An ant based rate allocation algorithm for media streaming in peer to peer networks

In this paper, we propose a novel algorithm for rate allocation in multiple-source media streaming peer to peer networks. Our algorithm is based on ant-colony optimization and capable of handling network changes which occur quite often in unstructured P2P networks. The suggested algorithm does not need any information about the topology of the network. Moreover, it could get over uncertainties in network state information, particularly the rate of media provider nodes that could happen due to lack of accurate measurements. We show that our algorithm will reach the maximum achievable rate of the network quite fast and with relatively little overhead. In our simulations, we have demonstrated that in cases where network state information is inaccurate, the suggested ant-based rate allocation method will lead to the same results that other optimization-based rate allocation algorithms yield. Moreover, we have shown that the proposed algorithm has an intrinsic low pass filter which discriminate between transient network changes from permanent ones. If the changes in the network is transient, the algorithm compensate the temporary losses quite fast and without much effort. In cases where the network changes last longer, the algorithm overcomes losses by employing other nodes that have the media stream available. The rate of adaptation is adjustable and must be carefully determined according to network conditions.