سال انتشار: ۱۳۸۵

محل انتشار: دوازدهمین کنفرانس سالانه انجمن کامپیوتر ایران

تعداد صفحات: ۴

نویسنده(ها):

Kambiz Rahbar – SaShiraz Electro-optic and Laser Technology Research Center,Shiraz, Iran
Mohammad Akbarzadeh – Electric Department, Faculty of Engineering, Ferdowsi University, Mashad, Iran

چکیده:

This research addresses computer network routing based on recursive modeling method (RMM). In our proposed method, each router as an intelligent agent uses RMM tree-like structure to make a rational and intelligent decision on transmitting packages. This decision is made based on the models of other routers in the network and its belief about them. However, as the network conditions vary with time, the needs of updating
each routers belief about others can not be neglected. To achieve this goal, Bayesian law is used to update routers belief about others. To validate the proposed method, we test it as a computer simulation. The results show that this method increases the network performance by decreasing the network overhead arising from routers packages. Additionally, as the network dynamics increases, employing Bayesian law helps the routers to quickly adapt to the new conditions.