可生存性虛擬網(wǎng)絡(luò)映射模型及算法研究
[Abstract]:With the explosive growth of the number of network users, the traditional network has been greatly impacted, and the problem of ossification is becoming more and more serious. In recent years, network virtualization (NV) technology, as an effective way to solve the problem of network fossilization, has received great attention. In the exploration of NV problem, as one of the important research contents, virtual network mapping, even though many virtual network requests (VNR) can be mapped to the same underlying physical network (SN), so that the resources on SN can be shared. However, due to the limited number of physical networks, the growth of network communications is seriously hindered. In view of this, this paper proposes a network virtualization NV (Network Virtualization NV) technology, which improves the degree of network fossilization to a large extent. At present, the network virtualization technology evaluation has a variety of indicators, such as SN acceptance of VNR, network speed response time and network stability. It is worth paying attention to, with the increasing number of network users, network failure has become an important factor affecting network stability. Therefore, how to improve the survivability of networks has become an important research topic in recent years. Most of the existing survivability algorithms focus on improving the stability of the network unilaterally, which makes the problem of resource waste become more and more prominent. At the same time, there are also some problems such as load imbalance and limited application in the network environment. Aiming at the above problems, this paper conducts experiments and probes into the network survivability problem. The main contents are as follows: 1) to meet the link protection needs of different users. A survivability virtual network mapping algorithm, GSVNE.GSVNE, which can adjust resource ratio, is proposed. Firstly, the physical network link resource is divided into two parts: the main stream and the backup stream resource. The former is the resource provided to the user under the normal condition of the network. The latter is the backup resource allocated to the user in the event of network failure. Then, a new intelligent optimization algorithm, Group search Optimizer GSO, is used to solve the problem. Finally, simulation experiments are used to verify the performance of the algorithm. Experimental results show that the proposed algorithm can meet the link protection needs of users and improve the resource utilization. 2) because of the increase in the number of network users and the setting up of backup resources, it is easy to lead to a low acceptance rate in a relatively small resource environment. Therefore, this paper further proposes a survivability algorithm (GSBK E-Pc-Yshare) that supports path cutting and resource sharing. This algorithm enables different links of virtual requests to share the same physical link to reduce the use of backup resources. That is, allowing two physical paths to provide backup resources for virtual links at the same time, mapping paths between devices are no longer restricted to a single path, thus greatly increasing the acceptance rate of the network. 3) in reality, multi-area network provider environments are the most common. However, most of the current research is confined to the single-area network provider environment. However, in real life, especially for network users with high data security requirements, it is difficult to meet the requirements of common single-area network mapping. Therefore, this paper proposes a survivability virtual network mapping algorithm (Int D-GRC-SVNE), which supports cross-region mapping and improves data security by mapping communication users to different area networks. At the same time, the existing new metric GRC (potential mapping ability of measuring nodes) is cited in the algorithm, which makes the load of the physical network more balanced, greatly improves the network acceptance rate, and gains higher income.
【學(xué)位授予單位】:山東師范大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類(lèi)號(hào)】:TP393.01
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