An Implementation of an Intelligent PCE-Agent-Based Multi-domain ...

An Implementation of an Intelligent PCE-Agent-Based Multi-domain Optical Network Architecture Ying Xu, Tiantian Zhang, and Renfa Li Key Laboratory for Embedded and Network Computing of Hunan Province, College of Computer Science and Electronic Engineering, Hunan University, Changsha, China, 410082 [email protected]

Abstract. This paper presents a new optical network architecture based on the PCE (Path Computation Element) by adding a PCE-Agent to intelligently control PCEs in each layer of the conventional multi-domain optical network. The PCE-Agent uses a weighted sum policy to evaluate the performance of each domain managed by a PCE in each layer for the selection of the next hop domain when establishing a P2P (Point to Point) or P2MP (Point to Multiple Points) routing path. A PA-BRPC (PCE-Agent Backward Recursive PCE-based Computation Algorithm) routing algorithm is then proposed by extending the BRPC (Backward Recursive PCE-based Computation Algorithm) algorithm in the PCE-Agent-based multi-domain optical network architecture. Compared with the traditional BRPC algorithm, our PA-BRPC algorithm based on the improved PCE-Agent architecture obtains better performance in terms of both the utilization rate of resources and the load balance of the optical network. Keywords: Path Computation Element, Multi-domain networks, PCE-Agent, BRPC.

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Introduction

With the development of the optical network communication, the multi-domain optical network topology is becoming more and more complex, and the transfer requirement of large capacity communication is increasing. The traditional optical network architecture becomes unable to meet the needs of calculating the optimal paths in optical network. Therefore, how to calculate routing paths in the multi-layer multi-domain optical network has become an important research focus in the future development of optical networks. In order to solve these problems, some protocols for the interconnection of multiple optical network domains have been proposed including Optical Border Gateway Protocol (OBGP), an optical network control protocol based on the border gateway protocol [1], External Network-to-Network Interface (E-NNI) [2], and the Path Computation Element (PCE) [3-5] and so on. At present, the main two types of routing mechanisms are the Generalized Multi-Protocol Label Switching (GMPLS) based multi-domain hierarchical routing [6-7] and the multi-domain hierarchical D.-S. Huang et al. (Eds.): ICIC 2014, LNAI 8589, pp. 375–384, 2014. © Springer International Publishing Switzerland 2014

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routing based on PCE. PCE, proposed by the Internet Engineering Task Force (IETF), has gained wide attention due to its efficiency and flexibility for computing the constrained routing paths. PCE is a functional entity in the optical network to perform the path computation. The optimal path satisfying certain constraints is calculated according to the request of the path computation client. When many service requests to the same PCE for the centralized processing result in large processing delay, so, for distributed multi-layer and multi-domain network architecture, the traditional PCEbased optical network architecture is not an ideal solution. In RFC5441, based on the PCE, IETF defines a Backward Recursive PCE-based Computation (BRPC) algorithm, which can support the multi-domain path computation based on backtracking [8]. With the known domain sequence, the algorithm of BRPC has an advantage of low complexity and can also provide the shortest path. However the algorithm does not guarantee a successful wavelength assignment. When the congestion and physical injury situation occur in the network, the algorithm of BRPC cannot timely and effectively avoid these situations. This will result in some cases that the network is blocked while there are still available resources in the network. To handle the above problem, we improve the multi-domain optical network architecture by adding a PCE-Agent to intelligently help the selection of the domain sequence by evaluating the performance of each domain controlled by a PCE for each layer. Based on the implementation of our proposed architecture, a new routing algorithm named PA-BRPC is proposed (PCE-Agent-based Backward Recursive PCE-based Computation Algorithm) by extending the BRPC algorithm. In each layer, a PCE-Agent is designed to estimate the performance of each domain when choosing the best next hop domain to build P2P or P2MP routing paths. The performance of each domain, such as the free wavelength, the available bandwidth, the average transmission delay and the blocking probability, etc., is weighted by calculating the weights of boundary nodes according to a measurement strategy. The simulation results show that our proposed algorithm can improve the resource utilization rate of the whole optical network and decrease the network blocking rate. The rest of the paper is organized as follows. In section 2, we present the relate work. Section 3 presents the proposed multi-domain optical network architecture based on PCE-Agent. Section 4 describes the proposed PA-BRPC routing algorithm. We evaluate our algorithm by experiments and summarize the obtained results in section 5. Finally, section 6 concludes this paper.

