def create_application():
# APLICATION
a = Application(name="VLIoT")
# MODULES (face detection, feature extraction, face recognition)
a.set_modules([{"Camera":{"Type":Application.TYPE_SOURCE}},
{"MLTTask": {"RAM": 256, "Type": Application.TYPE_MODULE}},
{"FLTTask": {"RAM": 256, "Type": Application.TYPE_MODULE}},
{"DLTTask": {"Type": Application.TYPE_SINK}}
])
# MESSAGES
m_cam_mlt = Message("M.Cam", "Camera", "MLTTask", instructions=1*10^6, bytes=2000)
m_mlt_flt = Message("M.MLT", "MLTTask", "FLTTask", instructions=1*10^6, bytes=2000)
m_flt_dlt = Message("M.FLT", "FLTTask", "DLTTask", instructions=1*10^6, bytes=2000)
# Add in the application those messages that come from pure sources (sensors). This distinction allows them to be controlled by the (:mod:`Population`) algorithm
a.add_source_messages(m_cam_mlt)
# Este nao eh o caso de usar um service_source - VER EXEMPLO DE VRGAME
# Um service_source normalmente modela um Module que produz dados de controle, por exemplo.
# dDistribution = deterministicDistribution(name="Deterministic", time=100)
# a.add_service_source("Camera", dDistribution, m_mlt_flt)
# MODULE SERVICES
a.add_service_module("MLTTask", m_cam_mlt, m_mlt_flt, fractional_selectivity, threshold=1.0)
a.add_service_module("FLTTask", m_mlt_flt, m_flt_dlt, fractional_selectivity, threshold=1.0)
a.add_service_module("DLTTask", m_flt_dlt)
return a
def create_applications_from_json(data):
applications = {}
for app in data:
a = Application(name=app["name"])
modules = [{"None":{"Type":Application.TYPE_SOURCE}}]
for module in app["module"]:
if "RAM" in module.keys():
modules.append({module["name"]: {"RAM": module["RAM"], "Type": Application.TYPE_MODULE}})
else:
modules.append({module["name"]: {"RAM": 1, "Type": Application.TYPE_MODULE}})
a.set_modules(modules)
ms = {}
for message in app["message"]:
#print "Creando mensaje: %s" %message["name"]
ms[message["name"]] = Message(message["name"],message["s"],message["d"],instructions=message["instructions"],bytes=message["bytes"])
if message["s"] == "None":
a.add_source_messages(ms[message["name"]])
#print "Total mensajes creados %i" %len(ms.keys())
for idx, message in enumerate(app["transmission"]):
if "message_out" in message.keys():
value_treshld = 1.0
if "fractional" in message.keys():
value_treshld = message["fractional"]
a.add_service_module(message["module"],ms[message["message_in"]], ms[message["message_out"]], fractional_selectivity, threshold=value_treshld)
else:
a.add_service_module(message["module"], ms[message["message_in"]])
applications[app["name"]]=a
#a.add_service_module("Client", m_egg, m_sensor, fractional_selectivity, threshold=0.9)
return applications
def create_application():
# APLICATION
a = Application(name="SimpleCase")
# (S) --> (ServiceA) --> (A)
a.set_modules([{
"Sensor": {
"Type": Application.TYPE_SOURCE
}
}, {
"ServiceA": {
"RAM": 10,
"Type": Application.TYPE_MODULE
}
}, {
"Actuator": {
"Type": Application.TYPE_SINK
}
}])
"""
Messages among MODULES (AppEdge in iFogSim)
"""
m_a = Message("M.A",
"Sensor",
"ServiceA",
instructions=20 * 10 ^ 6,
bytes=1000)
m_b = Message("M.B",
"ServiceA",
"Actuator",
instructions=30 * 10 ^ 6,
bytes=500,
broadcasting=True)
"""
Defining which messages will be dynamically generated # the generation is controlled by Population algorithm
"""
a.add_source_messages(m_a)
"""
MODULES/SERVICES: Definition of Generators and Consumers (AppEdges and TupleMappings in iFogSim)
"""
# MODULE SERVICES
a.add_service_module("ServiceA",
m_a,
m_b,
fractional_selectivity,
threshold=1.0)
return a
def create_application():
# APLICATION
a = Application(name="EGG_GAME")
a.set_modules([{"EGG":{"Type":Application.TYPE_SOURCE}},
{"Display": {"Type": Application.TYPE_SINK}},
{"Client": {"RAM": 10, "Type": Application.TYPE_MODULE}},
{"Calculator": {"RAM": 10, "Type": Application.TYPE_MODULE}},
{"Coordinator": {"RAM": 10, "Type": Application.TYPE_MODULE}}
])
"""
Messages among MODULES (AppEdge in iFogSim)
"""
m_egg = Message("M.EGG", "EGG", "Client", instructions=2000*10^6, bytes=500)
m_sensor = Message("M.Sensor", "Client", "Calculator", instructions=3500*10^6, bytes=500)
m_player_game_state = Message("M.Player_Game_State", "Calculator", "Coordinator", instructions=1000*10^6, bytes=1000)
