RecurrentEdgeStorageNeed

Params

name

A human readable description of the object.

edge_component

An instance of EdgeStorage.

recurrent_need

Storage need recurrent need, in typical week of hourly timeseries data, starting on Monday at midnight.

For example, 168 values in MB stored: first 10 vals [50, 50, 50, 50, 50, 50, 50, 50, 50, 50], last 10 vals [-50, -50, -50, -50, -50, -50, -50, -50, -50, -50]

Backwards links

• RecurrentEdgeDeviceNeed

Calculated attributes

recurrent_need_validation

Example value: 168 values in MB stored:
first 10 vals [50, 50, 50, 50, 50, 50, 50, 50, 50, 50],
last 10 vals [-50, -50, -50, -50, -50, -50, -50, -50, -50, -50]

Depends directly on:

• Storage need recurrent need

through the following calculations:

You can also visit the link to Validated recurrent need of Storage need’s full calculation graph.

unitary_hourly_need_per_usage_pattern

Dictionary with EdgeUsagePattern as keys and Storage need unitary hourly need for default edge usage pattern as values, in megabyte_stored.

Example value: {
EdgeUsagePattern Default edge usage pattern (fa81f1): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in MB stored:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
last 10 vals [50, 50, 50, 50, 50, 50, 50, 50, 50, 50],
}

Depends directly on:

• Storage 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 Storage need unitary hourly need for Default edge usage pattern’s full calculation graph.

cumulative_unitary_storage_need_per_usage_pattern

Dictionary with EdgeUsagePattern as keys and Storage need cumulative unitary storage need for default edge usage pattern as values, in terabyte_stored.

Example value: {
EdgeUsagePattern Default edge usage pattern (fa81f1): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in GB stored:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
last 10 vals [3.15, 3.2, 3.25, 3.3, 3.35, 3.4, 3.45, 3.5, 3.55, 3.6],
}

Depends directly on:

• Storage need unitary hourly need for Default edge usage pattern

through the following calculations:

You can also visit the link to Storage need cumulative unitary storage need for Default edge usage pattern’s full calculation graph.

total_hourly_need_across_usage_patterns

Storage need total hourly need across usage patterns in concurrent * terabyte_stored.

Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in TB stored:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
last 10 vals [15.7, 16, 16.2, 16.5, 16.7, 13.6, 10.3, 6.99, 3.54, 0]

Depends directly on:

• Storage need cumulative unitary storage 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 Storage need total hourly need across usage patterns’s full calculation graph.

fabrication_impact_repartition_weights

Dictionary with RecurrentEdgeDeviceNeed as keys and Custom edge device need weight in storage need impact repartition as values, in concurrent.

Example value: {
RecurrentEdgeDeviceNeed custom edge device need (a3d44e): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in M:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000999, 0.002, 0.003],
last 10 vals [0.005, 0.005, 0.005, 0.005, 0.005, 0.004, 0.003, 0.002, 0.000997, 0],
}

Depends directly on:

• edge function weight in custom edge device need impact repartition

through the following calculations:

You can also visit the link to custom edge device need weight in Storage need impact repartition’s full calculation graph.

fabrication_impact_repartition_weight_sum

Sum of storage need fabrication impact repartition weights in concurrent.

Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in M:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 0.000999, 0.002, 0.003],
last 10 vals [0.005, 0.005, 0.005, 0.005, 0.005, 0.004, 0.003, 0.002, 0.000997, 0]

Depends directly on:

• custom edge device need weight in Storage need impact repartition

through the following calculations:

You can also visit the link to Sum of Storage need fabrication impact repartition weights’s full calculation graph.

fabrication_impact_repartition

Dictionary with RecurrentEdgeDeviceNeed as keys and Storage need fabrication impact attribution to custom edge device need as values, in concurrent.

Example value: {
RecurrentEdgeDeviceNeed custom edge device need (a3d44e): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+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:

• custom edge device need weight in Storage need impact repartition
• Sum of Storage need fabrication impact repartition weights

through the following calculations:

You can also visit the link to Storage need fabrication impact attribution to custom edge device need’s full calculation graph.

usage_impact_repartition_weights

Dictionary with RecurrentEdgeDeviceNeed as keys and Custom edge device need weight in storage need impact repartition as values, in concurrent * gram / kilowatt_hour.

Example value: {
RecurrentEdgeDeviceNeed custom edge device need (a3d44e): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in ·g/kWh:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 84900, 170000, 255000],
last 10 vals [425000, 425000, 425000, 425000, 425000, 340000, 255000, 170000, 84700, 0],
}

Depends directly on:

• edge function weight in custom edge device need impact repartition

through the following calculations:

You can also visit the link to custom edge device need weight in Storage need impact repartition’s full calculation graph.

usage_impact_repartition_weight_sum

Sum of storage need usage impact repartition weights in concurrent * gram / kilowatt_hour.

Example value: 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+00:00 in ·g/kWh:
first 10 vals [0, 0, 0, 0, 0, 0, 0, 84900, 170000, 255000],
last 10 vals [425000, 425000, 425000, 425000, 425000, 340000, 255000, 170000, 84700, 0]

Depends directly on:

• custom edge device need weight in Storage need impact repartition

through the following calculations:

You can also visit the link to Sum of Storage need usage impact repartition weights’s full calculation graph.

usage_impact_repartition

Dictionary with RecurrentEdgeDeviceNeed as keys and Storage need usage impact attribution to custom edge device need as values, in concurrent.

Example value: {
RecurrentEdgeDeviceNeed custom edge device need (a3d44e): 105192 values from 2025-01-01 00:00:00+00:00 to 2037-01-01 00:00:00+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:

• custom edge device need weight in Storage need impact repartition
• Sum of Storage need usage impact repartition weights

through the following calculations:

You can also visit the link to Storage need usage impact attribution to custom edge device need’s full calculation graph.