival_rate'], avg_response_time, peak_response_time, sim_time))
# remove requests processed off the queue
ip_endpoint['request_queue'] -= int(requests_processed)
- current_time += TICK_TIME*1000
- end_time = time.time()
+ sim_time += TICK_TIME
+ end_time = sim_time
print("Simulation Finished. Start time {0}. End time {1}. Total time {2}".format(start_time,end_time,end_time-start_time))
def _createDB(self):
--
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