Skip to main content

Explain CRC code generation with example.

Decoding the Mystery of CRC Code Generation in Computer Networks

Understanding Cyclic Redundancy Check (CRC)

  • CRC is an error-detecting code used in data transmission and storage.
  • It ensures data integrity by adding a checksum to the data.
  • The checksum is generated using polynomial division.
  • Detects burst errors effectively.

The CRC Generation Process

  • Choose a generator polynomial (e.g., x⁴ + x + 1). This polynomial is predetermined and agreed upon by sender and receiver.
  • Represent the data as a polynomial. For example, the binary data 101100 becomes x⁵ + x³ + x².
  • Append zeros to the data polynomial equal to the degree of the generator polynomial (in this case, 4 zeros: 1011000000).
  • Perform polynomial long division of the augmented data polynomial by the generator polynomial.
  • The remainder from the division is the CRC checksum.
  • Append this remainder to the original data to create the transmitted data.

Example: CRC Calculation

  • Data: 101100
  • Generator Polynomial: x⁴ + x + 1 (10011 in binary)
  • Augmented Data: 1011000000
  • Polynomial Division: (using modulo-2 arithmetic, where addition and subtraction are equivalent to XOR) will result in a remainder. The steps will involve XORing according to the polynomial division rules.
  • Remainder (CRC Checksum): The remainder obtained from the division (e.g. 100). This depends on the chosen polynomial and the data.
  • Transmitted Data: Original data + CRC (e.g., 101100100).

CRC Verification at the Receiver

  • The receiver performs the same polynomial division on the received data (including the CRC) using the same generator polynomial.
  • If the remainder is zero, the data is considered error-free.
  • If the remainder is non-zero, an error occurred during transmission.
Labels:

Popular Posts

Explain Data collection methods and Techniques in UX Evaluation.

UX Evaluation: Agile Data Collection Methods & Techniques Qualitative Data Collection Methods User Interviews: Structured, semi-structured, or unstructured. Focus Groups: Moderated discussions with small groups. Contextual Inquiry: Observing users in their natural environment. Card Sorting: Organizing information architecture. Diary Studies: Users document their experiences over time. Think Aloud Protocols: Users verbalize their thoughts while using a product. Usability Testing Observations: Direct observation of user interactions. Heuristic Evaluation: Expert review against usability principles. Cognitive Walkthroughs: Step-by-step analysis of user tasks. Quantitative Data Collection Methods A/B Testing: Comparing two versions of a design. Eye Tracking: Measuring visual attention. Surveys: Gathering user feedback through questionnaires. Analytics: Tracking website or app usage data (e.g., Google Analytics). System Usability Scale (SUS): Standardized questionn...
Read more

What is Stegnography and list two examples.

Unveiling the Secrets: Understanding Steganography in Cybersecurity What is Steganography? Steganography is the art and science of hiding information within other information. It focuses on concealing the very existence of a secret message. Unlike cryptography (which scrambles messages), steganography aims to make hidden data undetectable. It's a powerful tool for covert communication and data exfiltration. Often used in conjunction with cryptography for enhanced security. Steganography Examples in Cybersecurity Hiding data within an image file: Modifying least significant bits (LSBs) of image pixels to embed secret data. The changes are usually imperceptible to the human eye. Embedding data within audio files: Similar to images, small modifications to audio waveforms can hide information without noticeably altering the sound quality.
Read more

What is LZW compression? Explain with example.

Decoding the Magic of LZW Compression: A Data Compression Deep Dive What is LZW Compression? Lempel-Ziv-Welch (LZW) is a lossless data compression algorithm. It works by replacing repeating sequences of data with shorter codes. It's widely used in GIF image format and other applications. Highly effective for data with repeating patterns. How LZW Compression Works: A Step-by-Step Guide Starts with a dictionary containing single characters. Reads the input data character by character. Concatenates characters to form strings. When a string is not found, it's added to the dictionary with a new code. The code for the longest matching string is written to the output. This process continues until the entire input is processed. LZW Compression Example: Initial Dictionary: {'A': 1, 'B': 2, 'C': 3} Input String: "ABABCABABCACC" Processing: - 'A' is encoded as 1. - 'AB' is encoded as 4 (added to diction...
Read more

Explain different compression techniques with example.

Mastering Data Compression: A Comprehensive Guide Lossless Compression Techniques Run-Length Encoding (RLE):  Represents consecutive repeating characters with a single count and character. Example: "AAABBBCC" becomes "3A3B2C". Huffman Coding: Assigns shorter codes to frequently occurring symbols and longer codes to less frequent ones. Example: In text, "e" gets a shorter code than "z". Lempel-Ziv (LZ77 & LZ78):  Identifies repeating patterns and replaces them with pointers to earlier occurrences. LZ77 uses a sliding window, LZ78 uses a dictionary. Arithmetic Coding: Represents data as a single fractional number, encoding probability. More efficient than Huffman for many cases. Lossy Compression Techniques JPEG (Joint Photographic Experts Group): Discards some image data, particularly high-frequency components, which are less noticeable to the human eye. MPEG (Moving Picture Experts Group): Uses techniques like motion compen...
Read more

what is type conversion in python? Explain with the suitable example.

Data Compression: Mastering Type Conversion in Python What is Type Conversion? Type conversion, also known as type casting, is the process of changing a variable's data type from one to another. Python supports both implicit (automatic) and explicit (manual) type conversion. Implicit Type Conversion Python automatically converts data types in certain situations to prevent errors. Example: Adding an integer to a float results in a float. Explicit Type Conversion We use built-in functions like `int()`, `float()`, `str()`, `bool()` etc. to explicitly change data types. Example: Converting a string "10" to an integer using `int("10")`. Example: Data Compression Context Imagine you're storing compressed file sizes (originally floats) in a database designed for integers. Explicit type conversion (using `int()`) would truncate the decimal part, losing precision but saving space. This is a type of lossy compression. Converting from a larger data t...
Read more