Apparatus and methods for adaptive data compression

A method for computer networking, comprising:

• receiving, by a computing device, an indication for transmitting a file to a server;
• gathering, by the computing device, a plurality of current impact factors on a duration for transmitting the file to the server and a user preference for performance or cost for transmitting the file to the server;
• and
• determining, by the computing device, whether to compress the file before transmitting the file to the server based at least in part on the plurality of current impact factors and the user preference, the determining including looking up a first total time with compression for transmitting the file and a second total time without compression for transmitting the file from a lookup table, the lookup table previously built using a random forest regression machine learning process based on at least one of a plurality of previously gathered impact factors, and
• wherein the user preference comprises one of a performance-centric policy that prioritizes reduced transmission time, a cost-centric policy that prioritizes reduced data usage, or a balanced policy that weighs transmission time and data usage where at least one weight is configurable.

A method for computer networking, comprising:

• receiving, by a module operating on a client or a server, an indication from the client for transmitting a file to the server;
• gathering, by the module, a plurality of current impact factors on a duration for transmitting the file from the client to the server and a user preference for performance or cost for transmitting the file from the client to the server;
• determining, by the module, whether the client is to compress the file before transmitting the file from the client to the server based at least in part on the plurality of current impact factors and the user preference, the determining comprising looking up a first total time with compression for transmitting the file and a second total time without compression for transmitting the file from a lookup table previously constructed using a random forest regression machine learning process, the machine learning process to construct the lookup table based on a plurality of previously gathered impact factors;
• and
• sending to the client, by the module, a result of the determination of whether the client is to compress the file before transmitting the file from the client to the server, and
• wherein the user preference comprises one of a performance-centric policy that prioritizes reduced transmission time, a cost-centric policy that prioritizes reduced data usage, or a balanced policy that weighs transmission time and data usage where at least one weight is configurable.