A New Fault Tolerant Routing Algorithm For GMPLS/MPLS Networks

Transcription

1 A New Fault Tolerant Routing Algorithm For GMPLS/MPLS Networks Mohammad HossienYaghmae Computer Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran and Fahimeh Jafari Computer Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran Abstract In this paper we present a new two steps Quality of Services (QoS) routing algorithm for GMPLS/MPLS networks. The proposed algorithm considers different input parameters including: QoS parameters, the failure probability parameter and the failure impact parameter of the GMPLS/MPLS networks. The main objective of this work is design and performance evaluation of a new routing algorithm in order to minimize the failure probability and the failure impact. The proposed model is not dependent to any specific QoS routing algorithm, but in the present study we use the Wang-Crowcroft algorithm []. Our proposed model consists of two modules. The first module is responsible to find the best path with respect to three constraints including: bandwidth, delay and link failure probability. In the second module depending on the state of the selected working path, the fault link probabilities and the requested protection level, a specific choice between different protection methods should be made. Based on computer simulation results, it can be seen that the proposed model has better performance than the Wang-Crowcroft algorithm. Keywords: GMPLS networks, MPLS networks, Quality of Services (QoS) routing, Traffic Engineering (TE), Fault tolerant. Introduction The IETF proposed the Multi-Protocol Label Switching (MPLS)[2], as a new technology for the high speed networks. It uses the benefits of IP routing and ATM switching, simultaneously. The promise of MPLS is to speed up the packet forwarding and to provide the traffic engineering in the IP networks. To accomplish this, the connectionless operation of IP networks becomes more like a connection-oriented network where the path between the source and the destination is pre-calculated based on user specified parameters. To speed up the forwarding scheme, an MPLS device uses label swapping technique. Furthermore, to provide traffic engineering, tables are used that represent the levels of quality of service. The tables and the labels are used together to establish an end-to-end path called the Label Switched Path (LSP). MPLS uses the traditional IP routing protocols (e.g., Open Shortest Path First (OSPF), Intermediate System to Intermediate System (IS IS)) and the extended version of signaling protocols (e.g., Resource Reservation Protocol (RSVP), Constraint-Based Routing Label Distribution Protocol (CR LDP)). The IP based MPLS networks are capable of providing advanced services such as bandwidth-based guaranteed service, priority-based bandwidth allocation, and preemption services. For each specific service, a table of Forwarding Equivalence Class (FEC) is created to represent a group of flows with the same traffic engineering requirements. A specific label is then bound to an FEC. In this type of networks, a Label Switching Router (LSR) does not need to examine the IP headers of the packets to find an output port (next hop). An LSR simply strips off the existing label and applies a new label for the next hop. On the other hand, the emergence of optical transport systems has dramatically increased the raw capacity of the optical networks and has enabled a slew of new, sophisticated applications. For example, network-based storage, P60/

2 bandwidth leasing, data mirroring, Add/Drop Multiplexing (ADM), Dense Wavelength Division Multiplexing (DWDM), Optical Cross-Connect (OXC), Photonic Cross-Connect (PXC), and multi-service switching platforms are some of the devices that may make up an optical network and are expected to be the main carriers for the growth in data traffic. The diversity and complexity in managing these devices have been the main driving factors in the evolution and enhancement of the MPLS suite of protocols to provide control for not only packet-based domains, but also time, wavelength, and space domains. The Generalized MPLS (GMPLS) [3,0] extends MPLS to provide the control plane (signaling and routing) for devices that switch in any of these domains: packet, time, wavelength, and fiber. This common control plane promises to simplify network operation and management by automating end-to-end provisioning of connections, managing network resources, and providing the level of QoS that is expected in the new, sophisticated applications. The deployment of GMPLS based nodes allows carriers to automate the provisioning and management of the network [8]. One of the major subjects about GMPLS is the failure recovery mechanism. There are two types of recovery mechanism in the GMPLS networks [4,9]: protection and restoration. A dedicated protection path is established for a connection in advance. When a failure occurs on the primary path, the connection is switched from the working (primary) path to the protection (backup) path. In the restoration mechanisms, the establishment of a backup path does not occur until a failure occurs in the primary path. After failure, the traffic is switched to the backup path. Note that in the restoration mechanism, the backup path can be selected (calculated) in advance. Restoration and protection are different mechanisms. They operate on different time scales; protection requires redundancy of resources, while restoration relies on dynamic resource reservation, hence restoration takes more time. Figure shows the classification of the GMPLS recovery mechanisms. GMPLS Recovery Mechanisms Protection Restoration Local Global Local Global Figure. The GMPLS recovery mechanisms The objective of local recovery is to protect against a link fault and to minimize the amount of time required for fault notification. The local recovery is initiated by the upstream node of the faulty link, which may be a transit node or the source node of the LSP. The objective of the global recovery is to protect against any link fault on a LSP or on a segment of the LSP. The global recovery is also called end-to-end path recovery, because only the source or destination node initiates the recovery process [4,9]. The recovery mechanisms can be used in any network that may have different switching technologies at any level of the GMPLS hierarchy, for instance, ATM networks, IP networks, optical (e.g., OXCs) network, etc [5-6]. The GMPLS networks support the following recovery models: The global backup model: In this model, the ingress node has the responsibility of the fault recovery. In the global backup model, protection is always activated at the ingress node, irrespective of where a failure occurs along the working path and each working path has an alternate disjoint backup path. There is a packet loss proportional to the required recovery time but this is a common drawback in all recovery models. The reverse backup model: The main objective of this model is to reverse traffic at the point of a failure back to the source switch of the protected path (ingress node) via a reverse backup LSP. There is pre-established alternative path to avoid packet loss. In this model, as soon as a failure along the protected path is detected, the LSR at the ingress of the failed link reroutes incoming P60/2

