Although the existing networks are more often deployed in the multidomain environment, most of existing researches focus on single-domain networks and there are no appropriate solutions for the multidomain virtual network mapping problem. In fact, most studies assume that the underlying network can operate without any interruption. However, physical networks cannot ensure the normal provision of network services for external reasons and traditional single-domain networks have difficulties to meet user needs, especially for the high security requirements of the network transmission. In order to solve the above problems, this paper proposes a survivable virtual network mapping algorithm (IntD-GRC-SVNE) that implements multidomain mapping in network virtualization. IntD-GRC-SVNE maps the virtual communication networks onto different domain networks and provides backup resources for virtual links which improve the survivability of the special networks. Simulation results show that IntD-GRC-SVNE can not only improve the survivability of multidomain communications network but also render the network load more balanced and greatly improve the network acceptance rate due to employment of GRC (global resource capacity).
Network virtualization enables multiple virtual networks (VNs) to coexist on the same physical network dynamically, so that virtual network users can share the underlying physical network [
This paper refers to the relevant algorithms in the literature [
This paper is organized as follows: we review related work in Section
As the core of network virtualization technology, the goal of virtual network mapping is to provide node and link resources for dynamic virtual requests to meet their mapping service requirements. However, with the number of network users climbing, the user requirements for the stability of the network are getting higher and higher. In order to improve the survivability of the network, many researchers have done some researches and most of the current researches focused on both protection and backup [
Physical failure is generally divided into node failure and link failure. In order to deal with physical link failure, Rahman et al. [
In order to guarantee the survivability of VN under the influence of physical node failure, Yu et al. [
The number of researches in the literature on the protection of node data is still relatively small, especially in the event of a major natural disaster such as earthquakes and tsunamis which may lead to domain network failure and serious loss of node data in a moment [
In this section, we first give a multidomain underlying physical network, virtual request network model, and their formal descriptions. Then we give a description of survivable virtual network mapping algorithm that supports multidomain mapping.
The underlying network topology is marked as a weighted undirected graph
Subnetwork 1 node information.
Physical node | Coordinate position |
Computing resources, CPU |
---|---|---|
|
(57, 54) | 57 |
|
(36, 46) | 39 |
|
(47, 60) | 34 |
|
(40, 11) | 24 |
|
(37, 33) | 25 |
Subnetwork 2 node information.
Physical node | Coordinate position |
Computing resources, CPU |
---|---|---|
|
(67, 74) | 57 |
|
(76, 66) | 39 |
|
(65, 60) | 34 |
|
(70, 81) | 24 |
|
(77, 63) | 25 |
Link resource information.
Link serial number | Link available bandwidth resources (bw) | Interdomain communication link (Y: 1, N: 0) |
---|---|---|
1 | 74.827859 | 0 |
2 | 83.370701 | 0 |
3 | 77.140495 | 0 |
4 | 95.433926 | 0 |
5 | 66.452354 | 0 |
7 | 69.448338 | 0 |
8 | 56.235293 | 1 |
9 | 57.188120 | 0 |
10 | 77.287520 | 1 |
11 | 54.428015 | 0 |
12 | 96.737798 | 0 |
13 | 88.669225 | 0 |
14 | 81.164182 | 0 |
15 | 60.910143 | 1 |
16 | 51.048862 | 1 |
17 | 79.065118 | 0 |
Physical network.
As shown in Figure
There are two types of physical links: the interdomain link which is used to complete the interdomain communication and the intradomain link in a single-domain network which is used to complete intradomain communication. No matter what kinds of underlying links are there and how many virtual links can be mapped, the substrate connection is a physical communication channel between two substrates nodes.
The undirected graph of the virtual network request is similar to the undirected graph of the underlying network. The network topology map is marked as a weighted undirected graph
Virtual network node information.
Virtual node | Coordinate position ( |
Resources required, CPU | Distance limit (Lim_Dis) |
---|---|---|---|
|
(55, 50) | 10 | 75 |
|
(37, 40) | 35 | 60 |
|
(80, 96) | 20 | 40 |
Resource requirements of virtual links.
