一种基于概率的QoS多播路由遗传算法

文章提出了一种基于概率的QoS多播路由遗传算法.该算法通过一种精度可控的次优化方法,解决了基 于非精确状态延时带宽限制代价最小的QoS多播路由问题.仿真实验表明,该算法能有效地屏蔽网络状态的非精确性,忍受较大的网络更新触发门限值,并保持较好的路由性能.     

一种基于概率的QoS多播路由遗传算法

文章提出了一种基于概率的QoS多播路由遗传算法。该算法通过一种精度可控的次优化方法,解决了基于非精确状态延时带宽限制代价最小的QoS多播路由问题。仿真实验表明,该算法能有效地屏蔽网络状态的非精确性,忍受较大的网络更新触发门限值,并保持较好的路由性能。     

延迟约束多播路由问题的分支优化算法

QoS保证下的多播服务对于许多多媒体实时应用程序是重要的,QoS约束下的多播路由协议要求寻找连接源节点和目标节点集的支撑树使得端到端的QoS约束得以满足同时优化网络资源消耗,延迟约束最小代价树DCST是其中的关键问题.本文提出一个关于DCST的分支优化算法,该算法的核心思想是通过反向分支调节过程调整不满足QoS约束的路径并且减少对原支撑树结构的影响.仿真显示本文的算法对于实际网络是有效的.     

Ad Hoc网络中基于粒子群优化的QoS多播路由研究

针对Ad Hoc网络中带QoS约束的多播路由问题，提出了一种新的结合MAODV多播路由发现方法和粒．子群优化算法的QoS多播路由发现算法。仿真试验显示该算法较好地改进了端到端传输的代价、延时和带宽利用率，能够找到一棵消耗趋于最小、状态稳定的多播路由树。     

一种基于蚁群算法的分布式多播路由算法

随着计算机网络的不断发展,大量多媒体应用要求网络具有满足QoS约束的多播功能.应用多播的关键是确定有效的多播路由,即求解最优Steiner树.目前提出的大部分都是集中式的或本质上是集中式的启发式算法,关于分布式算法的研究还比较少.本文提出了一种基于蚁群算法的分布式多播路由算法.该算法在源节点不掌握整个网络信息的情况下,利用网络的局部启发式信息和蚂蚁留下的信息素建立最优的多播路由.结合多播路由问题的特点,对算法进行了改进,使算法的收敛速度和解的质量都得到了较大的提高.仿真实验结果验证了该算法的有效性.     

Ad Hoc网络中基于协商机制的QoS多播路由研究

针对移动Ad Hoc网络QoS多播路由中普遍存在的拥塞问题,提出了一种基于协商机制的QoS多播路由协议,节点协商使用以一定QoS约束建立起的多播链路,避免过度使用多播资源引起网络拥塞,从而提高分组投递率和网络吞吐量。通过NS2仿真证明,该协议能够保证不同类型业务在网络中传输的服务质量,提高网络的利用率。     

一种多约束QoS多播路由算法

提出了带宽时延约束、代价最小的QoS多播路由模型,并提出了一种启发式算法求解该问题,分析了算法的复杂度。仿真试验证明,该算法是稳定有效的。它能够在满足两种约束的情况下,使多播树的代价优化。     

Ad Hoc网络中一种基于QoS的分布式多播路由算法

通过分析Ad Hoe网络的特点及基于QoS的多播路由问题，提出了一种新的分布式多播路由算法。实验和分析的结果表明，文中构造的路由方案成功地解决了Ad Hoe网中基于QoS的多播路由问题。当Ad Hoe网络的拓扑结构改变不太快时，本文提出的路由方案不仅满足了实时业务对网络带宽和端到端延时的要求，优化了路由树的代价，而且有效地控制了算法的复杂性并可适用于大规模的网络中。     