3 traffic and packets could continue to be sent along the primary path but they are redirected into the alternative LSP traversing the path in the reverse direction of the primary LSP. This method is very suitable in network where the traffic is very sensitive to packet losses. The local backup model: The main objective of this model is to offer low recovery time that imply on low packet loss. In this model, fault recovery starts from the point of the failure. This method has faster restoration time than another methods but it is difficult to maintain and create of multiple LSP backups, meaning low resource utilization and high management complexity. The segment backup model: This method is an intermediate solution of local backup. It is only for segments where a high degree of reliability is required. This model has lower recovery time (and lower packet loss) than global/reverse model. The + model: In this model, there are two working paths. After failure, the selector LSR detects that there is only one path and selects this path as the working path. This method has no notification times and no packet losses but it uses high resource consumption. The structure of the reminder of this paper is as follow. In section 2, we describe our proposed model in details. The simulation results are given in section 3. Finally section 4 concludes the paper. 2. The Proposed Model In this section we present our proposed routing algorithm for GMPLS/MPLS networks. The proposed algorithm uses different input parameters including: the QoS parameters, the failure probability parameter and the failure impact parameter of the GMPLS/MPLS networks. The main objective of this paper is design and performance evaluation of a new routing algorithm in order to minimize the failure probability and the failure impact. There is a tradeoff between reducing the failure impact and reducing the failure probability. For instance, reducing the failure probability may imply increasing the notification time, and therefore increasing the failure impact. In fact, reducing both the failure probability and the failure impact could imply more resource consumption. We use the Residual Failure Probability (RFP) parameter and the notification distance parameter for the failure probability and the failure impact, respectively. In the next subsections, we explain the failure probability and failure impact parameters which are used in our proposed model, then we explain our proposed algorithm in details. 2.. Failure Probability As the calculation of the exact failure probability of a network segment is difficult, an approximate value can be obtained. As shown in figure 2, consider a LSP with K different links. The LSP failure probability (LSP_FP) can be obtained as bellow: [7] 2 3 K- K LFP () LFP (2) LFP (K-) Figure 2: LSP failure probability LSP _ FP = K i= ( LFP i ) It is assumed that all LFPs are known and are independent of each other. When the LFPs of all links are small (LFP<<) and the number of links (K) is not very large, then the LSP failure probability is calculated as bellow: P60/3

