Robust Routing in Load-Balancing WDM Networks to ...

Robust Routing in Load-balancing WDM Networks to Cope with Multiple Failures Rui Dai, Lemin Li, Sheng Wang, Xiaoning Zhang Key Lab of Broadband Optical Fiber Transmission and Communication Networks, University of Electronic Science and Technology of China Chengdu, 610054, China {dairui, lml, wsh_keylab, xnzhang}@uestc.edu.cn Abstract—We address the issue of traffic-oblivious routing (i.e., robust routing) in WDM networks dealing with both link and node failures under load-balancing architectures. Two distinct schemes are proposed. One is static with the goal of minimizing total network cost given a set of multiple failures. The other considers dynamic network environment (i.e., connection requests arrive one after another), and is designed against the failures aiming at the maximum network throughput. We manifest by simulation that both of these two schemes perform better than the previously proposed protection schemes as well as the unprotected ones.

I.

INTRODUCTION

Wavelength division multiplexing (WDM) captures comprehensive acceptance in meeting the bandwidth requirements of nowadays booming telecommunication and Internet services. On the other hand, the ubiquitous and rapidly emerging packet traffic (e.g., IP, MPLS, etc) running over WDM networks have inevitably caused extreme dynamism and uncertainty in traffic patterns. This necessitates the equipment of sophisticated methods to infer and forecast traffic matrices at design time, which leads to significant operation complexity. Considerable research interest has been fastened on providing predictable performance for highly variable traffic demand profiles and accommodating failures in an effective manner. Of all the relative papers and documents, the Valiant Load-balancing (VLB) [1] [2] robust routing scheme based on hose model [6] (which confines the traffic information to the total traffic entering/leaving each network node rather than a precise traffic matrix) is a promising choice for hitting both robustness and simplicity targets in realization. In VLB, a logically full-mesh topology is established (Fig.1 (a)) and all traffic demands are routed in two phases (hops): in the first phase a source splits its traffic demand to a set of intermediate (hub) nodes in predetermined proportions (called traffic distribution fractions); in the second phase all intermediate nodes route the received traffic demands to their own destination nodes. When VLB is applied to WDM networks, a two-hop IP/MPLS over WDM architecture is introduced, where each link in Fig.1 (a) is a circuit connected by a set of optical crossconnects (OXC). All traffic demands are routed in these circuits during each phase of routing, only

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Figure 1. (a) Logical topology of VLB (b) Logical topology of SRLB when node 1 and node 2 are selected as intermediate nodes

the IP/MPLS routers of intermediate nodes forward the received traffic to their destinations using the circuits. VLB is congestion-free for any traffic matrices under hose model constraints (called valid traffic matrices) immune from any dynamic or real-time configuration of the network. Besides, it renders notable performances for link and node failures [4] [5]. Despite many of its merits, VLB induces time-of-flight differences and prolonged latency because all network nodes act as intermediate nodes for all flows or packets. To debase these flaws, authors of [3] proposed an improved scheme SRLB (selective randomized load-balancing) (Fig. 1(b)). It inherits the properties of VLB but selects a portion of network nodes producing less cost path trees as intermediate nodes, thus outperforms VLB in cost, delay and jitter. In this paper, we devote to VLB (SRLB) robust routing in WDM networks against multiple failures (including the failure of fibers, OXCs and IP routers) under a wide range of valid traffic matrices. This is due to the following factors. First, in VLB (SRLB), even the failure of one intermediate node will disable the accomplishment of traffic routing for each network node pair because of all traffic flows being split to traverse all intermediate nodes. Second, since a wavelength channel in WDM networks has a transmission of several gigabits or more [7], a large amount of connection requests will suffer a high risk of being blocked if a fiber or an OXC fails. Third, the IP router is shown to be more unreliable than traditional carrier-grade switches [8], so it is imperative to devise a robust scheme against router failures. We contemplate this issue in two aspects: 1) given a set of multiple failures, how to build a congestion-free and economical network, and then efficiently route the traffic

This research is supported by the National Key Basic Research Program of China (973 Program 2007CB307104 of 2007CB307100), the National Natural Science Foundation of China (NSFC) under grant No.90604002, and Program for New Century Excellent Talents in University (NCET) under grant No. 05–0807.