支持延时约束的覆盖多播路由协议的研究

研究有度和延时约束的覆盖多播路由问题,提出了一个新的覆盖多播路由协议-延时受限的树协议(DBTP)。该协议采用分布式和树优先的策略,使多播组成员之间能自组织地构建一棵基于源的覆盖多播树。DBTP协议采用了一种新的启发式局部优化算法,通过调节启发因子,能灵活地在延时和代价之间进行折衷。仿真实验表明,无论在静态还是动态节点模型下,选择适当的启发参数,DBTP都能获得较高的节点接纳率。     

基于主动网络层次的多播体系结构

研究了多播路由协议及多播源分发数据报文的机制,提出一种新型的基于主动网络层次的多播体系结构,在自治系统AS中的分枝节点,亦可以根据该策略,构造以分枝节点为根的动态管理方式,从而可以动态地构造层次多播体系结构,在动态层次多播路由的具体实现中引入了agent和主动网络的概念,从而可以动态的加载多播路由,使得网络体系结构灵活与可编程.     

Two algorithms for multi‐constrained optimal multicast routing

Multimedia applications, such as video‐conferencing and video‐on‐demand, often require quality of service (QoS) guarantees from the network, typically in the form of minimum bandwidth, maximum delay, jitter and packet loss constraints, among others. The problem of multicast routing subject to various forms of QoS constraints has been studied extensively. However, most previous efforts have focused on special situations where a single or a pair of constraints is considered. In general, routing under multiple constraints, even in the unicast case is an NP‐complete problem. We present in this paper two practical and efficient algorithms, called multi‐constrained QoS dependent multicast routing (M_QDMR) and (multicasting routing with multi‐constrained optimal path selection (M_MCOP)), for QoS‐based multicast routing under multiple constraints with cost optimization. We provide proof in the paper that our algorithms are correct. Furthermore, through extensive simulations, we illustrate the effectiveness and efficiency of our proposals and demonstrate their significant performance improvement in creating multicast trees with lower cost and higher success probability. Copyright © 2003 John Wiley & Sons, Ltd.     

A resource‐tuned QoS multicast routing protocol

This paper presents a novel framework for quality‐of‐service (QoS) multicast routing with resource allocation that represents QoS parameters, jitter delay, and reliability, as functions of adjustable network resources, bandwidth, and buffer, rather than static metrics. The particular functional form of QoS parameters depends on rate‐based service disciplines used in the routers. This allows intelligent tuning of QoS parameters as functions of allocated resources during the multicast tree search process, rather than decoupling the tree search from resource allocation. The proposed framework minimizes the network resource utilization while keeping jitter delay, reliability, and bandwidth bounded. This definition makes the proposed QoS multicast routing with resource allocation problem more general than the classical minimum Steiner tree problem. As an application of our general framework, we formulate the QoS multicast routing with resource allocation problem for a network consisting of generalized processor sharing nodes as a mixed‐integer quadratic program and find the optimal multicast tree with allocated resources to satisfy the QoS constraints. We then present a polynomial‐time greedy heuristic for the QoS multicast routing with resource allocation problem and compare its performance with the optimal solution of the mixed‐integer quadratic program. The simulation results reveal that the proposed heuristic finds near‐optimal QoS multicast trees along with important insights into the interdependency of QoS parameters and resources.     

QoS multicast routing in cognitive radio ad hoc networks

In this paper, we discussed the issues of QoS multicast routing in cognitive radio ad hoc networks. The problem of our concern was: given a cognitive radio ad hoc network and a QoS multicast request, how to find a multicast tree so that the total bandwidth consumption of the multicast is minimized while the QoS requirements are met. We proposed two methods to solve it. One is a two‐phase method. In this method, we first employed a minimal spanning tree‐based algorithm to construct a multicast tree and then proposed a slot assignment algorithm to assign timeslots to the tree links such that the bandwidth consumption of the tree is minimized. The other is an integrated method that considers the multicast routing together with the slot assignment. Extensive simulations were conducted to show the performance of our proposed methods. Copyright © 2011 John Wiley & Sons, Ltd.     

