Cloud Traffic Congestion Avoidance System Using Genetic Algorithm

Congestion control has been always a major problem when network and data transmission gets involved. With the emergence of cloud computing the same problem applies to cloud computing environment too. In this paper we consider the problem of congestion control in cloud web computing environment which support both multirate multicast sessions and unicast sessions. Our work proposes an efficient congestion control mechanism using genetic algorithm, which identifies service state information of the communication. A Subserver justifies packet speed labeled by identifier and it decides the rapidness in which the receiver should receive the packet. Based on the receiver's requirement speed, the sub server splits the packets and forwards it. Also it identifies service state information for allocating bandwidth to the receivers. We propose an architecture that significantly reduces this implementation complexity but still achieves approximately fair bandwidth allocations. The congestion-control mechanism takes into account the diverse user requirements when different receivers within a multicast session have proper fitness functions in GA, but does not require the network to have any knowledge about the receiver utility functions.