Spatio-Temporal Characterization(STC) of Network Traffic Test phase, srs, design phase and source code final deliverable

Spatio-Temporal Characterization(STC) of Network Traffic Test phase, srs, design phase and source code final deliverable

Project Domain / Category
Computer Networks

Abstract / Introduction
The expertise of community site visitors conduct is essential for traffic engineering duties which include link potential planning, traffic classification, and anomaly detection. Traffic characterization is normally addressed via statistical analysis of character link(s) and community-extensive site visitors volume homes including counts of bytes and packets in addition to through studying the distributional behavior of specific packet header fields. This project pursuits to develop a software program solution to signify community site visitors to pick out the spatio temporal functions. The community traffic captures may be downloaded from the data source given in tools section. Any different information supply also can be used.

Functional Requirements:
Students might be required to look into the spatio temporal capabilities of community site visitors and expand the ideal software solution to investigate the traffic from records resources given in this document.
1. The answer should be capable of read the pcap documents and extract the header records which includes timestamps , source/destination addresses, TCP port, Packet Size, Type of Packet and other relevant records.
2. It should be able to save the extracted header facts in a persistent database or textual content record together with csv.
Three. The solution need to allow the customers to cut up the big length pcap files into smaller length based totally on report length and time length.
Four. It need to be able to discover pinnacle flows for person site visitors and community manipulate plane site visitors based totally on followings
a. Source and destination with TCP port
b. Software kind
c. Data costs
d. Session length
five. It ought to be capable of measure the Flow Similarity across each day/weekly traffic captures.
6. It ought to be capable of approximate facts price probability distribution for wonderful flows for every day visitors
7. It ought to be capable of approximate interpacket postpone distribution on daily traffic
8. The consequences should consist of the analysis of at the least one-week traffic captures of fifteen mins from the respectable net site visitors assets.

Tools:
Python/Java, C/C++ (other programming languages can also be used.), And IDE of choice Data Source : http://mawi.Extensive.Ad.Jp/mawi/samplepoint-G/2020/

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