A new delay‐constrained algorithm for multicast routing tree construction

New multimedia applications provide guaranteed end‐to‐end quality of service (QoS) and have stringent constraints on delay, delay‐jitter, bandwidth, cost, etc. The main task of QoS routing is to find a route in the network, with sufficient resources to satisfy the constraints. Most multicast routing algorithms are not fast enough for large‐scale networks and where the source node uses global cost information to construct a multicast tree. We propose a fast and simple heuristic algorithm (EPDT) for delay‐constrained routing problem for multicast tree construction. This algorithm uses a greedy strategy based on shortest‐path and minimal spanning trees. It combines the minimum cost and the minimum radius objectives by combining respectively optimal Prim's and Dijkstra's algorithms. It biases routes through destinations. Besides, it uses cost information only from neighbouring nodes as it proceeds, which makes it more practical, from an implementation point of view. Copyright © 2004 John Wiley & Sons, Ltd.     

An integrated routing and admission control mechanism for real‐time multicast connection establishment

There are two major difficulties in real‐time multicast connection setup. One is the design of an efficient distributed routing algorithm which optimizes the network cost of routing trees under the real‐time constraints. The other is the integration of routing with admission control into one single phase of operations. This paper presents a real‐time multicast connection setup mechanism, which integrates multicast routing with real‐time admission control. The proposed mechanism performs the real‐time admission tests on a cost optimal tree (COT) and a shortest path tree (SPT) in parallel, aiming at optimizing network cost of the routing tree under real‐time constraints. It has the following important features: (1) it is fully distributed; (2) it achieves sub‐optimal network cost of routing trees; (3) it takes less time and less network messages for a connection setup. Copyright © 2001 John Wiley & Sons, Ltd.     

QoS multicast routing scheme using QGA in IP/DWDM networks

This article studies multi-constraints least-cost multicast routing problem in internet protocol over dense wavelength division multiplexing （IP/DWDM） networks. To address this problem, an individual-difference-based quantum genetic algorithm （IDQGA） is proposed. This algorithm considers individual differences among chromosomes by introducing an adaptive rotation angle step determination scheme and a grouping-based quantum mutation operation. Simulations are conducted over network topologies. The results indicate that compared with other heuristic algorithms, IDQGA has better optimal performance on solving quality of service （QoS） multicast routing problem in IP/DWDM networks and is characterized by strong robustness, high success ratio and excellent capability on global searching.     

QM2RP: A QoS-Based Mobile Multicast Routing Protocol Using Multi-Objective Genetic Algorithm

With the increasing demand for real-time services in next generation wireless networks, quality-of-service (QoS) based routing offers significant challenges. Multimedia applications, such as video conferencing or real-time streaming of stock quotes, require strict QoS guarantee on bandwidth and delay parameters while communicating among multiple hosts. These applications give rise to the need for efficient multicast routing protocols, which will be able to determine multicast routes that satisfy different QoS constraints simultaneously. However, designing such protocols for optimizing multiple objectives, is computationally intractable. Precisely, discovering optimal multicast routes is an NP-hard problem when the network state information is inaccurate – a common scenario in wireless networks. Based on the multi-objective genetic algorithm (MOGA), in this paper we propose a QoS-based mobile multicast routing protocol (QM²RP) that determines near-optimal routes on demand. Our protocol attempts to optimize multiple QoS parameters, namely end-to-end delay, bandwidth requirements, and residual bandwidth utilization. Furthermore, it is fast and efficient in tackling dynamic multicast group membership information arising due to user mobility in wireless cellular networks. Simulation results demonstrate that the proposed protocol is capable of discovering a set of QoS-based, near-optimal multicast routes within a few iterations, even with imprecise network information. Among these routes one can choose the best possible one depending on the specified QoS requirements. The protocol is also scalable and yields lower multicast call-blocking rates for dynamic multicast group size in large networks.