978-1-4244-2324-8/08/$25.00 © 2008 IEEE. This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE "GLOBECOM" 2008 proceedings.

demands in the pre-configured network? 2) Given a set of constraints on network resources, such as a limited number of transceivers, wavelength channels and wavelength converters, how to determine the route for the dynamic traffic demands (i.e., the traffic demands might come and go) in the current scenario 1 , so as to achieve a desirable throughput? Upon the first sub-issue, Zhang-Shen et al. [4] proposed an approach to design fault-tolerant backbone networks with uniform load-balancing (ULB)(i.e., each node equally splits its traffic flows to all the intermediate nodes). However, they addressed the failure of (logical) links and nodes for logically full-mesh networks other than taking physical topologies into consideration. This leads to a considerable over-provisioning of network resources when applied to large mesh networks, as a slight difference from the optimal solution may result in a notable waste of bandwidth. Ref. [12] is closer to our work, where the authors studied pre-configuration of IP-over-Optical networks against single router failures under VLB architecture, but it is restricted to node protection on IP layer without considering the features of WDM networks. There are no published papers dealing with the second sub-issue, as far as we know. Ref. [13] might be the closest one, which considers the dynamic routing in circuit-switched networks using VLB without referring to the failure case. We propose two schemes, one static and one dynamic, to handle the above two sub-issues, respectively. Both of them are applied to low-speed (e.g., OC-1) connections with traffic grooming [9] [10] [11]. For the static scheme, we first put forward a novel scheme SMEN (select most efficient nodes) to configure the WDM network given a set of intact (no failed) and failed scenarios. Then we gravitate toward the robust routing in the pre-configured network. SMEN is focused on calculating the traffic distribution fractions with the goal of minimum network cost by forwarding more packet flow through the nodes with larger upper-bound of egress/ingress traffic and loading more traffic on the paths with less link cost as well as smaller hop count. It takes an insight into both network topologies and traffic conditions, thus outperforms the method proposed in [4]. For the dynamic routing scheme, we introduce the concept of node availability to index the criticality and efficiency of a node, and a dynamic robust routing scheme NAL (node availability load-balancing) is proposed for a close to optimal throughput. NAL adaptively routes every arrived request through one intermediate node according to the state of network. It is also promising compared with the unprotected scheme [13]. The rest of the paper is structured as follows. In Section II, we introduce the network model. Then Section III and Section IV present the static scheme and dynamic scheme, respectively. Section V offers the simulation results and Section VI concludes the paper. 1

The term “scenario” in this paper means a possible network state, where the “intact scenario” means the state that the network is of no failure, and the “failure scenario” corresponds to the state that the network suffers from a specific single (multiple) component failure(s).

II.

NETWORK MODEL

Define a WDM network topology G (N, E, W), where N, E and W is the set of nodes, bidirectional fiber links, and available wavelengths per links, respectively. Let N, E and W denote the node number, the bidirectional link number, and the wavelength number, respectively. We assume each node has multiplexing/demultiplexing and time-slot interchange capability, but has no wavelength conversion capability. The granularity of OC-1 is regarded as the bandwidth unit, and the other notations used in our study are listed in Fig.2. r(i, j): a connection request from source node i to destination node j. Tr: the number of tunable transceivers of each network node. Each transceiver

in the network consists of a transmitter and a receiver. C: the number of bandwidth units of each wavelength channel (C=48 in the paper). Ri (Ci): the number of maximum OC-1 connection requests entering/leaving the network at node i. tiin (tiout): the number of OC-1 connection requests entering/leaving the network at node i measured every period of time. SRLB-M: the SRLB architecture where M nodes are selected as hub nodes. S: the set of hub nodes under a given intact VLB (SRLB) architecture. α: the traffic distribution vector. α=[α0,α1 …αN-1] (Σi ∈ S αi=1, 0≤αi≤1),where αi is the traffic distribution fraction from any source node in the network to the intermediate node i (αi=1/N under ULB architecture). Pij: the shortest path between node pair (i, j). dij: the distance of Pij. Hij: the hop count of Pij. Sc = {f0, f1,…, fk}: the set of given scenarios. Sc = {f0, f1,…, fk}, where f0 is the intact scenario, and fk is a certain failure scenario. Sfk: the set of intact nodes over scenario fk. num_Wij(fk): the number of wavelengths assigned to Pij in scenario fk. Figure 2. The list of notations in this paper

III.

