[SOLVED] : COMP SCI 4094/4194/7094 Distributed Databases and Data Mining Assignment 1

COMP SCI 4094/4194/7094 Distributed Databases and Data Mining Assignment 1
Important Notes
Handins:
DUE: 23:30 Friday, 15th Sept, 2017
The deadline for submission of your assignment is 23:30 Friday, 15th Sept, 2017.
You must do this assignment individually and make individual submissions.
Your program should be coded in C++ and pass test runs on the two test files. The sample input and output files are downloadable from the track of Assignment 1 at MyUni (https://myuni.adelaide.edu.au/courses/25366/assignments/40064).
You need to use svn to upload and run your source code in the web submission system following Web-submission instructions stated at the end of this sheet. You should attach your name and student number in your submission.
Late submissions will attract a penalty: the maximum mark you can obtain will be reduced by 25% per day (or part thereof) past the due date.
Marking scheme:
10 marks for testing on 2 standard tests: 5 marks per test.
4 marks for the code structure.
1 mark for the comments.
Note: If it is found your code did not implement the required computation tasks in this assignment, you will receive zero mark regardless of the correctness of test output.
If you have any questions, please send them to the student discussion forum. This way you can all help each other and everyone gets to see the answers.
The assignment
In the past decade, network management has been benefited from traffic classification to clas- sify the raw internet traffic packets to different applications, such as http, smtp, dns, msn and ftp. For a given traffic pack, the attributes we may obtain include source address, source port, destination address, destination port and packet length. Assume that the raw traffic data are distributed over a set of servers at which users submit their applications (queries) as needed. It is observed that some attributes are often accessed together by user applications and hence show a high affinity. The affinity aff(Ai,Aj) between attributes Ai and Aj is defined by Cosine-based similarity (https://en.wikipedia.org/wiki/Cosine_similarity) and computed by the fol- lowing equation, where n is the number of attributes, m is the number of sites, and Aik is the number of times Attribute Ai is accessed by Query qk from all sites.
nk=1 Aik Ajk
aff(Ai,Aj)= nk=1(Aik)2 nk=1(Ajk)2 (1)

m
Aik =use(qk,Ai) accj(qk) (2)
j=1
In this assignment, to localise data accesses of users applications, you are required to code a C++ program that partitions the given traffic flow attributes according to user applications such that attributes of a high affinity are placed within the same group. Your code should round off the decimals in the results of all divisions to four digits only.
Hint: You should apply the appropriate algorithms learned from the first part of this course distributed databases.
Example
You are given the following inputs: Attributes (Ai):
Queries (qi) and their access frequencies at different sites (Si):
q1 q2 q3 q4
Queries
SELECT DstAddr FROM PROJ WHERE ScrAddr=Value SELECT SrcPort, DstAddr FROM PROJ SELECT SrcPort FROM PROJ WHERE DstPort=Value SELECT DstAddr FROM PROJ WHERE DstPort=Value
S1 S2 S3 15 20 10 5 0 0 25 25 25 3 0 0
Label Name
A1 SrcAddr
A2 SrcPort
A3 DstAddr
A4 DstPort
Your partitioning program will generate the the following em clustered affinity matrix as output:
A1 A3 A2 A4 A1 1.0000 0.9917 0.0000 0.0000 A3 0.9917 1.0000 0.0073 0.0026 A2 0.0000 0.0073 1.0000 0.9970 A4 0.0000 0.0026 0.9970 1.0000
Web-submission instructions
First, type the following command, all on one line (replacing xxxxxxx with your student ID):
svn mkdir parents -m DDDM https://version-control.adelaide.edu.au/svn/axxxxxxx/2017/s2/dddm/assignment1
Then, check out this directory and add your files:
svn co https://version-control.adelaide.edu.au/svn/axxxxxxx/2017/s2/dddm/assignment1 cd assignment1
svn add PartitionAttributes.cpp
svn add StudentFile1.cpp
svn add StudentFile2.cpp

svn commit -m assignment1 solution
Next, go to the web submission system at: https://cs.adelaide.edu.au/services/websubmission/
Navigate to 2017, Semester 2, Distributed Databases and Data Mining, Assignment 1. Then, click Tab Make Submission for this assignment and indicate that you agree to the declaration. The automark script will then check whether your code compiles. You can make as many resubmissions as you like. If your final solution does not compile you will not get any marks for this solution.
Note:
1. Your PartitionAttributes.cpp should accept two input files in the order of Attributes,
Queries and Access frequencies then print the CA matrix as the output. 2. Please follow the forms in sample output files.
3. Your local file path will not work with our web-submission system.