Timestamp and data synchronization in SCADA systems - Step-by-Step Execution

Process Flow - Timestamp and data synchronization

Data Generated at Sensor

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Timestamp Added Locally

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Data Sent to Central System

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Central System Receives Data

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Compare Timestamp with System Clock

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Adjust Data Time or Flag

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Store or Process Synchronized Data

Data is created at sensors, timestamped locally, sent to a central system, where timestamps are checked and synchronized before storing or processing.

Execution Sample

SCADA systems

sensor_time = get_local_time()
data = read_sensor()
data_packet = {"timestamp": sensor_time, "value": data}
send_to_central(data_packet)
central_time = get_central_time()
if abs(central_time - data_packet["timestamp"]) > threshold:
    flag_sync_issue()

This code reads sensor data, timestamps it, sends it to central system, then checks if timestamp difference exceeds threshold to flag sync issues.

Process Table

Step	Action	Local Timestamp	Central Timestamp	Time Difference (s)	Sync Status
1	Sensor reads data	2024-06-01 10:00:00			Pending
2	Timestamp added locally	2024-06-01 10:00:00			Pending
3	Data sent to central	2024-06-01 10:00:00			Pending
4	Central system receives data	2024-06-01 10:00:00	2024-06-01 10:00:02	2	Check Needed
5	Compare timestamps	2024-06-01 10:00:00	2024-06-01 10:00:02	2	Threshold Exceeded
6	Flag synchronization issue	2024-06-01 10:00:00	2024-06-01 10:00:02	2	Issue Flagged
7	Store data with flag	2024-06-01 10:00:00	2024-06-01 10:00:02	2	Stored with Warning

💡 Execution stops after data is stored with synchronization issue flagged due to timestamp difference exceeding threshold.

Status Tracker

Variable	Start	After Step 1	After Step 2	After Step 4	After Step 6	Final
sensor_time	null	2024-06-01 10:00:00	2024-06-01 10:00:00	2024-06-01 10:00:00	2024-06-01 10:00:00	2024-06-01 10:00:00
central_time	null	null	null	2024-06-01 10:00:02	2024-06-01 10:00:02	2024-06-01 10:00:02
time_difference	null	null	null	2	2	2
sync_status	Pending	Pending	Pending	Check Needed	Issue Flagged	Stored with Warning

Key Moments - 3 Insights

Why is the central timestamp different from the sensor timestamp?

The central system clock may not be perfectly synchronized with the sensor's local clock, causing a time difference as shown in step 4 of the execution table.

What happens if the time difference is within the threshold?

If the difference is small, the data is accepted without flagging, but here in step 5 the difference exceeds the threshold, so a sync issue is flagged.

Why do we store data even if synchronization issues are flagged?

Storing data with a warning allows later review or correction, ensuring no data loss while highlighting potential timing problems, as shown in step 7.

Visual Quiz - 3 Questions

Look at the execution table, what is the time difference at step 5?

A 2 seconds

B 0 seconds

C 5 seconds

D Not calculated yet

💡 Hint

Check the 'Time Difference (s)' column at step 5 in the execution table.

At which step is the synchronization issue flagged?

A Step 4

B Step 6

C Step 2

D Step 7

💡 Hint

Look at the 'Sync Status' column to find when 'Issue Flagged' appears.

If the central time was 10:00:01 instead of 10:00:02, what would happen?

A Sync issue would still be flagged

B Data would be stored without warning

C Data would be rejected

D Timestamp would be changed to central time

💡 Hint

Consider the threshold and compare the time difference in the variable_tracker.

Concept Snapshot

Timestamp and data synchronization:
- Sensors add local timestamps to data
- Data sent to central system
- Central system compares timestamps
- If difference > threshold, flag sync issue
- Store data with or without warning
- Ensures data timing consistency in SCADA

Full Transcript

In SCADA systems, data from sensors is timestamped locally when generated. This timestamp travels with the data to the central system. The central system compares the sensor timestamp with its own clock. If the difference is larger than a set threshold, it flags a synchronization issue but still stores the data with a warning. This process helps keep data timing consistent and highlights potential clock mismatches for later review.