4 LSP _ FP = K i= K ( LFP i ) LFP i= i The above formula is corrected when the working path is not protected. In this case the RFP of this path is K computed as: RFP = LFP i.figure 3 shows an example which a portion of the working path is protected. In i= this case the RFP of the total path can be obtained as bellow: LSP_FP (4-7-6) LFP () LFP (2) LFP (3) LSP_FP (4-5-6) Figure 3: The RFP of a protected path RFP = LFP + LFP 2 + LFP 3 + LSP _ FP(4 6) LSP _ FP(4 6) = LSP _ FP(4,5,6) * LSP _ FP(4,7,6) 0 As the LSP _ FP(4,5,6) and LSP _ FP(4,7,6) are very small, thereby the LSP _ FP(4 6) is negligible and assumed to be zero. In this case the RFP of the path is calculated as: RFP = LFP + LFP2 + LFP3. Consequently, if the path is protected, the residual failure probability is negligible (for simplicity it is assumed to be zero). When a working path consists of both protected and non-protected paths, then the residual failure probability is calculated as the sum of all the non-protected link failure probabilities Failure Impact The failure impact is evaluated after a failure occurs in the protected segment. The failure impact is proportional to the failure recovery time. The failure recovery time is proportional to the notification time. Furthermore, the notification time is proportional to the notification distance [7]. Consequently, the failure impact can be evaluated based on the notification distance parameter. To make a tradeoff between reducing the failure impact and reducing the failure probability, with respect to resource consumption, the state of selected working route should be detected Structure of the Proposed Model As the two-step routing algorithm give us a better choice respect to one step routing algorithm, we use it to establish the working and backup paths. In figure 4 the structure of the proposed model is shown. P60/4

5 QoS parameters Link failure probabilities State of selected working route Two-step routing algorithm Working path with requested protection level Traffic class type protection level Figure 4. The structure of proposed model The proposed model is not dependent to any specific QoS routing algorithm, but in the present study we use the Wang-Crowcroft algorithm []. Our major objective is to modify the Wang-Crowcroft algorithm and enhance it in such a way that satisfies the appropriate protection level. The details of our proposed two steps routing algorithm are shown in figure 5. QoS parameters Link failure probabilities Module : WP routing State of selected WR Traffic class type protection level Module 2: Select the appropriate protection method Figure 5. The details of the proposed two steps routing algorithm As shown in this figure, the proposed model consists of the following two major modules: Module : This module is a modified version of the Wang-Crowcroft algorithm, which considers the failure probability as a third parameter. In the proposed algorithm, at first all routes with bandwidth less than requested bandwidth are eliminated, then routes that have appropriate delay are selected. In the third step, the best path with respect to minimum hop and link failure probabilities is chosen. Module 2: In this module depending on the state of the selected working path, the link failure probabilities and the requested protection level, a specific choice between different protection methods should be made. The selected protection type is also depended on the type of traffic class. This module is useful to take into account the state of the working path in order to select the working path with the appropriate protection requirements. P60/5

6 The high level description of our proposed QoS routing algorithm used in module, is summarized as bellow: ) Prune the topology graph from these links: Suppose that (i,j) is the link between nodes i and j. a) if Bandwidth(i,j) < Bandwidth constraint, then delete (i,j) from topology graph. b) if Delay(i,j) > Delay constraint then delete (i,j) from topology graph c) if (Delay(i,j)==Delay Constraint) &&!(i == source node && j== destination node) then delete(i,j) from the topology graph d) if node i is of degree (i has only one neighborhood, j ) &&!((i == source node && j == destination node) (i == destination node && j == source node)) then delete (i,j) from the topology graph. 2) Assign link s delay to their cost and find the shortest path using Dijkstra s algorithm. 3) if there are no feasible path, reject the request, but if there are more than one feasible path, select the path with the minimum hop. 4) if there are more than one feasible path, select the path with the minimum residual failure probability (RFP). 3. Performance Evaluation In this section, by using the computer simulation we compare the performance of our proposed QoS routing algorithm with that of Wang-Crowcroft algorithm. For this purpose we developed a discrete event call simulator in C++ environment. The evaluation parameters are: the RFP of selected paths and the number of failed active paths. The network topology used in the simulation is shown in figure 6. The bandwidth and the propagation delay of all links are given in table Figure 6. The network topology used in the simulation In the simulation, a random value of LFP is assigned to each network s link. We consider two different scenarios as bellow: Scenario: In this scenario, the links failure probabilities are set in interval [0 5 2 و 0 ]``. Six consequent calls are arrived to source node 0. The destination of all input calls is node. In table 2, for both Wang- Crowcroft and proposed algorithms, the status of the arrived calls and the RFP of the selected paths are given. Based on results shown in table 2, it is clear that the proposed algorithm selects paths with minimum residual failure probabilities. P60/6

