2005/03/31 by Desmond S. Lun, Niranjan Ratnakar, N. Ratnakar +9 · 2 citations
Computer Science · Mathematics · #Computer network #Computer science #Cooperative Communication and Network Coding #Distance Vector Multicast Routing Protocol #Distributed computing #IP multicast #Mobile Ad Hoc Networks #Multicast #Network packet #Pragmatic General Multicast #Protocol Independent Multicast #Source-specific multicast #Unicast #Wireless Networks and Protocols #Xcast #cs.IT #cs.NI #math.IT
paper · pdf · doi:10.1109/tit.2006.874523
published as IEEE Trans. Inform. Theory, vol. 52, no. 6, pp. 2608-2623, June 2006 · 17 pages, 6 figures; to appear in IEEE Transactions on Information Theory (special issue on Networking and Information Theory); revised version, with major changes
arxiv created 2006/01/31 · openalex publication_date 2006/06/01 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We consider the problem of establishing minimum-cost multicast connections over coded packet networks, i.e., packet networks where the contents of outgoing packets are arbitrary, causal functions of the contents of received packets. We consider both wireline and wireless packet networks as well as both static multicast (where membership of the multicast group remains constant for the duration of the connection) and dynamic multicast (where membership of the multicast group changes in time, with nodes joining and leaving the group). For static multicast, we reduce the problem to a polynomial-time solvable optimization problem, and we present decentralized algorithms for solving it. These algorithms, when coupled with existing decentralized schemes for constructing network codes, yield a fully decentralized approach for achieving minimum-cost multicast. By contrast, establishing minimum-cost static multicast connections over routed packet networks is a very difficult problem even using centralized computation, except in the special cases of unicast and broadcast connections. For dynamic multicast, we reduce the problem to a dynamic programming problem and apply the theory of dynamic programming to suggest how it may be solved.