STATIC PROTECTION SCHEME

Network designers are likely to be confronted with a set of failure scenarios. In this section we dedicate to figure out an effective protection scheme assuring 100% throughput for a set of particular failure scenarios. We begin with pre-configuring such a network using VLB (SRLB). A. Building Economical and Congestion-free WDM Networks under Load-balancing Architectures To construct a load-balancing WDM network tolerant with a set of multiple failures, we firstly need to solve the following sub-problems for each given scenario: 1) determine the routes of all possible connection requests for every scenario in Sc; 2) compute the traffic distribution vectors for all of these scenarios according to the routes. After that, the network is to be configured with wavelength assignment algorithms in terms of the traffic distribution vectors. Our proposed scheme SMEN is based upon the above procedures. Since every failure scenario corresponds to a set of optical fiber, OXC and IP (or MPLS) router failures, the protection on both optical layer and IP layer needs to be considered. We present residual layered graph (RLG) to cope with a given scenario. RLG consists of two sub-graphs:


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(c) (d) Figure 3. (a) Physical topology (b) Logical topology where node 1,2,3 are intermediate nodes (c) RGOL of the failure scenario when fiber {1,2},OXC 3 and IP router 2 fail, it is divided into wavelenth plane λ0 and wavelenth plane λ1 (d) RGIL of the same failure scenario (the nodes indicated by square boxes are OXCs, the nodes indicated by circles are IP routers)

residual graph on optical layer (RGOL) and residual graph on IP layer (RGIL). Both of them are constructed in terms of the present scenario. RGOL contains a set of unused optical network resources such as wavelengths and transceivers, and it is divided into several wavelength planes. RGIL is composed of a set of light paths (or circuits) existed in the scenario. Fig.3 illustrates how RGOL and RGIL are created. We suppose W=2 (the wavelengths are labeled by λ0 and λ1), Tr=3, and presume the failure of bidirectional fiber link {1, 2}, OXC 3 and IP router 2. Besides, three requests r(1, 4), r(1, 5) and r(5, 4) are running over this failure scenario, where both r(1, 4) and r(1, 5) require a wavelength bandwidth, and r(5, 4) requires 12 bandwidth units. Then 3 light paths λ0 (1-5-4), λ1 (1-5), λ1 (5-4) are set up through nodes 1-5-4, 1-5 and 5-4, respectively. Since there is no residual bandwidth on edges and of wavelength plane λ0, and of wavelength plane λ1, they are deleted from RGOL. The numbers (m, n) beside each node denote that there are m (n) unused transmitters (receivers) in this node. In addition, we note that IP router 3 is deleted from the logical topology when OXC 3 fails. This is because that it can neither send nor receive any traffic through the optical layer. On the basis of RGOL and RGIL, SMEN first routes all the existed requests across the given scenarios with Dijkstra algorithm. Then it computes the traffic distribution vectors so as to access the minimum cost as close as possible. The basic idea is to load more traffic on the nodes with larger upper-bound of egress/ingress traffic and the paths with less link cost as well as smaller hop count. Here we skip the details due to the space limitation and go straight to the final equations. That is, for every scenario fk, αi is:

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⎧M i / M i ,∀i ∈ S ∩ S fk and S ∩ S fk ≠ φ ⎪ i∈S ∩ S fk ⎪⎪ α i = ⎨1, S ∩ S = φ and M / M i = max M k / Mk fk i ⎪ k i∈S fk k∈S fk ⎪ 0, otherwise ⎩⎪

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The network is able to be configured after the traffic distribution vectors of all given scenarios are computed. For each scenario fk, we have to assign wavelength to the light paths in RGIL under the wavelength continuity constraints. According to the rules of load-balancing [1] [2] [3] and features of WDM networks, SMEN assigns wavelengths to the light paths in RGIL using the first-fit algorithm. That is: ⎧ceil(( floor(α j Ri ) + floor(αiC j ) + 2(N − 1)) / C), ⎪ ⎪∀i, j ∈ S ∩ S fk ⎪ num _ Wij ( fk) = ⎨ceil(( floor(α j Ri ) + ( N − 1)) / C), ∀i ∈ S fk − S ∩ S fk , j ∈ S ∩ S fk ⎪ ⎪ceil(( floor(αiC j ) + ( N − 1)) / C), ∀i ∈ S ∩ S fk , j ∈ S fk − S ∩ S fk 0, otherwise ⎩⎪

where function floor(x) and ceil(x) perform to calculate the lower and higher integer bound of x, respectively. Therefore the number of wavelengths assigned to each light path Pij across all the given scenarios is max num _ wij ( fk ) . fk ∈S c

