Read "Streaming Systems" 1&2, Streaming 101 Read "F1, a distributed SQL database that scales" Read "Zanzibar, Google’s Consistent, Global Authorization System" Read "Spanner, Google's Globally-Distributed Database" Read "Designing Data-intensive applications" 12, The Future of Data Systems IOS development with Swift Read "Designing Data-intensive applications" 10&11, Batch and Stream Processing Read "Designing Data-intensive applications" 9, Consistency and Consensus Read "Designing Data-intensive applications" 8, Distributed System Troubles Read "Designing Data-intensive applications" 7, Transactions Read "Designing Data-intensive applications" 6, Partitioning Read "Designing Data-intensive applications" 5, Replication Read "Designing Data-intensive applications" 3&4, Storage, Retrieval, Encoding Read "Designing Data-intensive applications" 1&2, Foundation of Data Systems Three cases of binary search TAMU Operating System 2 Memory Management TAMU Operating System 1 Introduction Overview in cloud computing 2 TAMU Operating System 7 Virtualization TAMU Operating System 6 File System TAMU Operating System 5 I/O and Disk Management TAMU Operating System 4 Synchronization TAMU Operating System 3 Concurrency and Threading TAMU Computer Networks 5 Data Link Layer TAMU Computer Networks 4 Network Layer TAMU Computer Networks 3 Transport Layer TAMU Computer Networks 2 Application Layer TAMU Computer Networks 1 Introduction Overview in distributed systems and cloud computing 1 A well-optimized Union-Find implementation, in Java A heap implementation supporting deletion TAMU Advanced Algorithms 3, Maximum Bandwidth Path (Dijkstra, MST, Linear) TAMU Advanced Algorithms 2, B+ tree and Segment Intersection TAMU Advanced Algorithms 1, BST, 2-3 Tree and Heap TAMU AI, Searching problems Factorization Machine and Field-aware Factorization Machine for CTR prediction TAMU Neural Network 10 Information-Theoretic Models TAMU Neural Network 9 Principal Component Analysis TAMU Neural Network 8 Neurodynamics TAMU Neural Network 7 Self-Organizing Maps TAMU Neural Network 6 Deep Learning Overview TAMU Neural Network 5 Radial-Basis Function Networks TAMU Neural Network 4 Multi-Layer Perceptrons TAMU Neural Network 3 Single-Layer Perceptrons Princeton Algorithms P1W6 Hash Tables & Symbol Table Applications Stanford ML 11 Application Example Photo OCR Stanford ML 10 Large Scale Machine Learning Stanford ML 9 Anomaly Detection and Recommender Systems Stanford ML 8 Clustering & Principal Component Analysis Princeton Algorithms P1W5 Balanced Search Trees TAMU Neural Network 2 Learning Processes TAMU Neural Network 1 Introduction Stanford ML 7 Support Vector Machine Stanford ML 6 Evaluate Algorithms Princeton Algorithms P1W4 Priority Queues and Symbol Tables Stanford ML 5 Neural Networks Learning Princeton Algorithms P1W3 Mergesort and Quicksort Stanford ML 4 Neural Networks Basics Princeton Algorithms P1W2 Stack and Queue, Basic Sorts Stanford ML 3 Classification Problems Stanford ML 2 Multivariate Regression and Normal Equation Princeton Algorithms P1W1 Union and Find Stanford ML 1 Introduction and Parameter Learning

TAMU Computer Networks 1 Introduction




Parts are identical to Berkeley sockets in Unix.


  1. Should be done before other winsock calls.
  2. Once per program.
#include <Winsock2.h>
WSADATA wsaData;
WORD wVersionRequested = MAKEWORD(2,2);
if (WSAStartup(wVersionRequested, &wsaData) != 0)
printf("WSAStartup error %d\n", WSAGetLastError());


Steps for TCP:

  • Open a socket
  • Determine the IP address of the server in URL
    • Check if host is IP address, inet_addr(host)
    • If not, do DNS lookup, gethostbyname(host)
  • Initiate connection with the server, IP and port
    • Convert port to network byte order
  • Send request
  • Receive response
    • Until receive 0 byte.
  • Close socket

Note that all numbers must be in network byte order (MSB first). Convert two-way using

  • host to network, htons(), htonl()
  • network to host, ntohs(), ntohl()




  • Edge: Hosts (end systems)
  • Core
    • Routers, forward packets
    • Communication links

Internet standards:

  • IETF, Internet Engineering Task Force
  • RFC: Request for comments

The architecture is roughly hierarchical

  • Center: tier-1 ISPs
    • as backbone of the Internet
    • interconnect at public NAPs (network access points)
    • Level3, Sprint, AT&T, Verizon
  • tier-2
    • customers of tier-1
  • tier-3 and local


4 sources:

  1. Router processing delay
    • check bit error
    • determine output link
    • place packet in buffer
  2. queuing delay
    • at output link
    • depends on congestion level
  3. Transmission delay
    • fire packet out (, packet length, link rate)
  4. Propagation delay

queuing delay increase exponentially as traffic rate approaches link bandwidth


  • traceroute
  • tracert in windows
  1. Send 3 packets for each router along the path to destination.
  2. Routers return responses to the sender.
  3. Sender times intervals.

Packet loss

  1. Queues have finite capacity.
  2. Drop-tail queuing at routers

Protocol Stack

  1. Application
    • interact with users
    • message
  2. Transport
    • inter-process data transfer
    • TCP, UDP
    • segment
  3. Network
    • routing of datagrams from source to destination host
    • IP, routing protocols
    • datagram
  4. Link
    • data transfer between neighboring network elements
    • Ethernet
    • frame
  5. Physical
    • bits on wire


This is my class notes while taking CSCE 612 at TAMU. Credit to the instructor Dr. Loguinov.

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