Improvement of Routing Operation Based on Learning with Using Smart Local and Global Agents and with the Help of the Ant Colony Algorithm
الموضوعات :
Majid Mohammadpour
1
(Department of Computer Engineering, Khormooj Branch, Islamic Azad University, Khormooj, Iran)
Hamid Parvin
2
(Department of Computer Engineering, Khormooj Branch, Islamic Azad University, Khormooj, Iran)
Ali Chamkoori
3
(Department of Computer Engineering, Khormooj Branch, Islamic Azad University, Khormooj, Iran)
الکلمات المفتاحية: learning, Routing, Computer Networks, Ant Colony Algorithms,
ملخص المقالة :
Routingincomputernetworks has played a special role in recent years.The cause ofthisisthe role ofroutingina performanceof the networks.The quality ofserviceand securityis one of the most importantchallengesin routing due tolack of reliablemethods.Routers use routing algorithms to findthe best route toa particulardestination. When talkingabout the bestpath, we consider parameters likethe number of hops, change times, and communication cost of sending data packet. In this study we will try to improve the routing operations using local and global smart factors. The Ants Colony Algorithm is a multi-factor solution for optimization issues. This solution has models based on the ants’ collective intelligence and has attracted some users in computer networks through converting to an efficient technology. Although the Ant is a simple insect, but a colony of them are able to perform useful tasks such as finding the shortest path to the food source and to share this information with other ants through leaving back a chemical material called pheromone. This algorithm consists of three stages. The first phase is clustering nodes of the network to smaller colonies. This phase is conducted by using learning automata network in accordance with the need of the network; For example, putting nodes in one cluster which will have more close relations in near future. The second phase is finding the routes of the network by ants, and the third phase is sending network