Link serial number | Link bandwidth resources required (bw) |
---|---|
1 | 74.827859 |
2 | 83.370701 |
3 | 77.140495 |
Virtual request.
As shown in Figure
The lines identified as 1 and 2 are virtual links which are logical interconnections between virtual nodes. For a viutual network, the function of virtual link is to connect directly with the physical network and dynamically display the user’s resource requirements.
In the node mapping phase, the corresponding mapping nodes need to be found on the underlying physical network for each virtual node. In general, all physical nodes with more resources than the resources required by the virtual node can be used as candidate nodes for virtual nodes. In this paper, we obtain the unit of measurement
In (
The calculation of GRCS for all nodes using the vector format can be defined as follows:
where
The primary evaluation index of the network is defined as follows:
In (
In (
In (
Link pressure is divided into two parts, the primary flow link pressure and backup flow link pressure. As the former is used to provide link resources under the normal service of the network, the latter is used to provide backup link resources for network failure. In (
In (
Virtual network mapping problems are generally defined as mapping:
As shown in Figure
Network mapping.
In order to minimize the geographical coordinates caused by the failed mapping and improve the acceptance rate of the network, the proposed IntD-GRC-SVNE in this paper supports multidomain network mapping, so we can find a feasible physical node in the network outside subnetwork 1. For example, as shown in Figure
As the nodes are mapped in different domain subnetworks, when a major accident happened in a subnetwork, such as earthquakes, floods, or other large natural disasters, mapping in different domain subnetworks can effectively avoid the loss of data and improve the security of the data.
As shown in Figure
At the same time, in order to prevent the impact of link failure, IntD-GRC-SVNE sets the primary resources and backup resources and the proportion of the former is
The network mapping process is shown in Figure
Based on the description of the network mapping problem in Section
In (
The goal of the algorithm in this paper is to achieve greater revenue by improving the acceptance rate of the network as much as possible in the case of satisfying the requirement of users. The relevant constraints of this algorithm are as follows (see (
Resource capacity limits of primary flows and backup flows of intradomain physical link and interdomain physical link are as follows:
Resource capacity limits of primary flow and backup flow of virtual network link are as follows:
In (
The primary and backup flow resource cannot be crossed:
Range of variables is as follows:
In (
The implementation of this algorithm is in accordance with the order of arrival of the events. At different time points, the algorithm will deal with different events which include two types of virtual network requests: the new virtual request waits for service and the virtual request leaves after service has been completed. The algorithm flow will not be completed until all the events have been processed.
In Figure
Flow chart of network mapping.
Flow chart of searching a mapping scheme in multidomain environment.
The survivable virtual network mapping algorithm (GRC-SVNE) is described in Algorithm
( ( ( ( ( ( ( ( ( (
( (
( ( ( ( ( (
( ( ( ( ( (
(25) (26) (27) (28) (29)
(30) (31) (32) (33) (34) (35) (36) (37) (38) (39)
(40)
In this paper, the topology and location information of the network are randomly generated by the GT-ITM tools. The underlying network topology which consists of six domain subnetworks includes 100 nodes and 570 links. The node CPU resource and bandwidth resource in each domain subnetwork obey a uniform distribution of 50–100. The rest of the parameters involved in the paper are shown in Table
Simulation parameters.
Node number of the substrate network | 100 |
Link number of the substrate network | 570 |
Initial available computing resources on substrate nodes | 50–100 units |
Initial available bandwidth resources on substrate links | 50–100 units |
Average lifetime of the VNRs | 500 time-units |
Bandwidth demand of a virtual link | 0–50 units |
Computing resource demand of a virtual node | 0–50 units |
Node number in a VNR | 10–25 |
|
0.5 |
|
0.5 |
Resource information for each domain subnetwork.
Domain network serial number | Number of nodes | Number of links |
---|---|---|
0 | 19 | 38 |
1 | 16 | 34 |
2 | 15 | 27 |
3 | 17 | 32 |
4 | 18 | 38 |
5 | 15 | 26 |
Interdomain link number information.