B. Implementing the Robust Routing with TrafficGrooming As the granularity of all the requests is OC-1, we need to perform efficient multiplexing of these low-rate requests on the high-capacity light paths, i.e., to implement the robust routing with traffic grooming in the network configured by SMEN. Considering the wavelength continuity, this can be done by routing all the requests on the wavelength planes of RGOL. Fig.4 shows the details: step1. Put all the node pairs whose source and destination nodes are both intact in a List L according to RGIL over the present scenario, and then measure tiin and tiout for every node i every period of time. step2. Take out a node pair (i, j) from L. Then: If both i and j are intermediate nodes, first route the amount of traffic floor (αj tiin) +N−1 in each wavelength plane of RGOL until Pij is j found and update RGOL; then route the traffic floor (αi t out) +N−1 in these wavelength planes and update RGOL; finally go to step 3. If i is intermediate node but j is not intermediate node, route the traffic floor (αi tjout) +N−1 in each wavelength planes of RGOL until Pij is found, update RGOL and go to step 3. If i is not intermediate node but j is intermediate node, route the traffic floor (αj tiin) +N−1 in each wavelength plane of RGOL until Pij is found, update RGOL and go to step 3. If neither i nor j is intermediate node, go to step 3. step3. Delete node pair (i, j) from L. If L is empty, go to step 1; else go to step 2. Figure 4. Robust Routing in the pre-configured WDM network

IV.

DYNAMIC ROBUST ROUTING TO HANDLE MULTIPLE FAILURES

A. Node Availability Load-balancing (NAL) In nowadays networks, the traffic fluctuates drastically over time, i.e., traffic demands are dynamic and may come and go. Given this highly dynamic traffic, we can count on load-balancing to handle failures with some modifications. That is, each intermediate node i under a certain VLB (SRLB) architecture is associated with a load-balancing probability [13] pi (Σi ∈ S pi=1, 0≤pi≤1), and any newly arrived request is routed through one of the intermediate nodes according to pi.


Clearly, if a request is forwarded by one of its end nodes, the path is one-hop; otherwise it is two-hop. To achieve a close to optimal throughput, we have to identify the main factors that contributes most: 1) network topology and connectivity; 2) capacity of links; 3) traffic information. In other words, it is inclined to route a request through the intermediate node forwarding less traffic and possessing more spare capacity to avoid congestion. This inspires us to introduce the metric node availability (NA) to index the criticality and efficiency of a node so as to estimate the impact of the aforementioned factors on throughput. It is WS ij WS ji defined that: NAi = ( + ) / N i ,where C R j j j∈S ∩ S j∈S ∩ S

∑

B. Procedures of NAL The Procedures of NAL are stated in Fig.5. Here we assume that each arrived connection request demands for one bandwidth unit (OC-1) and the total arrival rates (in number of arrivals per second) of the requests entering /leaving at a node other than the rates between a node pair is given.

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WSij and WSji are the number of unused wavelengths on Pij and Pij, respectively, and Ni is the number of paths traversing node i. Ni expresses the criticality of a node as the node with larger Ni is more liable to cause blockage when it fails. The basic idea of NAL is to let the intermediate nodes with larger NA more likely to be traversed by the currently arrived requests. This guides the calculation of the load-balancing probabilities, i.e., p i = NAi / NAi (1).

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Moreover, since we apply our scheme to low-speed requests and assume wavelength continuity as well as the limited number of transceivers, it is necessary to packet the multiple traffic streams to each light path with the construction of wavelength planes for a better resource utilization. That is, NAL is a scheme comprised of dynamic traffic grooming. step1. Build RGOL and RGIL for the present scenario fk. If S=null, add the node producing the least cost path tree in Sfk to S. step2. Wait for a connection request r(i, j): if i or j is failed, block r(i, j) and go back to step 2; otherwise if the request is to establish a connection, go to step 3; if it is to release a connection, go to step 4. step3. Route r(i, j) with dynamic traffic grooming. 1. Delete the nodes with none residual transceivers from S. If S is null, block this request and jump back to step 2; else compute the traffic distribution probability vector Pt= {pi} according to (1) and randomly determine the intermediate node k; 2. Delete the links whose bandwidth is smaller than that of r(i, j) in RGOL and run Dijkstra algorithm to compute Pik and Pkj in each wavelength plane of RGOL. If Pik and Pkj are found, go to 3; otherwise block r(i, j), jump back to step 2. 3. Allocate bandwidth and optical transceivers (if Pik or Pkj is a new light path) for r(i, j), update RGOL and jump to step 2. step4. Release the bandwidth and transceivers occupied by r(i, j) , update RGOL and go to step 5. step5. Keep track of the network conditions. If the scenario remains unchanged, jump back to step 2. If the network recovers from failures, release the failed resources, and jump back to step 1. If any part of the network is found malfunctioned, block all the affected requests and jump back to step 1. Figure 5. Procedures of NAL

Figure 6. NSFNET topology

V.