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Related Work

From the BRPC algorithm that we know how to get a good domain sequence is a crucial problem to be solved. The manner by which the sequence of traversed domains is selected has been studied in both management [9,10] and Border Gateway Protocol (BGP) [11 13] based networks. The BGP-based scheme, which has the inter-domain link traffic engineering information, can dynamically perform domain sequencing. In a BGP-based scheme, however, the lack of knowledge on intra-domain

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resource information leads to a high blocking probability, especially in networks where intra-domain and inter-domain topologies are both complicated. So a k random path (KRP)-based inter-domain routing algorithm in a hierarchical PCE architecture has been proposed [14]. The network traffic blocking performance improves because of the introduction of factor k. As k increases, the proposed algorithm achieves lower blocking probability. Compared with the traditional scheme, the proposed algorithm achieves lower blocking probability and more efficient resource utilization while preventing the increase in PCEP signaling overhead. But the KRP algorithm also has some questions such as for different large optical networks how to set the value of k to make the optimal path is still worth discussing. IETF has proposed a backtracking algorithm based on the PCE multi-domain optical network architecture. The algorithm calculates the shortest path from the source node to the destination node for the given domain sequence. The procedure is first to calculate the Virtual Shortest Path Tree VSPT from the destination node to the boundary nodes of the PCE that contains the destination node, then send the VSPT to the upper reaches of the PCE. The PCE of the upstream domain calculates the VSPT from the entrance boundary node to the outlet boundary nodes reserves the optimal path, and removes the suboptimal path which does not meet the conditions. The upstream domains repeat the above process repeatedly, until the source node's domain is found and the optimal path from the source node to the destination node is thus obtained.

（

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Fig. 1. The multi-domain optical network topology with three domains

Figure 1 shows an example calculation of a virtual shortest path from the source node S to the destination node D using BRPC. The process is as follows: the known domain sequence is Domain-A - Domain-B - Domain-C. The destination node D lies in Domain-C and the source node S lies in Domain-A.A path calculation request

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message is delivered from PCE-A, PCE-B and PCE-C in turn. The virtual shortest path tree is calculated by PCE-C from the entrance gateway and sent the results to PCE-B.PCE-B calculate the virtual shortest path tree of the Domain-B’s import gateway nodes to the export gateway nodes. Combining the results sent by PCE-C, the shortest path tree from the import gateway nodes to the destination node .Then the results are sent to the upstream PCE-A. PCE-A calculate the virtual shortest path tree from the source node S to the adjacent gateway nodes between Domain-A and Domain-B. Combining the results from PCE-B, the shortest path tree from the source node to the destination node is thus obtained. As mentioned above, the traditional BRPC algorithm assumes the domain sequence is known and has a low complexity. However, the algorithm does not guarantee a wavelength assignment for success when the congestion or physical injury situation occurs in the network. In order to balance the utilization of the network resources, this paper improves the traditional multi-layer multi-domain optical network architecture by designing a PCE-Agent-based multi-domain optical network architecture. Then a new PA-BRPC algorithm based on the designed architecture is proposed to test the effectiveness and efficiency of the new architecture.

