Network Slice Modeling

Users in 5G-Slicer are able to introduce network slices under the Fogify’s networks primitive. The model of network slices include the name, which is the identifier of the network slice, the network_type that is always should be slice, midhaul_qos that is the connectivity QoS among RUs and Edge nodes, backhaul_qos that is the QoS connectivity between cloud-enabled core and edge, RU to UE connection type (wireless_connection_type) along with its parameters, and optional property network_functions of the network functions (or VNFs), that includes the Fogify’s firewall rules (firewall_rules) and the packet level monitoring capability (packet_level_monitoring).

networks:
  - name: 'slice_name'
    network_type: slice
    midhaul_qos:
      ....
    backhaul_qos:
      ....
    wireless_connection_type: ....
    parameters:
      ....
    network_functions: # Optional
      ....
        

Midhaul and Backhaul QoS

For the midhaul and backhaul qos, users can introduce network latency, including delay and its deviation, data rate (bandwidth) and the packets’ error rate (error_rate).

  midhaul_qos:
      latency:
        delay: 30ms
        deviation: 1ms
      bandwidth: 100mbps
      error_rate: 1%

5G MIMO and SISO connectivity

For MIMO(mutli-input-multi-output) connections, users are able to select MIMO (or SISO for single-input-single-output) as wireless_connection_type and to introduce specific parameters, like transmit_power, which is the power in dbm of the transmitter, the currier frequency (carrier_frequency) in gigahrz, signal bandwidth in megahrz, user equipment noise figure (UE_noise_figure), RU and UE antenna gains (RU_antennas_gain & UE_antennas_gain), the expected (or measured) maximum and minimum bitrate (maximum_bitrate & maximum_bitrate), the system’s queuing delay (queuing_delay), and RU and UE antennas elements (RU_antennas & UE_antennas)

    networks:
      - name: dublin_network
        network_type: slice
        midhaul_qos: ...
        backhaul_qos: ...
        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
        network_functions: ....
        

Mathematical Models

Users are also able to select if the degradation of the signal follows a specific mathematical model. Specifically, we provide four different models, namely, static, step_wise, linear and logarithmic singal degradation.

Static Signal Degradation

Static (or flat) degradation model applies the same QoS in a specific radius around the RUs.
Users have to select FlatWirelessNetwork as the wireless_connection_type, the effective radius of the RUs, and the respective network’s QoS.

...
    wireless_connection_type: FlatWirelessNetwork
    parameters:
      radius: 8km
      qos:
        latency:
          delay: 5ms
          deviation: 1ms
        bandwidth: 10mbps
....

Step-wise Signal Degradation

Step-wise (or multi-range network) connection has different QoS for different ranges from the RU. For instance, the following description indicates that the QoS from 0 to 0.4km will be equals to 3ms delay and 10mbps data rate, from 0.4km to 0.7km will be 7ms delay and data rate again 10mbps, and, finally, from 0.7km to the radius the delay and data rate will be 15ms and 1mbps, respectively.

...
    wireless_connection_type: MultiRangeNetwork
    parameters:
      radius: 1km
      bins:
          0km:
            latency:
              delay: 3ms
              deviation: 1ms
            bandwidth: 10mbps
          0.4km:
            latency:
              delay: 7ms
              deviation: 1ms
            bandwidth: 10mbps
          0.7km:
            latency:
              delay: 15ms
              deviation: 1ms
            bandwidth: 1mbps
....

Linear and Logarithmic Signal Degradation

For linear and logarithmic degradation, users are able to select the best(best_qos) and worst(worst_qos) connection QoS and the radius. The system will degrade respectively the QoS based on the distance between RU-to-UE by following the respective function.

...
    wireless_connection_type: LinearDegradation|Log10Degradation
    parameters:
      radius: 0.8km
      best_qos:
        latency:
          delay: 5ms
          deviation: 1ms
        bandwidth: 10mbps
      worst_qos:
        latency:
          delay: 100ms
          deviation: 10ms
        bandwidth: 1mbps
...