
1) Internet System Handbook by Marshall Rose and Daniel Lynch - Overview of The Internet from the 1990s. Very valuable to get the big picture.
2) An Engineering Approach to Computer Networking: ATM Networks, the Internet, and the Telephone Network by S. Keshav - Excellent textbook which covers three different types of Networks.
3) The TCP/IP Guide by Charles Kozierok. - Reference: http://www.tcpipguide.com/ Start at "Networking Fundamentals" : http://www.tcpipguide.com/free/t_NetworkingFundamentals.htm
4) Mathematical Foundations of Computer Networking by S. Keshav - https://news.ycombinator.com/item?id=30964707
The same technique with necessary modifications is also applicable to figuring out whether it is worthwhile to completely Read a Book. These days Books have so much unnecessary filler that a lot can be skipped with no loss of information/knowledge.
PS: The same author has also written two great books on Computer Networking; 1) An Engineering Approach to Computer Networking 2) Mathematical Foundations of Computer Networking
Nevertheless, you will find the following books useful;
* An Engineering Approach to Computer Networking: ATM Networks, the Internet, and the Telephone Network by S. Keshav.
* Mathematical Foundations of Computer Networking by S. Keshav.
* The TCP/IP Guide: A Comprehensive, Illustrated Internet Protocols Reference by Charles Kozlerok.
* The All-New Switch Book: The Complete Guide to LAN Switching Technology by Seifert and Edwards.
* Wireless Networking: Understanding Internetworking Challenges by Burbank et al.
* An Engineering Approach to Computer Networking: ATM Networks, the Internet, and the Telephone Network.
* Mathematical Foundations of Computer Networking
Thought, if you're interested there are some other pretty good intro probability courses online:
Math and Probability for Life Sciences (UCLA): http://www.academicearth.org/courses/math-and-proability-for... The course doesn't cover as much material, but is still fairly detailed.
CS 798 Mathematical Foundations of Computer Networking, Fall 2008, University of Waterloo: http://blizzard.cs.uwaterloo.ca/keshav/mediawiki-1.4.7/index... This is a really great course that covers a broad set of topics, and is some what similar in structure to the Stat 110 course. Beyond the basics of probability, you also can learn a good deal about statistical inference and stochastic processes.
My interest is to study the J language in an application setting but could only find this book in paper copy form. I am quite surprised as to why the AI/ML community has not discovered the J language since at first glance it seems it would be a good fit.