SIMULATION RESULTS AND ANALYSIS

We first demonstrate the performance of SMEN in total network cost by comparing it with ULB over a set of given scenarios. The simulation network is NSFNET (Fig. 6). Based on this network, 3 SRLB architectures—SRLB-1, SRLB-7 and SRLB-14 (i.e., VLB) are picked for simulation. Correspondingly, we respectively denote ULB-1, 7, 14 and SMEN-1, 7, 14 the average network cost of ULB and SMEN under the SRLB-1, 7, 14 architectures among the generated hose models. They are cost ratios normalized to the cost of ULB under the SRLB-1 architecture over the intact scenario. In our simulation, 100 hose models are randomly produced, with the values of Ri and Ci (i=1, 2,…,N−1) obeying the (100, 1000) uniform integer distribution. The failure scenarios are also produced in random. That is, we decide whether a network component is intact or failed in certain probabilities and let the percentage of failed network components (PFNC) to measure the degree of failure. Moreover, we keep the network connected across all the produced failures, as a disconnected network can not be assured congestion-free. For NSFNET, the network can not be connected if more than 40% links are failed. Due to this fact and the unlikelihood that a large number of multiple component failures occur at the same time, we set the maximum value of PFNC to 0.4. Fig.7 quantifies the cost benefits of SMEN against multiple failures under the given SRLB architectures. Prior to all, we observe that SMEN consumes desirably less network resources than ULB over the same scenario. As an example, when the network is intact, the value of SMEN-14 is 94.1% of that of the ULB-14. This is because that SMEN considers the impact of the network topology, traffic conditions and the physical hop count of all possible node pairs on network cost, and it tends to put more traffic on the paths with smaller link cost and hop count in order to reach the optimal method as close as possible. ULB ignores all of these factors thus cost more than SMEN. We also notice that the cost first increases as PFNC grows, and then begins to decrease when PFNC grows up to around 0.35. The reason lies in two aspects: on one hand, more backup resources need


to be assigned to the intact network components for the intact node pairs across the given failure scenarios as PFNC grows; on the other hand, the number of requests also decreases as the amount of failed node increases, and we do not have to configure bandwidth for the failed node pairs. When PFNC0.35, the latter aspect dominates, so it begin to decrease. Moreover, the SRLB architecture itself contributes a lot to the network cost. This is due to the fact that SRLB always selects the M lowest cost node(s) as intermediate node(s), so the less intermediate nodes are chosen, the more network cost can be reduced.

Normalized Network Cost

1.8 1.7

increases. The throughput of NAL and UDVLB under the SRLB-1, 7, 14 architectures are plotted in curves NAL-1, 7, 14 and UDVLB-1, 7, 14 respectively. We reconfirm that UDVLB is a well designed scheme when the network is intact. However, it performs unfavorably for failed scenarios, as it routes the connection requests with predetermined traffic distribution probabilities irrespective of the network conditions. Instead, NAL dynamically adjust the routes for any newly arrived request in terms of the present scenario and network conditions. In other words, NAL always tries to put the requests on paths of more spare capacity and avoids them being forwarded by nodes of high criticality, thus outperforms UDVLB. We also see that a much higher throughput is achieved under the load-balancing architecture with more hub nodes. This is straightforward in that more resources can be used in such architectures.

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VI.

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ULB-1 ULB-14 SMEN-7

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ULB-7 SMEN-1 SMEN-14

In this paper, we focused upon robust routing in Valiant Load-balancing WDM Networks against multiple failures. We proposed one static scheme (SMEN) and one dynamic scheme (NAL) to cope with this issue. Both of them are showed promising compared with the previous schemes. REFERENCES

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Figure 7. Comparison of network cost: SMEN vs ULB UDVLB-1 UDVLB-7 UDVLB-14 NAL-1 NAL-7 NAL-14

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Next we compare the throughput of NAL with that of the unprotected dynamic VLB (UDVLB) routing scheme [13], where the traffic distribution probabilities keep unchanged after the network is configured. We assume all the requests arrive in Poisson process and their holding time follow negative exponential distribution. The requests are generated up to 106 and the aggregated arrival rates at each node is bounded by the hose model complying with the (100, 1000) uniform integer distribution. Plus, we suppose each link and node has the same number of wavelengths and transceivers with W=16, Tr=8, respectively. Fig.8 illustrates the throughput of NAL versus that of the UDVLB as PFNC

CONCLUSION

[9]

[10] [11]

[12]

[13]

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