A QoS Routing Method for Multimedia Communication in Broadband Networks

今天的网络正在经历一个快速的发展，他们预计将支持广泛的多媒体应用。对多媒体数据的及时传送的需求对下一代宽带网络提出了新的挑战。关键问题是服务质量（QoS）路由。此外，确保业务流和流组的QoS需求是未来宽带网络的重要挑战，并且通过呼叫准入控制（CAC）的资源供应是实现这一点的关键机制。为了支持宽带网络上的多媒体通信，需要开发一种路由算法，该路由算法可以同时考虑多个QoS参数，如吞吐量、时延和丢失率。这是因为新的服务，如视频点播和远程会议系统需要更好的QoS。但是，由于以下原因，QoS路由问题是困难的。分布式应用在时延、丢包率、服务质量等方面有着不同的QoS约束 ...更多信息 比率和带宽。多个约束条件往往使路由问题变得棘手。例如，找到一个可行的路线，两个独立的路径约束是NP完全的。在我们以前的工作中，我们提出了一个智能路由和CAC策略，使用合作代理。然而，我们只考虑了路由的时间延迟。QoS和拥塞控制（CC）参数被认为是QoS满意度和拥塞的指标。提出了一种基于遗传算法的路由算法ARGAQ，它可以支持两个QoS参数：延迟和传输成功率。仿真结果表明，ARGAQ方法比一种只有一个QoS参数的路由算法ARGA方法具有更好的性能。然而，ARGAQ方法是有效的，只有当参数之间有一个关系，遗传算法的适应度函数可以表示为一个数学公式。在这项工作中，我们扩展了我们以前的工作，提出并实现了新的算法的基础上模糊逻辑（FL）和遗传算法（GA），用于CAC和路由许多QoS参数。提出的基于遗传算法的多目标优化算法采用多划分群体模型进行多目标优化。仿真结果表明，该框架具有良好的性能，是一种很有前途的QoS路由和CAC决策方法，并将该算法应用于ad-hoc网络中的QoS路由，表明该算法可以应用于ad-hoc网络。我们还提出并实现了P2P系统和远程学习系统，在宽带网络中表现出良好的性能。

The networks of today are going through a rapid evolution and they are expected to support a wide range of multimedia applications. The requirement for timely delivery of multimedia data raises new challenges for the next generation broadband networks. The key issue is the Quality of Service (QoS) routing. Also, ensuring the QoS demands to traffic flows and groups of flows is an important challenge for future broadband networks, and resource provisioning via Call Admission Control (CAC) is a key mechanism for achieving this. In order to support multimedia communication over broadband networks, it is necessary to develop routing algorithms which use for routing more than one QoS parameter such as throughput, delay, and loss probability. This is because new services such as video on demand and remote meeting systems require better QoS. But, the problem of QoS routing is difficult due to the following reasons. The distributed applications have very diverse QoS constraints on delay, loss r … More atio and bandwidth. Multiple constraints often make the routing problem intractable. For example, finding a feasible route with two independent path constraints is NP-complete.In our previous work, we proposed an intelligent routing and CAC strategy using cooperative agents. However, we only considered the time delay for the routing. The QoS and Congestion Control (CC) parameters were considered as indicators of QoS satisfication and congestion. The proposed a GA based routing algorithm called ARGAQ could support two QoS parameters : delay and transmission success rate. The simulation results show that ARGAQ method has better performance than a routing algorithm with only one QoS parameter called ARGA method. However, the ARGAQ method is effective only if the parameters have a relation between them and the GA fitness function can be expressed by a mathematical formula. In this work, we extend our previous work by proposing and implementing new algorithms based on Fuzzy Logic (FL) and Genetic Algorithm (GA) which use for CAC and routing many QoS parameters. The proposed GA-based multi-objective optimization algorithm uses a multi-division group model for multi-objective optimization. The simulation results show that proposed framework has a good performance and is a promising method for QoS routing and CAC decision.We also applied the proposed GA-based algorithm for QoS routing in ad-hoc networks and we showed that the proposed algorithm can be applied for ad-hoc networks. We proposed and implemented also a P2P system and Distance Learning System which show a good performance in broadband networks Less