m_concentration = Message("M.Concentration", "Calculator", "Client", instructions=14*10^6, bytes=500) # This message is sent to all client modules
m_global_game_state = Message("M.Global_Game_State", "Coordinator", "Client", instructions=28*10^6, bytes=1000, broadcasting=True) # This message is sent to all client modules
m_global_state_update = Message("M.Global_State_Update", "Client", "Display",instructions=1000*10^6,bytes=500)
m_self_state_update = Message("M.Self_State_Update", "Client", "Display",instructions=1000*10^6,bytes=500)
"""
Defining which messages will be dynamically generated # the generation is controlled by Population algorithm
"""
a.add_source_messages(m_egg)
"""
MODULES/SERVICES: Definition of Generators and Consumers (AppEdges and TupleMappings in iFogSim)
"""
# MODULE SOURCES: only periodic messages
dDistribution = deterministicDistribution(name="Deterministic", time=100)
a.add_service_source("Calculator", dDistribution, m_player_game_state) #According with the comments on VRGameFog.java, the period is 100ms
a.add_service_source("Coordinator", dDistribution, m_global_game_state)
# # MODULE SERVICES
a.add_service_module("Client", m_egg, m_sensor, fractional_selectivity, threshold=0.9)
a.add_service_module("Client", m_concentration, m_self_state_update, fractional_selectivity, threshold=1.0)
a.add_service_module("Client", m_global_game_state, m_global_state_update, fractional_selectivity, threshold=1.0)
a.add_service_module("Calculator", m_sensor, m_concentration, fractional_selectivity, threshold=1.0)
a.add_service_module("Coordinator", m_player_game_state)
return a
def create_applications_from_json(data):
applications = {}
for app in data:
# Create application
a = Application(name=app["name"])
# Set modules
modules = []
for module in app["module"]:
modules.append({
module["name"]: {
"RAM": module["RAM"],
"Type": module["Type"]
}
})
a.set_modules(modules)
# Set messages
ms = {}
for message in app["message"]:
# print "Creando mensaje: %s" %message["name"]
ms[message["name"]] = Message(message["name"],
message["src"],
message["dst"],
instructions=message["instructions"],
bytes=message["bytes"])
if message["src"] == "Source":
a.add_source_messages(ms[message["name"]])
for idx, message in enumerate(app["service"]):
if "message_out" in message.keys():
a.add_service_module(message["module"],
ms[message["message_in"]],
ms[message["message_out"]],
fractional_selectivity,
threshold=1.0)
# else:
# a.add_service_module(message["module"], ms[message["message_in"]])
applications[app["name"]] = a
return applications
def create_application(name, params=None):
# APLICATION
a = Application(name=name, params=params)
# MODULES (face detection, feature extraction, face recognition)
a.set_modules([{
"Camera": {
"Type": Application.TYPE_SOURCE
}
}, {
"MLO": {
"RAM": 256,
"Type": Application.TYPE_MODULE
}
}, {
"Broker": {
"RAM": 256,
"Type": Application.TYPE_MODULE
}
}, {
"FLO": {
"RAM": 256,
"Type": Application.TYPE_MODULE
}
}, {
"DLO": {
"Type": Application.TYPE_SINK
}
}])
# MESSAGES
m_cam_mlo = Message("RawVideo",
"Camera",
"MLO",
instructions=100 * 10 ^ 6,
bytes=20000)
m_mlo_brk = Message("ObjectDetected",
"MLO",
"Broker",
instructions=5 * 10 ^ 6,
bytes=2000)
m_brk_flo = Message("IdentifyObject",
"Broker",
"FLO",
instructions=50 * 10 ^ 6,
bytes=2000)
m_flo_brk = Message("ObjectIdentified",
"FLO",
"Broker",
instructions=2 * 10 ^ 6,
bytes=100)
m_brk_dlo = Message("EventIdentified",
"Broker",
"DLO",
instructions=5 * 10 ^ 6,
bytes=2000)
# Add in the application those messages that come from pure sources (sensors).
# This distinction allows them to be controlled by the (:mod:`Population`) algorithm
a.add_source_messages(m_cam_mlo)
# dDistribution = deterministicDistribution(name="Deterministic", time=50)
# Which module will start processing services and in which distribution and message
# a.add_service_source("Camera", dDistribution, m_cam_mlo)
# MODULE SERVICES
a.add_service_module("MLO",
message_in=m_cam_mlo,
message_out=m_mlo_brk,
distribution=fractional_selectivity,
threshold=0.5) # probability to yield message_out
a.add_service_module("Broker", message_in=m_mlo_brk, message_out=m_brk_flo)
a.add_service_module("FLO", message_in=m_brk_flo, message_out=m_flo_brk)
a.add_service_module("Broker", message_in=m_flo_brk, message_out=m_brk_dlo)
a.add_service_module("DLO", message_in=m_brk_dlo)
return a