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The Multi-domain Optical Network Architecture Based on PCE-Agent

The multi-domain optical network architecture based on PCE-Agent is the improvement of the traditional PCE architecture. PCE’s TED (Traffic Engineer Database) contains all the domain's resource information, the link resource information of the domain and the neighboring domain. for each domain, its neighboring domain is directly connected with it and the link resource information of other domains is unknown. A PCE-Agent is able to communicate with PCEs in each layer. It is designed to set the weights for the boundary nodes of each domain so that it can quantify each domain’s performance. The performance is represented by some traffic engineering information including the free wavelength, the available bandwidth, the distance between the neighboring routing domains, the average transmitting time and the blocking rate. The aim is to choose the best neighboring domain to complete the establishment of P2P or P2MP routing. By extending the existing PCEP [15] protocol, we propose a PCE-Agent-based multi-domain optical network architecture as an example shown in Figure 2. Each layer has a PCE-Agent which can communicate with all the PCEs within this layer. It is responsible for the collection and collaboration of traffic information among PCEs through the PCEP, i.e. each PCE can report the real time routing information of its domain to PCE-Agent. The multi-domain optical network architecture based on PCE-Agent can be implemented as the extension of the traditional optical network layered routing model, where a PCE-Agent is added to intelligently determine the routing paths for the multi-domain multi-layer optical networks. When a path computation request arrives, PCE-Agent will weight each domain’s performance and select the next neighboring domain to form a better domain sequence. The selected domain’s PCE calculates the shortest path using the BRPC algorithm.

An Implementation of an Intelligent PCE-Agent- Based Multi-domain

PCE-Agent

The source node The destination node

λ1 λ2

PCE-A

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PCEP

PCEP

PCEP

PCE-B

Domain-B

PCE-D PCEP

PCC

Domain-D

Domain-A

PCE-C Domain-C Fig. 2. The PCE-Agent-based multi-domain optical network architecture

The PCE-Agent-based multi-domain optical network architecture is effective with the increasing number of network domains. In Figure 2, there are four domains in the network, the source node's domain is Domain-A and the destination node is located in Domain-D. When calculating the routing path from Domain-A to Domain-D, which inter domain, i.e., Domain-B or Domain-C will be selected as the neighboring domain will be decided by the PCE-Agent considering the current traffic engineering information returned by PCE-B and PCE-C. A weighted sum policy is defined as a weighted combination W of cost, delay and packet loss rate each domain, the value of W is calculated according to the formula 1. Where C represents the network cost; D represents the delay; P represents the packet loss rate; x, y, z represent the weighs of C, D, P respectively. A domain with smaller W value has a better overall performance in terms of the current traffic information. The cost is the cost of the whole building of the link. The delay refers to the transit time of sending a message or packet from one node to another node. The packet loss rate is defined as to the percent of lost packets to the packets sent.

C* x + D* y + P *z,x + y + z =1 W = ∞ 4

(1)

The PA-BRPC Algorithm

he PA-BRPC is an extension of the traditional BRPC algorithm based on the proposed multi-domain optical network architecture based on the PCE-Agent. The domain sequence is selected according to the current traffic condition. PA-BRPC is more flexible for large scale multi-domain optical network.

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Fig. 3. The Multi-domain optical network topology with four domains

，

，

For example as shown in Figure 3 the source node is S, the destination node is G, where the source node S lays is Domain-A and the destination node lays in Domain-B. Domain-A and Domain-B have the same boundary nodes E and F, which means Domain-A and Domain-B are neighboring domains. The shortest path tree from boundary nodes to the source node S is(S-B-F), (S-A-C-E) calculated by PCEA, the shortest path tree from the source node S to the destination node is calculated as (S-B-F-G). By using the defined weighted sum policy as in Formula 1, considering the impact of the routing delay, the packet loss rate and the energy consumption simultaneously. Domain-B’s value of w is smaller than that of Domain-C. PCE-Agent thus concludes that Domain-B has better performance than that of Domain-C, and then the domain sequence is selected as Domain-A - Domain-B - Domain-D. The same BRPC procedure is applied to calculate the shortest path from the source node S to the destination node D as follows: 1, The known domain sequence is Domain-A - Domain-B - Domain-D. The destination node D lies in Domain-D and the source node S lies in Domain-A. A path calculation request message is delivered from PCE-A, PCE-B and PCE-D in turn. The virtual shortest path tree is calculated by PCE-D from the entrance gateway O and P to the destination node D, i.e. O-D, and the results are sent to PCE-B. 2, PCE-B calculates the virtual shortest path tree of the Domain-B’s import gateway E and F to the export gateway nodes O and P: E-G-H-O, F-G-H-O, and F-IO. Combining the results sent by PCE-D, the shortest path tree from the import gateway nodes to the destination node is E-G-H-O-D and F-I-O-D. Then the results are sent to the upstream PCE-A. 3, PCE-A calculate the virtual shortest path tree from the source node S to the adjacent gateway nodes E and F between Domain-A and Domain-B is S-A-C-E and S-B-F. Combining the results from PCE-B, the shortest path tree from the source node to the destination node is S-B-F-I-O-D in this example.

