数据中心网络中组播路由优化和可靠性问题的研究
发布时间：2019-05-09 14:51
【摘要】：数据中心作为云计算的核心支撑部分，数据中心的性能直接决定了云计算服务的质量。数据中心网络作为数据中心中的通信桥梁，其负载正变得越来越重，并开始影响数据中心的性能。组播在数据中心中的扩展受到了越来越多人的关注。组播可以有效的降低数据中心中的网络负载，提高网络的性能。本文主要研究了数据中心网络中的组播路由优化问题和可靠性组播中的恢复节点和路径选取的问题。 数据中心网络的架构方式主要有两种，一种是以交换机为核心，另一种以服务器为核心。其中以服务器为核心的架构中服务器也参与数据包的转发，，如果服务器的负载压力很大，这时对数据包的接受和转发都会造成影响，比如增大数据包的发送时延，增大丢包率等。所以在生成组播树的时候，如果考虑到服务器的负载压力的状况，不仅可以使组播树更加健壮，同时也起到了调节数据中心服务器之间负载均衡的作用。本文提出了一种基于服务器节点负载和距离作为优化目标的新的组播树生成算法。该算法使用蚁群算法和遗传算法相结合的算法，将服务器负载和距离当做衡量适应值的参数，找出最符合条件的解作为有效结果。该算法尽量避免组播树的边经过负载过大的服务器节点，有效地降低了组播的时延并减小丢包的概率。 传统可靠性组播的数据包恢复方法是通过组播树的原有路径来恢复。但针对数据中心网络中拥有丰富冗余链路的特点，现在提出的数据包恢复的方法都是一对一单播的方法。这样可以有效的避免通过组播树中原路径来进行数据包的恢复，不仅减小了原路径的负担，还增大了数据包恢复的成功率。本文提出了一种基于丢包节点和恢复节点位置优先级的一种恢复节点的选取算法。通过节点本身的位置确定该节点容易丢包的程度，让丢包概率越大的节点优先选择最佳的恢复节点，建立节点之间的一对一恢复关系。该算法增加了易丢包节点的数据包恢复能力，使各节点间的恢复压力平均，并且占用更少的链路资源。 最后通过进行仿真实验，验证了两个算法的正确性和有效性。
[Abstract]:Data center as the core support part of cloud computing, the performance of data center directly determines the quality of cloud computing services. As the communication bridge in the data center, the load of the data center network is becoming heavier and heavier, and the performance of the data center is beginning to be affected. More and more people pay attention to the expansion of multicast in data center. Multicast can effectively reduce the network load in the data center and improve the performance of the network. This paper mainly studies multicast routing optimization in data center network and recovery node and path selection in reliable multicast. There are two main architectures of data center network, one is based on switch and the other is server. In the server-centered architecture, the server is also involved in the forwarding of packets. If the load of the server is very heavy, then the acceptance and forwarding of packets will be affected, such as increasing the transmission delay of packets. Increase the packet loss rate, etc. So when the multicast tree is generated, if the load pressure of the server is taken into account, not only can the multicast tree be more robust, but also it can adjust the load balance among the servers in the data center. In this paper, a new multicast tree generation algorithm based on server node load and distance is proposed. The algorithm uses ant colony algorithm and genetic algorithm, takes the server load and distance as the parameters to measure the fitness value, and finds out the most qualified solution as the effective result. The algorithm tries to avoid the edge of the multicast tree from passing through the server node with too much load, which effectively reduces the delay and the probability of packet loss. The traditional packet recovery method of reliable multicast is to recover through the original path of multicast tree. However, in view of the rich redundant links in the data center network, the proposed packet recovery methods are one-to-one unicast methods. In this way, the packet recovery through the central path of the multicast tree can be effectively avoided, which not only reduces the burden of the original path, but also increases the success rate of packet recovery. In this paper, a recovery node selection algorithm based on packet loss node and recovery node location priority is proposed. The degree of easy packet loss of the node is determined by the position of the node itself, and the node with the higher probability of packet loss is allowed to select the best recovery node first, and the one-to-one recovery relationship between the nodes is established. The algorithm increases the packet recovery ability of packet-prone nodes, makes the recovery pressure between each node average, and occupies less link resources. Finally, the correctness and effectiveness of the two algorithms are verified by simulation experiments.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP308
本文编号：2472847
[Abstract]:Data center as the core support part of cloud computing, the performance of data center directly determines the quality of cloud computing services. As the communication bridge in the data center, the load of the data center network is becoming heavier and heavier, and the performance of the data center is beginning to be affected. More and more people pay attention to the expansion of multicast in data center. Multicast can effectively reduce the network load in the data center and improve the performance of the network. This paper mainly studies multicast routing optimization in data center network and recovery node and path selection in reliable multicast. There are two main architectures of data center network, one is based on switch and the other is server. In the server-centered architecture, the server is also involved in the forwarding of packets. If the load of the server is very heavy, then the acceptance and forwarding of packets will be affected, such as increasing the transmission delay of packets. Increase the packet loss rate, etc. So when the multicast tree is generated, if the load pressure of the server is taken into account, not only can the multicast tree be more robust, but also it can adjust the load balance among the servers in the data center. In this paper, a new multicast tree generation algorithm based on server node load and distance is proposed. The algorithm uses ant colony algorithm and genetic algorithm, takes the server load and distance as the parameters to measure the fitness value, and finds out the most qualified solution as the effective result. The algorithm tries to avoid the edge of the multicast tree from passing through the server node with too much load, which effectively reduces the delay and the probability of packet loss. The traditional packet recovery method of reliable multicast is to recover through the original path of multicast tree. However, in view of the rich redundant links in the data center network, the proposed packet recovery methods are one-to-one unicast methods. In this way, the packet recovery through the central path of the multicast tree can be effectively avoided, which not only reduces the burden of the original path, but also increases the success rate of packet recovery. In this paper, a recovery node selection algorithm based on packet loss node and recovery node location priority is proposed. The degree of easy packet loss of the node is determined by the position of the node itself, and the node with the higher probability of packet loss is allowed to select the best recovery node first, and the one-to-one recovery relationship between the nodes is established. The algorithm increases the packet recovery ability of packet-prone nodes, makes the recovery pressure between each node average, and occupies less link resources. Finally, the correctness and effectiveness of the two algorithms are verified by simulation experiments.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP308
【参考文献】
相关期刊论文 前1条
1 丁建立,陈增强,袁著祉;遗传算法与蚂蚁算法的融合[J];计算机研究与发展;2003年09期
本文编号：2472847
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