Data compression techniques in SCADA systems - Step-by-Step Execution

Process Flow - Data compression techniques

Start: Raw Data

↓

Choose Compression Method

↓

Apply Compression Algorithm

↓

Compressed Data Output

↓

Store or Transmit Data

↓

Decompression on Receiver Side

↓

Retrieve Original Data

↓

End

The flow shows how raw data is compressed using a chosen method, then stored or sent, and finally decompressed to get the original data back.

Execution Sample

SCADA systems

compressed_data = compress(data)
transmit(compressed_data)
original_data = decompress(compressed_data)

This simple sequence compresses data, sends it, then decompresses it back to original.

Process Table

Step	Action	Input Data Size (bytes)	Output Data Size (bytes)	Result/Note
1	Start with raw data	1000	1000	Raw data ready for compression
2	Apply compression algorithm	1000	400	Data compressed to 40% of original size
3	Transmit compressed data	400	400	Compressed data sent over network
4	Receive compressed data	400	400	Data received intact
5	Decompress data	400	1000	Original data restored after decompression
6	End process	1000	1000	Data ready for use

💡 Process ends after decompression restores original data size

Status Tracker

Variable	Start	After Compression	After Transmission	After Decompression	Final
data_size	1000	400	400	1000	1000
data_state	raw	compressed	compressed	decompressed	original

Key Moments - 2 Insights

Why does the data size decrease after compression but return to original after decompression?

Compression reduces data size by encoding it efficiently (see step 2 in execution_table). Decompression reverses this to restore the original data size (step 5).

Is the compressed data usable before decompression?

No, compressed data is not in original form and must be decompressed before use (steps 3 and 5 show transmission and decompression).

Visual Quiz - 3 Questions

Look at the execution table, what is the data size after compression?

A 600 bytes

B 1000 bytes

C 400 bytes

D 200 bytes

💡 Hint

Check the 'Output Data Size' column at step 2 in the execution_table

At which step does the data return to its original size?

A Step 5

B Step 3

C Step 2

D Step 4

💡 Hint

Look at the 'Output Data Size' column and find when it goes back to 1000 bytes

If the compression algorithm was less efficient and compressed data to 600 bytes, how would step 2's output change?

A Input Data Size would change to 600 bytes

B Output Data Size would be 600 bytes

C Output Data Size would remain 400 bytes

D Data size would increase to 1200 bytes

💡 Hint

Compression output size depends on algorithm efficiency shown in step 2's output

Concept Snapshot

Data compression reduces data size for storage or transmission.
Choose a compression method, apply it to raw data.
Send or store compressed data.
Decompress to restore original data.
Compression saves space and bandwidth.
Decompression must perfectly restore data.

Full Transcript

Data compression techniques involve taking raw data and applying a method to reduce its size. This smaller data is easier to store or send over networks. Later, the compressed data is decompressed to get back the original data exactly. The process starts with raw data, then compression reduces size, followed by transmission or storage. Finally, decompression restores the data. This helps save space and speed up communication in SCADA systems.

Practice

1. What is the main purpose of data compression in SCADA systems?

easy

A. To reduce the size of data for easier storage and faster transfer

B. To increase the size of data for better security

C. To convert data into a different format for display

D. To delete unnecessary data permanently

Solution

1. Step 1: Understand data compression purpose

   Data compression reduces the size of data to save space and speed up transfer.

2. Step 2: Apply this to SCADA systems

   In SCADA, smaller data means faster communication and less storage needed.

3. Final Answer:

   To reduce the size of data for easier storage and faster transfer -> Option A

4. Quick Check:

   Compression = smaller data size [OK]

Hint: Compression makes data smaller to save space and time [OK]

Common Mistakes:

• Confusing compression with encryption
• Thinking compression deletes data
• Believing compression changes data meaning

2. Which of the following is the correct syntax to compress data using a function named compress in a SCADA script?

easy

A. compressed_data = compress(data)

B. compressed_data = compress data

C. compressed_data <- compress(data)

D. compressed_data = compress[data]

Solution

1. Step 1: Identify correct function call syntax

   Functions are called with parentheses enclosing arguments, like compress(data).

2. Step 2: Check each option

   compressed_data = compress(data) uses correct syntax with parentheses and assignment.

3. Final Answer:

   compressed_data = compress(data) -> Option A

4. Quick Check:

   Function call syntax = parentheses [OK]

Hint: Use parentheses to call functions with arguments [OK]

Common Mistakes:

• Omitting parentheses in function calls
• Using wrong assignment operators
• Using brackets instead of parentheses

3. Given the following SCADA script snippet:

data = "sensor_reading_12345"
compressed = compress(data)
decompressed = decompress(compressed)
print(decompressed)

What will be the output?

medium

A. compressed data bytes

B. Error: decompress function not found

C. sensor_reading_12345

D. sensor_reading

Solution

1. Step 1: Understand compression and decompression

   compress() shrinks data, decompress() restores it to original form.

2. Step 2: Follow the script flow

   Data is compressed then decompressed, so print shows original data.

3. Final Answer:

   sensor_reading_12345 -> Option C

4. Quick Check:

   Decompress(compress(data)) = original data [OK]

Hint: Decompress reverses compress, output original data [OK]

Common Mistakes:

• Thinking print shows compressed bytes
• Assuming decompress changes data
• Ignoring function order

4. A SCADA script uses compressed = compress(data) but later decompressed = decompress(data) is called instead of decompress(compressed). What is the likely problem?

medium

A. Data will be compressed twice

B. Compression will fail because decompress is called too early

C. No problem, decompress can use original data

D. Decompression will fail or give wrong data because wrong variable is used

Solution

1. Step 1: Identify variable usage error

   Decompress must use compressed data, not original data variable.

2. Step 2: Understand effect of wrong variable

   Using original data in decompress causes failure or incorrect output.

3. Final Answer:

   Decompression will fail or give wrong data because wrong variable is used -> Option D

4. Quick Check:

   Decompress(compressed) needed, not decompress(data) [OK]

Hint: Always decompress the compressed variable [OK]

Common Mistakes:

• Passing original data to decompress
• Assuming decompress auto-detects input
• Mixing variable names

5. You need to compress SCADA data but want to keep it quickly accessible for real-time monitoring. Which compression technique is best?

hard

A. No compression to avoid delay

B. Lossless compression for exact data recovery

C. Lossy compression to reduce size drastically

D. Encrypt data instead of compressing

Solution

1. Step 1: Understand real-time monitoring needs

   Real-time needs exact data quickly without loss.

2. Step 2: Choose compression type

   Lossless compression keeps data exact and fast to decompress.

3. Step 3: Evaluate other options

   Lossy loses data, no compression wastes space, encryption is different.

4. Final Answer:

   Lossless compression for exact data recovery -> Option B

5. Quick Check:

   Real-time + exact data = lossless compression [OK]

Hint: Use lossless compression for exact, fast data access [OK]

Common Mistakes:

• Choosing lossy compression for critical data
• Skipping compression to save time
• Confusing encryption with compression