Dublin's Buses Use-case
5G-Slicer gives the opportunity for users to implement their scenarios via the Template class (from usecases.template import Template).
Specifically, users need to implement generate_experiment function or to utilize the already created use-cases of the 5G-Slicer packet.
The 5G-Slicer has already implemented a city-scale usecase of dublin’s buses datasets.
Users need only to introduce their application and a basic 5G-Slicer model like the following:
services:
cloud_service:
image: bus-exp:0.0.1
edge_service:
image: bus-exp:0.0.1
bus_service:
image: bus-exp:0.0.1
environment:
- "NODE_TYPE=IOT_NODE"
volumes:
- "/home/ubuntu/data:/data"
version: '3.7'
x-fogify:
networks:
- network_type: slice
midhaul_qos:
latency:
delay: 10ms
deviation: 1ms
bandwidth: 1000mbps
backhaul_qos:
latency:
delay: 30ms
deviation: 1ms
bandwidth: 100mbps
wireless_connection_type: MIMO
parameters:
transmit_power: 30 # dbm
carrier_frequency: 28 # gigahrz
bandwidth: 100 # megahrz
UE_noise_figure: 7.8 # db
RU_antennas_gain: 8 # db
UE_antennas_gain: 3 # db
maximum_bitrate: 538.71
minmum_bitrate: 53.87
queuing_delay: 2 # ms
RU_antennas: 8
UE_antennas: 4
name: dublin_network
nodes:
- capabilities:
memory: 2G
processor:
clock_speed: 2400
cores: 4
name: cloud_machine
- capabilities:
memory: 2G
processor:
clock_speed: 1400
cores: 2
name: edge_device
- capabilities:
memory: 0.25G
processor:
clock_speed: 500
cores: 1
name: bus_device
Then, they need to select specific parameters at the BusExperiment class implementation like:
bounding box (bounding_box) in which the execution will take place,
number of RUs, MECs, Cloud nodes, and buses (num_of_RUs, num_of_edge, num_of_clouds, num_of_buses)
that the system randomly will extract from the dublin’s buses dataset, place of the traces file and bus stop file, etc.
Then, the function generate_experiment will return a SlicerSDK object that already has the information about the deployment.
from usecases.dublin_buses_experiment import BusExperiment
from SlicerSDK import SlicerSDK
file_path = "<docker-compose.yaml path>"
fogify_controller_url = "http://controller:5000"
slicerSDK = SlicerSDK(fogify_controller_url, file_path)
experiment = BusExperiment(slicerSDK,
bounding_box = ( # geographic bounding box of the experiment
(53.33912464060235, -6.286239624023438),
(53.35833815100412, -6.226158142089845)),
num_of_RUs = 1, # number of radio units
num_of_edge = 1, # number of edge servers
num_of_clouds = 1, # number of cloud servers
num_of_buses = 1, # number of IoTs (buses)
time_to_run = 60, # minimum time of a bus-trace for the bounding box
traces_filename = 'usecases/data/all.csv', # file of the traces
bus_stops_filename = 'usecases/data/stops.csv', # file of the bus stops
edge_service = 'edge_service', # name of the edge service of the docker-compose file
edge_device = 'edge_device', # name of the edge device (described in fogify model) of the docker-compose file
bus_service = 'bus_service', # name of the IoT workload service of the docker-compose file
bus_device = 'bus_device', # name of the IoT device (described in fogify model) of the docker-compose file
cloud_service = 'cloud_service', # name of the cloud service of the docker-compose file
cloud_device = 'cloud_machine', # name of the cloud service device (described in fogify model) of the docker-compose file
slice_name = 'dublin_network', # name of the network that will be created
max_num_of_trace_steps = 60, # maximum number of changes(locations) that a trace can have
min_num_of_trace_steps = 0, # minimum number of changes(locations) that a trace can have
bus_ids = [], # specific bus-ids (traces) for the emulation, if it is empty, system takes `num_of_buses` randomly
ru_overlap: str = "random" # selects specific RUs based on their radius overlapping (`random`, `min_density`, `max_density`, `kmeans`)
)
slicerSDK = experiment.generate_experiment() # builds the experiment based on user's preferences
slicerSDK.deploy() # deploy the infrastructure
slicerSDK.scenario_execution('mobility_scenario') # executes the mobility scenario of the selected buses