Multicast routing for multimedia communication
IEEE/ACM Transactions on Networking (TON)
Distributed algorithms for multicast path setup in data networks
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
A Distributed Algorithm for Minimum-Weight Spanning Trees
ACM Transactions on Programming Languages and Systems (TOPLAS)
Introduction to algorithms
A source-based algorithm for delay-constrained minimum-cost multicasting
INFOCOM '95 Proceedings of the Fourteenth Annual Joint Conference of the IEEE Computer and Communication Societies (Vol. 1)-Volume - Volume 1
IEEE/ACM Transactions on Networking (TON)
A Service-Centric Multicast Architecture and Routing Protocol
IEEE Transactions on Parallel and Distributed Systems
Research on multicast routing protocols for mobile ad-hoc networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
IEEE Communications Magazine
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The multicast routing is one of the important techniques for achieving multicast applications in wireless networks, e.g., real-time video multicasting in Vehicular Ad-hoc NETwork (VANET). The main objective of a delay-bounded multicast algorithm is to determine the least-cost multicast tree while satisfying the delay-bounded requirement for multicasting voice/video transmission. Several multicast algorithms have been proposed, some disadvantages have not yet solved, including: (1) yielding a large numbers of control messages, (2) yielding dangling nodes, (3) exhibiting the cycle-free problem, (4) increasing the tree setup time, (5) suffering from the tree setup-break problem, etc. Thus, this paper proposes an adaptive distributed multicast routing (ADMR) algorithm to guarantee cycle-free, to overcome the tree setup-break and the dangling nodes problems while achieving the least-cost delay-bounded multicast tree for high density member multicast networks. Numerical results demonstrate that ADMR significantly outperforms the compared algorithms in the number of control messages and the setup convergence time. Finally, the worst case time complexity and the number of messages of ADMR are analyzed, which requires O(n · (m + c)) time and O(2m + 2c) messages, respectively. The analyzed results of ADMR are lower than that of the compared algorithms.