Conference Paper

Forwarding state reduction for sparse mode multicast communication

Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC
DOI: 10.1109/INFCOM.1998.665093 Conference: INFOCOM '98. Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, Volume: 2
Source: IEEE Xplore

ABSTRACT Reducing forwarding state overhead of multicast routing protocols
is an important issue towards a scalable global multicast solution. We
propose a new approach, dynamic tunnel multicast, which utilizes
dynamically established tunnels on unbranched links of a multicast
distribution tree to eliminate unnecessary multicast forwarding states.
Analysis and simulation results show promising reduction in the state
overhead of sparse mode multicast routing protocols

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    ABSTRACT: This paper investigates routing algorithms that compute paths along which combined unicast and multicast traffic can be forwarded altogether, i.e., over the same path. For this purpose, the concept of AnyTraffic group is introduced that defines a set of nodes capable to process both unicast and multicast traffic received from the same (AnyTraffic) tree. The resulting scheme is referred to as AnyTraffic routing. This paper defines a heuristic algorithm to accommodate the AnyTraffic group and to find the proper set of branch nodes of the tree. The algorithm supports dynamic changes of the leaf node set during multicast session lifetime by adapting the corresponding tree upon deterioration threshold detection. Studies are performed for both static and dynamic traffic scenarios to i) determine the dependencies of the algorithm (node degree, clustering coefficient and group size); and ii) evaluate its performance under dynamic conditions. Initial results show that the AnyTraffic algorithm can successfully handle dynamic requests while achieving considerable reduction of forwarding state consumption with small increase in bandwidth utilization compared to the Steiner Tree algorithm.
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    ABSTRACT: Bloom Filter based multicast has been proposed as a source-specific multicast solution to eliminate the multicast state requirements in the routers. However, the inherent limitation, the false positives, in the Bloom filter data structure amplifies the bandwidth wastage when the multicast tree scales to a large number of receivers. In this paper, we propose an algorithm which enhances the performance of the Bloom filter based multicast. It keeps the bandwidth waste below an acceptable upper bound while scaling the multicast tree for a large number of receivers. The large multicast tree is split into multiple smaller ones which are encoded into separate Bloom filters. Our algorithm enables multicast forwarding to be efficient - with careful setting of some parameters - for a hundreds of receivers as compared to the 20-30 receivers per group in the original technique. Furthermore, our algorithm, while slightly increasing the state requirements in the multicast sources, retains the desired property of statelessness in the intermediate routers.
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    ABSTRACT: Software-Defined Networking (SDN) enables flexible network resource allocations for traffic engineering, but at the same time the scalability problem becomes more serious since traffic is more difficult to be aggregated. Those crucial issues in SDN have been studied for unicast but have not been explored for multicast traffic, and addressing those issues for multicast is more challenging since the identities and the number of members in a multicast group can be arbitrary. In this paper, therefore, we propose a new multicast tree for SDN, named Branch-aware Steiner Tree (BST). The BST problem is difficult since it needs to jointly minimize the numbers of the edges and the branch nodes in a tree, and we prove that it is NP-Hard and inapproximable within $k$, which denotes the number of group members. We further design an approximation algorithm, called Branch Aware Edge Reduction Algorithm (BAERA), to solve the problem. Simulation results demonstrate that the trees obtained by BAERA are more bandwidth-efficient and scalable than the shortest-path trees and traditional Steiner trees. Most importantly, BAERA is computation-efficient to be deployed in SDN since it can generate a tree on massive networks in small time.

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