Domain subnetworks |
Domain subnetworks |
Number of communication links |
---|---|---|
0 | 1 | 24 |
0 | 2 | 34 |
0 | 3 | 22 |
0 | 4 | 21 |
0 | 5 | 9 |
1 | 2 | 23 |
1 | 3 | 29 |
1 | 4 | 8 |
1 | 5 | 18 |
2 | 3 | 28 |
2 | 4 | 42 |
2 | 5 | 28 |
3 | 4 | 22 |
3 | 5 | 37 |
4 | 5 | 30 |
We assume that the number of virtual network requests arriving in 100 time-units obeys the
As IntD-GRC-SVNE supports multidomain virtual network mapping, in order to improve the network load balancing, the algorithm uses the existing metric GRC that measures the potential mapping capability of physical nodes to select the more reasonable nodes as the mapping nodes in node mapping phase. In addition, in order to demonstrate the performance of the algorithms in multidomain networks, this paper applies the traditional random algorithm (named as IntD-RANDOM-SVNE in experimental results) and greedy algorithm (named as IntD-GREEDY-SVNE in experimental results) to multidomain network environment. The acceptance rate, average cost, and long-term revenue of the experimental comparison results between the three algorithms are shown in Figures
Acceptance rate.
Network costs.
Node pressure variance.
As shown in Figure
In addition, the algorithms used in this paper preferentially look for mapping nodes in different network domains. So IntD-RANDOM-SVNE, IntD-GREEDY-SVNE, and IntD-GRC-SVNE have higher data security guarantees than those algorithms previously mapped in a single-domain network environment.
As shown in Figure
In general, the network cost consists of two parts: the node resource and the link resource. In the context of this experiment, the link resource includes the primary flow resource and the backup flow resource. In the case of its highest acceptance rate, the network cost of IntD-GRC-SVNE is still lower compared with the other two algorithms; this can fully show the rationality of the mapping scheme. As IntD-GRC-SVNE can not only realize the multidomain mapping to meet the data security requirements but also make network costs lower when compared to the traditional algorithms IntD-GREEDY-SVNE and IntD-RANDOM-SVNE in the same multidomain network environment, the above experimental results and analysis demonstrate the practicality of IntD-GRC-SVNE proposed in this paper.
Figure
Similar to the node pressure variance, Figure
Link pressure variance.
There is also something that is worth emphasizing: because virtual requests are mapped across different domain networks, single-domain communication congestion is avoided. This also improves the load balancing of the network compared to the previous single-domain network mapping algorithm.
As shown in Figure
Average network revenue.
In general, the mapping of virtual requests in different subnetworks can avoid the sudden termination of service due to domain disastrous paralysis of the network. Although the experimental results cannot directly reflect the algorithm to improve the security of the data as the three algorithms support multidomain network mapping to ensure the consistency of mapping conditions, in practical applications, there is no doubt that the virtual request mapping in multidomain network environment will improve data security.
After summarizing the existing research on network survivability and node data security, this paper proposes a survivable virtual network mapping algorithm (IntD-GRC-SVNE) that supports multidomain network mapping. A new metric, GRC, is used to represent the potential mapping capability of the node in the node selection phase. In order to facilitate the comparison of the experimental results, this paper has applied the existing greedy algorithm and random algorithm to the multidomain network environment, which are called IntD-RANDOM-SVNE and IntD-GREEDY-SVNE, respectively, in experimental results. The simulation results show that IntD-GRC-SVNE proposed in this paper not only realizes the multidomain mapping but also improves the survivability of the network. When compared with the two traditional algorithms, the acceptance rate, the network load, and the network revenue of IntD-GRC-SVNE embody the obvious advantages.
Further work mainly focuses on the following two aspects: (1) studying IntD-GRC-SVNE’s adaptability in different physical network environments and the impact of physical resources on algorithm performance and (2) studying the multidomain network problem and attempting to reduce the impact of network services failure.
The authors declare that they have no conflicts of interest.
The authors are grateful for the support of the National Natural Science Foundation of China (61373149 and 61672329).