Abstract
Multicast has great advantages in data forwarding. But the number of forwarding states becomes huge in routers when there are large numbers of multicast groups in the network, which may cause explosions of state information and control information. Aggregated multicast is a novel approach to reducing multicast state numbers. It enables multicast groups to share a single distribution tree so that the tree management overhead at core routers can be reduced. Aggregated Multicast can actually be attributed to minimal set cover problem, which is an NP-complete problem. To solve it this paper proposes a self-adaptive Lagrange Relaxation Algorithm, which can achieve global optimal solution. Simulation results show that this algorithm is better than the conventional greedy algorithm in that it improves aggregation degree and reduces multicast state number.
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Wang, H., Ge, Z., Ma, J. (2007). Self-adaptive Lagrange Relaxation Algorithm for Aggregated Multicast. In: van Leeuwen, J., Italiano, G.F., van der Hoek, W., Meinel, C., Sack, H., Plášil, F. (eds) SOFSEM 2007: Theory and Practice of Computer Science. SOFSEM 2007. Lecture Notes in Computer Science, vol 4362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69507-3_47
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DOI: https://doi.org/10.1007/978-3-540-69507-3_47
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