Minimum Cost Multicast Routing Research Articles

A delay-bounded low-cost multicast routing algorithm for mobile ad hoc networks

In this paper, we focus on developing delay-bounded low-cost multicast tree, linking a source to a set of multicast nodes in a mobile ad hoc network The problem of our concern is given a wireless ad hoc network and a multicast request, how to find a multicast tree such that the total cost of the multicast tree is minimized, the cost can be regarded as transmitting power, bandwidth, battery energy, and so on. We proposed a novel minimum-cost multicast routing heuristic algorithm (delay-bounded low-cost multicast routing algorithm) to solve this well-known hard problem, and this algorithm can be easily implemented in a distributed fashion. The algorithm guarantees the multicast tree, which satisfies the delay bound and has low cost if it exists. And finally, the performance of mobile ad hoc network scared from 50 to 200 nodes is evaluated. Simulations results show that the delay and tree cost of the proposed method are lower than well-known multicast ad hoc on-demand distance vector protocol and QoS Dependent Multicast Routing protocol.

Minimum Cost Multicast Routing Using Ant Colony Optimization Algorithm

Multicast routing (MR) is a technology for delivering network data from some source node(s) to a group of destination nodes. The objective of the minimum cost MR (MCMR) problem is to find an optimal multicast tree with the minimum cost for MR. This problem is NP complete. In order to tackle the problem, this paper proposes a novel algorithm termed the minimum cost multicast routing ant colony optimization (MCMRACO). Based on the ant colony optimization (ACO) framework, the artificial ants in the proposed algorithm use a probabilistic greedy realization of Prim’s algorithm to construct multicast trees. Moving in a cost complete graph (CCG) of the network topology, the ants build solutions according to the heuristic and pheromone information. The heuristic information represents problem-specific knowledge for the ants to construct solutions. The pheromone update mechanisms coordinate the ants’ activities by modulating the pheromones. The algorithm can quickly respond to the changes of multicast nodes in a dynamic MR environment. The performance of the proposed algorithm has been compared with published results available in the literature. Results show that the proposed algorithm performs well in both static and dynamic MCMR problems.

On minimum cost multicast routing based on cost prediction

We have designed an algorithm for a problem in multicast communication. The problem is to construct a multicast tree while minimizing its cost, which is known to be NP-complete. Our algorithm, which employs new concepts defined as potential cost and spanning cost, generates a multicast tree more efficiently than the well-known heuristic called Takahashi and Matsuyama (TM) [1] in terms of tree cost. The time complexity of our algorithm is O(kn <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) for an n-node network with k members in the multicast group and is comparable to the TM. Our empirical performance evaluation comparing the proposed algorithm with TM shows that the enhancement is up to 1.25%∼4.23% for each best case.

Enforcing Minimum-Cost Multicast Routing against Selfish Information Flows

We study multicast in a noncooperative environment where information flows selfishly route themselves through the cheapest paths available. The main challenge is to enforce such selfish multicast flows to stabilize at a socially optimal operating point incurring minimum total edge cost, through appropriate cost allocation and other economic measures, with replicable and encodable properties of information flows considered. We show that known cost allocation schemes are not sufficient. We provide a shadow-price-based cost allocation for networks without capacity limits and show that it enforces minimum-cost multicast. This improves previous result where a 2-approximate multicast flow is enforced. For capacitated networks, computing cost allocation by ignoring edge capacities will not yield correct results. We show that an edge tax scheme can be combined with a cost allocation to strictly enforce optimal multicast flows in this more realistic case. If taxes are not desirable, they can be returned to flows while maintaining weak enforcement of the optimal flow. We relate the taxes to VCG payment schemes and discuss an efficient primal-dual algorithm that simultaneously computes the taxes, the cost allocation, and the optimal multicast flow, with potential of fully distributed implementations.

A Distributed Cross-Layer Optimization Method for Multicast in Interference-Limited Multihop Wireless Networks

We consider joint optimization of data routing and resource allocation in multicast multihop wireless networks where interference between links is taken into account. The use of network coding in such scenarios leads to a nonconvex optimization problem. By applying the probability collectives (PCs) technique the original problem is turned into a new problem which is convex over probability distributions. The resulting problem is then further decomposed into a data routing subproblem at network layer and a power allocation subproblem at physical layer in order to achieve a cross-layer distributed solution for the whole range of SINR values. The proposed approach is also extended to minimum cost multicast problems and routing problems based on multicommodity flow and single Steiner tree, resulting in new distributed algorithms for such problems.

Efficient solutions to multicast routing in communication networks

An important problemin both wireless and wired communication networks is to be able to efficiently multicast information to a group of network sites. Multicasting reduces the transmission overhead of both wireless and wired networks and the time it takes for all the nodes in the subset to receive the information. Since transmission bandwidth is a scarce commodity especially in wireless networks, efficient and near minimum-cost multicast algorithms are particularly useful in the wireless context. In this paper, we discuss methods of establishing efficient and near minimum-cost multicast routing in communication networks. In particular, we discuss an efficient implementation of a widely used multicast routing method which can construct a multicast tree with a cost no greater than twice the cost of an optimal tree. We also present two efficient multicast tree constructions for a general version of the multicast routing problem in which a network consists of different classes of nodes, where each class can have one or more nodes of the same characteristic which is different fromthe characteristics of nodes fromother classes. Because of their efficient running times, these multicast routing methods are particularly useful in the mobile communication environments where topology changes will imply recomputation of the multicast trees. Furthermore, the proposed efficient and near minimum-cost multicast routing methods are particularly suited to the wireless communication environments, where transmission bandwidth is more scarce than wired communication environments.