7 Link BW (Mb/s) Table. The link s bandwidth and propagation delay Link BW delay (ms) Link (Mb/s) delay (ms) BW (Mb/s) delay (ms) Call no. BW (Mb/s) Table 2. Simulation results for scenario 2 ( LFP [0 5 و 0 ]) dealy (ms) Wang-Crowcroft algorithm Proposed algorithm Call status RFP of Call status RFP of selected selected path path Accept Accept Accept Accept Accept Accept Accept Accept Reject - Accept Accept Accept To evaluate the performance of the proposed model in a faulty network, some random faults are applied to the network. In figure 7, for both Wang-Crowcroft and proposed algorithms, the number of failed active paths is plotted versus the number of faults in the network. It can be seen that by increasing the number of faults in the network, for both mechanisms the number of failed active paths is increased too. Based on the results shown in this figure, it is clear that the proposed algorithm has better fault tolerance than the Wan-Crowcroft algorithm. P60/7

8 For example, when 5 faults occur in the network, for the Wang-Crowcroft algorithm, 5 active paths are failed while for the proposed algorithm, only 2 active paths are failed. Number of failed active paths Wang-Crow croft Proposed Number of faults Figure 7. The number of failed active paths versus the number of faults Scenario2: In this scenario, in comparison to scenario, we choose a greater interval ([0 5 و 0 ] ) for the LFP of each link. We expect a better performance for our proposed algorithm. Like scenario, 6 consequent calls are arrived to the network. The simulation results are given in table 3. Call no. BW (Mb/s) Table 3. Simulation results for scenario ( RFP [0 5 و 0 ] ) dealy (ms) Wang-Crowcroft algorithm Proposed algorithm Call status RFP of Call status RFP of selected selected path path Accept Accept Accept Accept Accept Accept Accept Accept Reject - Reject Accept Accept In figure 8, for both Wang-Crowcroft and proposed algorithms, the number of failed active paths is plotted versus the number of faults in the network. Like scenario, it can be seen that the performance of the proposed model is better than that of Wang-Crowcroft algorithm. For example, when 5 faults occur in the network, for Wang-Crowcroft and proposed algorithms, the number of failed paths are 7 and, respectively. So in this scenario our proposed model has 6 failed active paths less than Wang-CrowCroft algorithm. 4. Conclusion The GMPLS networks, support not only devices that perform packet switching, but also those that perform switching in the time, wavelength, and space domains. The development of GMPLS requires modifications to current signaling and routing protocols. In this paper we presented a novel two steps quality of services routing algorithm for GMPLS/MPLS networks. The main objective of the proposed model is to minimize the failure probability and the failure impact. The proposed model consists of two modules. The first module is responsible to find the best path with respect to three constraints including: bandwidth, delay and link failure probability. In the second module depending on the state of the selected working path, the failure link probabilities and the requested protection level, a specific choice between different protection methods should be made. Simulation P60/8

9 results confirmed that the proposed model has a good performance. Currently we are working to develop and implement the module 2 of the proposed model. Number of failed active paths Wang-Crow croft Proposed Number of faults Figure 8. The number of failed active paths versus number of faults References [] Z. Wang and J. Crowcroft, QoS Routing for Supporting Multimeda Application, IEEE Journal on Selected Areasin Communications, 996 [2] Rosen, A.Viswanathan, R.Callon, Multiprotocol Label Switching Architecture, RFC 303, Jan 200. [3] Generalized Multi-Protocol Label Switching Architecture IETF draft-ietf-ccamp-gmpls-architecture- 07.txt [4] Ziyng Chen The LSP Protection/Restoration Mechanism in GMPLS, October 2003 [5] Changcheng Huang, Vishal Sharma, Ken Owens, Srinivas Makam, Building reliable MPLS Networks using a path protection mechanism, IEEE Communications Magazine, March 2002 [6] V. Sharma, B. M. Crane, S. Makam, K. Owens,C. Huang, F. Hellstrand, J. Weil, L. Andersson, B. Jamoussi, B. Cain, S. Civanlar, A. Chiu. "Framework for MPLS-Based Recovery". RFC3469. February [7] Eusebi Calle, Jose L Marzo Enhanced fault recovery methods for protected traffic services in GMPLS networks Girona, February 2004 [8] Control Plane architecture in GMPLS Networks, draft-shiomoto-ccamp-cplane-architecture-00.txt, October 2003 [9] Generalized MPLS Recovery Functional Specification, IETF draft-ietf-ccamp-gmpls-recovery-functional- 0.txt [0] Generalized Multi-Protocol Label Switching :An Overview of Signaling and Management Enhancement and Recovery Techniques Ayan Banerjee, et.al P60/9