Quality Of Service Multicast Routing Algorithm Research Articles

A EA- and ACA-based QoS multicast routing algorithm with multiple constraints for ad hoc networks

With the rapid development of communication networks, the quality of service (QoS) on such networks has become an important research topic. With regard to ad hoc networks, this paper presents an evolutionary algorithm (EA) and an ant colony algorithm (ACA) to serve as the basis for a QoS multicast routing algorithm (EA-ACA-QMRA). This algorithm combines the rapid global search capability and robustness of EAs with the pheromone feedback factors of ACAs while accounting for multiple constraints, including constraints related to delay, delay jitter, packet delivery ratio, bandwidth and cost. For the case of self-adapting ad hoc networks in particular, our new algorithm is far superior to traditional ACAs. Our experimental results show that the EA-ACA-QMRA can address multiple constraints in the QoS multicast routing problem and can achieve higher accuracy and faster convergence than can traditional ACAs in terms of the end-to-end delay and packet delivery ratio. The proposed algorithm provides an effective means of solving the QoS multicast routing problem for ad hoc networks, and it is better than the traditional methods at avoiding network congestion.

Performance Analysis of QoS Multicast Routing in Mobile Ad Hoc Networks Using Directional Antennas

in this paper, a quality of service (QoS) multicast routing protocol in mobile ad hoc networks (MANETs) by using directional antennas has been presented. Many important applications, such as audio/video conferencing, require the quality of service guarantee. Directional antenna technology provides the capability for considerable increase in spatial reuse, which increases the efficiency of communication. This paper studies TDMA-based timeslot allocation and directional antennas, and presents an effective algorithm for calculating bandwidth of a multicast tree. We also propose a novel on-demand QoS multicasting routing algorithm in TDMA-based mobile ad hoc networks using directional antennas. The simulation result shows the performance of this QoS multicast routing algorithm in TDMA-based mobile ad hoc networks using directional antennas.

Enhanced QoS Multicast Routing in Wireless Mesh Networks

Wireless mesh network (WMN) has recently emerged as a promising technology for next-generation wireless networking. In WMNs, many important applications, such as mobile TV and video/audio conferencing, require the support of multicast communication with quality-of-service (QoS) guarantee. In this paper, we address the QoS multicast routing issue in WMNs. Specifically, we propose a novel network graph preprocessing approach to enable traffic engineering and enhance the performance of QoS multicast routing algorithms. In this approach, we employ prioritized admission control scheme and develop a utility-constrained optimal priority gain policy. Extensive simulation results show that our approach can significantly improve the performance of QoS multicast routing in WMNs.

A GA-based QoS multicast routing algorithm for large-scale networks

For multimedia applications, the routing algorithms should consider many Quality of Service (QoS) parameters. However, to find routes with two or more QoS parameters is an NP-hard problem. Therefore, recently many researchers are trying to use heuristic methods such as Genetic Algorithm (GA). In a previous work, a QoS multicast routing based on GA was proposed. However, in this algorithm, the multicast routing falls in the local minimum and cannot satisfy the application requirements. In this paper, we propose a new QoS multicast routing protocol, which has better genetic operations than the conventional algorithm, resulting in a better performance.

QoS multicast routing for multimedia group communications using intelligent computational methods

In this paper, we investigate the problem of quality-of-service (QoS) multicast routing for multimedia group communications. We first develop a unified framework for achieving QoS multicast trees using intelligent computational methods. The framework consists of the model for multimedia communication network, the formulation of QoS multicast routing problem, and three key components used in intelligent computational methods-based QoS multicast routing algorithms. Then we propose three QoS multicast algorithms based on three representative intelligent computational methods (i.e., genetic algorithm, simulated annealing, and Tabu search), separately. In these algorithms, both the network resource requirements and the end-to-end delay are considered as the QoS parameters. Various issues are analyzed and designed for applying these three intelligent computational methods to construct QoS multicast trees. By simulation, we evaluate the performance of these three algorithms on a small-scale real-world multimedia communication network and a randomly generated large-scale network. Simulation results show that our algorithms can find near-optimal QoS multicast trees with high success rate. We also compare the running time among them, which help explain the algorithmic structures.

A QoS multicast routing optimization algorithm based on genetic algorithm

Most of the multimedia applications require strict quality of service (QoS) guarantee during the communication between a single source and multiple destinations. This gives rise to the need for an efficient QoS multicast routing strategy. Determination of such QoS-based optimal multicast routes basically leads to a multi-objective optimization problem, which is computationally intractable in polynomial time due to the uncertainty of resources in Internet. This paper describes a network model for researching the routing problem and proposes a new multicast tree selection algorithm based on genetic algorithms to simultaneously optimize multiple QoS parameters. The paper mainly presents a QoS multicast routing algorithm based on genetic algorithm (QMRGA). The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or near-optimal solution within few iterations, even for the networks environment with uncertain parameters. The incremental rate of computational cost can close to polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated using simulations. The simulation results show that this approach has fast convergence speed and high reliability. It can meet the real-time requirement in multimedia communication networks.

QoS-based multicast routing optimization algorithms for Internet

Most of the multimedia applications require strict Quality-of-Service (QoS) guarantee during the communication between a single source and multiple destinations. The paper mainly presents a QoS Multicast Routing algorithms based on Genetic Algorithm (QMRGA). Simulation results demonstrate that the algorithm is capable of discovering a set of QoS-based near optimized, non-dominated multicast routes within a few iterations, even for the networks environment with uncertain parameters.

QoS-guaranteed one-to-many and many-to-many multicast routing

Quality-of-service (QoS) multicast routing with more than one metric has always been technically challenging, since many of them are NP-hard. Most existing QoS multicast routing algorithms are heuristic. Furthermore, many of them considered only the unicast shortest paths, either based on propagation delay or the number of hops. The first part of this paper deals with one-to-many multicast routing. We observed that the end-to-end delay experienced by network packets is determined not only by the propagation distance, but also (and in many cases largely) by the hop-by-hop transmission and queuing delay, which in turn depends on the available bandwidth. Based on this observation, we propose an optimal multicast routing algorithm (the MBDC algorithm), which maximizes the reserved bandwidth while satisfying both delay and bandwidth constraints. Its correctness and time complexity of O( n 2 log n) are formally verified, where n is the number of nodes in the network. We also extend the algorithm to support dynamic membership, allowing nodes to join or leave the network, with the cast route updated dynamically. We carefully evaluate both the static and the dynamic algorithms via simulation. The second part of the paper focuses on minimizing the number of centers of multiple-shared multicast trees (MSMT) in many-to-many multicast routing. We propose three heuristic algorithms to this NP-complete problem and compare them with an existing one. We prove, theoretically and through simulation, that our algorithms give the same good results with a significantly shorter running time. We also apply the MBDC extension to the MSMT algorithms, so that the resulting solution not only reduces the number of centers, but also optimizes (maximizes) the bottleneck bandwidth. Proof of correctness, analysis of run-time, and simulation results of these extensions are also provided. We believe that the results report here are significant to the area of QoS-aware multicast routing; the algorithms may be applied to the Internet intra- and inter-domain multicast routing with minimal changes.