RecurrentEdgeProcessCPUNeed
Params
name
A human readable description of the object.
edge_component
An instance of EdgeComputerCPUComponent.
Backwards links
Calculated attributes
recurrent_need
Example value: 168 values in cpu_core:
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
Depends directly on:
through the following calculations:
You can also visit the link to edge process CPU need recurrent need’s full calculation graph.
validated_recurrent_need
Example value: 168 values in cpu_core:
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
Depends directly on:
through the following calculations:
You can also visit the link to Validated recurrent need of edge process CPU need’s full calculation graph.
unitary_hourly_need_per_usage_pattern
Dictionary with EdgeUsagePattern as keys and Edge process cpu need unitary hourly need for default edge usage pattern as values, in cpu_core.
Example value: {
EdgeUsagePattern Default edge usage pattern (eef937): 105192 values from 2024-12-31 23:00:00+00:00 to 2036-12-31 23:00:00+00:00 in cpu_core:
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
}
Depends directly on:
- edge process CPU need recurrent need
- edge usage journey hourly nb of edge usage journeys in parallel
- devices country timezone from user data
through the following calculations:
You can also visit the link to edge process CPU need unitary hourly need for Default edge usage pattern’s full calculation graph.
total_hourly_need_across_usage_patterns
Edge process cpu need total hourly need across usage patterns in concurrent * cpu_core.
Example value: 105192 values from 2024-12-31 23:00:00+00:00 to 2036-12-31 23:00:00+00:00 in ·cpu_core:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 999, 2000],
last 10 vals [5000, 5000, 5000, 5000, 5000, 5000, 4000, 3000, 2000, 997]
Depends directly on:
- edge process CPU need unitary hourly need for Default edge usage pattern
- edge usage journey hourly nb of edge usage journeys in parallel
through the following calculations:
You can also visit the link to edge process CPU need total hourly need across usage patterns’s full calculation graph.
fabrication_impact_repartition_weights
Dictionary with RecurrentEdgeProcess as keys and Edge process weight in edge process cpu need impact repartition as values, in concurrent.
Example value: {
RecurrentEdgeProcess edge process (875613): 105192 values from 2024-12-31 23:00:00+00:00 to 2036-12-31 23:00:00+00:00 in M:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0.000999, 0.002],
last 10 vals [0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 0.004, 0.003, 0.002, 0.000997],
}
Depends directly on:
through the following calculations:
You can also visit the link to edge process weight in edge process CPU need impact repartition’s full calculation graph.
fabrication_impact_repartition_weight_sum
Sum of edge process cpu need fabrication impact repartition weights in concurrent.
Example value: 105192 values from 2024-12-31 23:00:00+00:00 to 2036-12-31 23:00:00+00:00 in M:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0.000999, 0.002],
last 10 vals [0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 0.004, 0.003, 0.002, 0.000997]
Depends directly on:
through the following calculations:
You can also visit the link to Sum of edge process CPU need fabrication impact repartition weights’s full calculation graph.
fabrication_impact_repartition
Dictionary with RecurrentEdgeProcess as keys and Edge process cpu need fabrication impact attribution to edge process as values, in concurrent.
Example value: {
RecurrentEdgeProcess edge process (875613): 105192 values from 2024-12-31 23:00:00+00:00 to 2036-12-31 23:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
}
Depends directly on:
- edge process weight in edge process CPU need impact repartition
- Sum of edge process CPU need fabrication impact repartition weights
through the following calculations:
You can also visit the link to edge process CPU need fabrication impact attribution to edge process’s full calculation graph.
usage_impact_repartition_weights
Dictionary with RecurrentEdgeProcess as keys and Edge process weight in edge process cpu need impact repartition as values, in concurrent * gram / kilowatt_hour.
Example value: {
RecurrentEdgeProcess edge process (875613): 105192 values from 2024-12-31 23:00:00+00:00 to 2036-12-31 23:00:00+00:00 in ·g/kWh:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 84900, 170000],
last 10 vals [425000, 425000, 425000, 425000, 425000, 425000, 340000, 255000, 170000, 84700],
}
Depends directly on:
through the following calculations:
You can also visit the link to edge process weight in edge process CPU need impact repartition’s full calculation graph.
usage_impact_repartition_weight_sum
Sum of edge process cpu need usage impact repartition weights in concurrent * gram / kilowatt_hour.
Example value: 105192 values from 2024-12-31 23:00:00+00:00 to 2036-12-31 23:00:00+00:00 in ·g/kWh:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 84900, 170000],
last 10 vals [425000, 425000, 425000, 425000, 425000, 425000, 340000, 255000, 170000, 84700]
Depends directly on:
through the following calculations:
You can also visit the link to Sum of edge process CPU need usage impact repartition weights’s full calculation graph.
usage_impact_repartition
Dictionary with RecurrentEdgeProcess as keys and Edge process cpu need usage impact attribution to edge process as values, in concurrent.
Example value: {
RecurrentEdgeProcess edge process (875613): 105192 values from 2024-12-31 23:00:00+00:00 to 2036-12-31 23:00:00+00:00 in :
first 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
last 10 vals [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
}
Depends directly on:
- edge process weight in edge process CPU need impact repartition
- Sum of edge process CPU need usage impact repartition weights
through the following calculations:
You can also visit the link to edge process CPU need usage impact attribution to edge process’s full calculation graph.