Answer:
It we were asked to develop a new data compression tool, it is recommended to use Huffman coding since it is easy to implement and it is widely used.
Explanation:
The pros and the cons of Huffman coding
Huffman coding is one of the most simple compressing encoding schemes and can be implemented easily and efficiently. It also has the advantage of not being patented like other methods (e.g. arithmetic codingfor example) which however are superior to Huffman coding in terms of resulting code length.
One thing not mentioned so far shall not be kept secret however: to decode our 96 bit of “brief wit” the potential receiver of the bit sequence does need the codes for all letters! In fact he doesn’t even know which letters are encoded at all! Adding this information, which is also called the “Huffman table” might use up more space than the original uncompressed sentence!
However: for longer texts the savings outweigh the added Huffman table length. One can also agree on a Huffman table to use that isn’t optimized for the exact text to be transmitted but is good in general. In the English language for example the letters “e” and “t” occur most often while “q” and “z” make up the least part of an average text and one can agree on one Huffman table to use that on average produces a good (=short) result. Once agreed upon it doesn’t have to be transmitted with every encoded text again.
One last thing to remember is that Huffman coding is not restricted to letters and text: it can be used for just any symbols, numbers or “abstract things” that can be assigned a bit sequence to. As such Huffman coding plays an important role in other compression algorithms like JPG compression for photos and MP3 for audio files.
The pros and the cons of Lempel-Ziv-Welch
The size of files usually increases to a great extent when it includes lots of repetitive data or monochrome images. LZW compression is the best technique for reducing the size of files containing more repetitive data. LZW compression is fast and simple to apply. Since this is a lossless compression technique, none of the contents in the file are lost during or after compression. The decompression algorithm always follows the compression algorithm. LZW algorithm is efficient because it does not need to pass the string table to the decompression code. The table can be recreated as it was during compression, using the input stream as data. This avoids insertion of large string translation table with the compression data.
This site is only for education related questions. You should only answer or ask questions. That's what we are here for. Whoever is reading this answer, please spread it to stop people from zooming, hurting others, or just posting non-related to education questions. Thank you.
Explanation:
1. How many computers do you want to connect or how big the network should be?
This would tell us what kind of a network need to be built. It can be LAN/MAN/WAN
2. The location where network needs to be built?
We have to check the geographic condition too before creating a network
3. What is the budget?
Based on the budget only, we can decide the wires to be used if require we can negotiate the budget so that we can create effective network
4. Will I get an additional resources to work?
This is essential to estimate the time that is required to complete the task.
5. When the project needs to be completed?
This is crucial because a business might be planned thereafter.
Answer:
The American Registry for Internet Numbers ARIN
Explanation:
The American Registry for Internet Numbers (ARIN) is a not for profit organization that serves as the administrator and distributor of Internet numeric resources such as IP addresses (IPv4 and IPv6) ASN for the United States, Canada, as well as North Atlantic and Caribbean islands
There are four other Regional Internet Registry including APNIC, RIPE NCC, LACNIC and AFRINIC.
