Optimizing co-existing multicast routing trees in IP network via discrete artificial fish school algorithm

Abstract

Increasingly more internet-applications require the supports of multiple multicasts, while existing multicast routing algorithms only aim to establish a single multicast routing tree (MRT). Sequentially optimizing the co-existing MRTs each is a common practice of handling the situation of multiple multicast session being concurrent, but it results in link-congestion on low-cost routes, or leads to non-optimal solution even if bandwidth reservation strategy is adopted. This paper proposes to optimize multiple co-existing MRTs as a whole via one-off optimization instead of sequentially optimizing each in isolation. To carry out the one-off optimization, a discrete artificial fish school algorithm (DAFSA) is proposed. The simulation results show that the proposed DAFSA is capable of optimally packing co-existing MRTs and exhibits remarkably better ability than several the most representative state-of-the-art algorithms in the sense of avoiding the link-congestion and minimizing the overall tree cost. The running time of the proposed DAFSA fully meets the requirements of the practical IP multicasting. Besides, Monte Carlo test proves that the convergence of the proposed DAFSA is not sensitive to its parameters.