No Description

Siyuan Ye eb442c2eae readme 10 months ago
middle_data 6f79496b81 all 10 months ago
v1 baf181aaec Modify code comments 10 months ago
v2 6f79496b81 all 10 months ago
v3 63999acd8a delete log file 10 months ago
db0.json.gz 8d7854d8a4 上传文件至 '' 10 months ago
readme.txt eb442c2eae readme 10 months ago

readme.txt

V1 corresponds to V1 in the thesis; V2 is the fixed-schedule, which is not shown in the thesis; V3 corresponds to V2 in the thesis

main.go in text is the program at client; agent is the program at ACS; receiver is the program at recipient; final is the clustering's program

All the files in middle_data are used when doing clustering. The data from redis is exported, filtered and finally used as input data for final.py. The grouping results from final.py are then returned to ACS


V1:
client:
First use the test2 function to take out all the data to be sent in db0 in redis for this round, then cache the message and timestamp into db2, and the user id and corresponding ip into db1
The finalsend() function takes the data from db2 and consolidates it into a merged message that is sent to the ACS. Depending on the status of the user (arrival, learning and online), different actions are performed
StatusChangeOrNot_arrival_to_learning(), StatusChangeOrNot_learning_to_online() and StatusChangeOrNot_eliminated() functions, which handle the status change in each round respectively
ACS:
peocessConn() function, responsible for receiving messages from the client, and depending on the status of the users, they are processed differently and cached in different databases
arrivalToLearn1(), learning_To_online_batchList(h24), learning_function(h24), online_cache_process() for handling transitions between different states

V2:
before_finalsend(), before() function, responsible for communication between client and ACS, determining schedule