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The Analysis of Simulation Results

Based on the proposed PCE-Agent-based multi-domain optical network architecture, we use Matlab as the simulation software to build the experimental platform to test the performance of our proposed PA-BRPC algorithm. The network topology with 17 random nodes the simulation model is built in a square area of the 100*100. Each node’s location coordinate is recorded, based on the geographical location, the network topology is divided based on K-means clustering method (MacQueen, 1967) is one of the simplest unsupervised learning algorithms that solve the well-known clustering problem. The procedure follows a simple and easy way to classify a given data set through a certain number of clusters (assume k clusters) fixed a priori. The main idea is to define k centroids, one for each cluster. These centroids should be placed in a cunning way because of different location causes different results [16]. The link bandwidth and the node energy are randomly generated in a certain range. The delay value represents the distance between two points divided by 2/3 speed of light, packet loss rate is randomly selected between 0 ~ 0.01. Three parameters (x, y, z) are used to describe the characteristics of each network topology as defined in formula (1). In order to investigate the effectiveness of the PA-BRPC algorithm, three different types of multi-domain optical network topologies as shown in Figure 5, Figure 6 and Figure 7 have been used as the test instances. We compare three algorithms including the traditional BRPC algorithm the KRP algorithm and our proposed PA-BRPC algorithm based on the designed multi-domain optical network simulation platform. All the experiments are repeated 30 times on each network topology for each algorithm. The experimental results are shown in Figure 7, 8, 9, 10, 11 and 12.

，

Fig. 4. The network topology A

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Fig. 5. The network topology B

Fig. 6. The network topology C

Fig. 7. The Packet Loss on the topology A

Fig. 8. The Delay on the topology A

Fig. 9. The Cost on the topology A

Fig. 10. The Delay on three topologies

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Fig. 11. The Cost on three topologies

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Fig. 12. The Packet Loss rate on three topologies

The simulation results show that the adding of PCE-Agent in the multi-domain optical network architecture improves the utilization rate of resources in the optical networks. From Figure 7, 8 and 9, we can see that for most cases, the average delay, packet loss rate, cost obtained by the proposed PA-BRPC algorithm is better than those of the other two algorithms on the network topology A. The comparisons of three network parameters (i.e. the average delay, the packet loss rate and cost) on the three network topologies are shown in Figure 10, 11 and 12. Experimental results show that the PA-BRPC algorithm has the best overall performance than both the traditional BRPC algorithm and the KRP algorithm in terms of the average delay, the packet loss rate and cost on the three network topologies.

6

Conclusions

In this paper, we propose a new multi-domain optical network architecture based on the Path Computation Element (PCE) by adding a PCE-Agent to intelligently control PCEs in each layer of the conventional multi-domain optical network. In order to quantify each domain’s network performance, the PCE-Agent is designed to intelligently set the weights for the boundary nodes of each domain, which can be helpful for choosing the best neighboring domain when building the P2P or P2MP routing paths in the multi-domain optical networks. Then, a PA-BRPC routing algorithm is proposed based on the PCE-Agent-based multi-domain optical network architecture. The simulation results indicate that network performance is improved because of the introduction of PCE-Agent. Compared with the traditional BRPC algorithm and the KRP algorithm, the proposed algorithm achieves lower blocking probability and more efficient resource utilization. This work can be further extended for solving the multicast routing problem in multi-domain multi-layer optical networks.

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Acknowledgment. This research is supported by Natural Science Foundation of China (NSFC project No. 61202289) and the project of the support plan for young teachers in Hunan University, China (Ref. 531107021137).

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