design and analysis of partial protection mechanisms in groomed optical wdm mesh networks

Vol. 7, No. 6 / June 2008 / JOURNAL OF OPTICAL NETWORKING 617

Design and analysis of partialprotection mechanisms in groomed

optical WDM mesh networks

Mahesh Sivakumar,1 Jing Fang,2 Krishna M. Sivalingam,1,3 and Arun K. Somani2

1Department of Computer Science and Electrical Engineering (CSEE), Universityof Maryland, Baltimore County, Baltimore, Maryland 21250, USA

2Department of Electrical and Computer Engineering, Iowa State University, Ames,Iowa 50011, USA

3Department of Computer Science and Engineering (CSE), Indian Instituteof Technology Madras, Chennai, India

*Corresponding author: [email protected]

Received November 6, 2007; revised March 3, 2008; accepted March 29, 2008;published May 14, 2008 �Doc. ID 89463�

We consider the problem of survivable network design in traffic-groomed op-tical WDM mesh networks that support subwavelength capacity connections.In typical survivable network designs, individual sessions are provided eitherfull protection or no protection. We consider a quality of protection (QoP)framework where a connection is provided partial protection, i.e., when a linkfailure occurs on the primary path, the protection bandwidth provided on thebackup path is less than or equal to the primary bandwidth. Each connectionrequest specifies the primary bandwidth and a minimum backup bandwidthrequired. The network will guarantee at least the minimum backup band-width and, if capacity is available, higher backup bandwidth up to the pri-mary path’s bandwidth. The advantage of such a model is that it can reducebackup capacity requirements based on connection needs leading to lowerblocking probability and lower network costs. We consider two scenarios: (i) anetwork with static traffic that is designed using an integer linear program(ILP) formulation and (ii) a network with dynamic traffic for which we presenta heuristic connection admission control algorithm that prevents backup re-source contention during recovery from a link failure. The results quantify thegain in blocking probability for different partial protection scenarios. Themechanism proposed to counter backup contention is seen to provide an aver-age of 120% reduction in the contention among backup paths of connectionstraversing a link, especially when the number of wavelengths in each link issmall. © 2008 Optical Society of America

OCIS codes: 060.4251, 060.4256, 060.4257, 060.4261.

1. IntroductionOptical networking has shown remarkable progress in the past few years with devel-opments in wavelength division multiplexing (WDM) and in transport technology[1,2]. WDM technologies allow several data sessions to be multiplexed on differentwavelength channels of a single optical fiber, with each channel capable of transport-ing several tens of gigabits of data. Mesh-topology-based networks are being increas-ingly considered, especially for backbone networks due to their compelling cost andflexibility benefits over synchronous optical network (SONET) rings.

In this paper, we consider a wide area network based on an optical WDM meshtopology. We also assume that a circuit-switched model is used, where an end-to-endoptical light path is set up to satisfy a given connection request. Further, since amajority of the traffic streams supported by the network typically require only a frac-tion of the wavelength capacity, multiple connections are carried on a given wave-length, leading to subgranularity light-path allocations. This is defined as trafficgrooming. A survey of related work on traffic grooming in optical WDM mesh net-works can be found in [3,4].

We also consider another important aspect of network design, namely, survivability.Network monitoring statistics indicate that failures are not an uncommon occurrencein backbone networks [4,5]. Hence, fault tolerance or survivability is an importantconsideration for such high-capacity networks. One of the main strengths of the cur-rent SONET/synchronous digital hierarchy (SDH) infrastructure is the protection ser-

1536-5379/08/060617-18/$15.00 © 2008 Optical Society of America


vice that it offers, i.e., the ability to respond to and recover from network failures. Itis therefore necessary for WDM and future SONET optical layers to provide similarprotection services. Research on this topic has also considered the notion of quality ofprotection (QoP), where the degree of survivability provided to each connection variesbased upon user requirements [6–11].

As wavelength-routed networks evolve toward accommodating traffic grooming, it isimperative that survivability requirements be investigated for groomed networks.Survivability in mesh networks operating at wavelength granularities has been wellinvestigated [12]. However, the design of survivability mechanisms for subchannelcapacity allocation still remains an open research problem. There are several uniqueand interesting challenges that arise when survivability techniques are considered forgroomed networks. Some of these include scalability since several subwavelength con-nections have to be restored under failure and also the possibility that the differentconnections on a wavelength might require different protection guarantees.

This paper proposes a partial protection model that enables the provision of vari-able protection bandwidth to connections. We consider a QoP framework where a con-nection is provided partial protection, i.e., when a failure occurs on the primary path,the protection bandwidth provided on the backup path is less than or equal to the pri-mary bandwidth. Each connection request specifies the primary bandwidth and aminimum backup bandwidth. The network will guarantee at least the minimumbackup bandwidth and, if capacity is available, higher backup bandwidth up to theprimary path’s bandwidth. Note that the availability of traffic grooming facilitatesthis concept since it allows provisioning of subwavelength capacity to each connection.The advantage of this model is that it can reduce backup capacity requirements basedon connection needs leading to lower blocking probability and lower network costs.One possible application of such a model is for digital video distribution, as presentedin [13]. Note that SONET virtual concatenation (VCAT) techniques could also providepartial protection by using traffic splitting at the source [14] so that when failuresoccur on any of the substreams, traffic can still be carried on the other streams.

We consider two different scenarios for applying the partial protection model: (i) anetwork with static traffic that is designed using an integer linear program (ILP) for-mulation and (ii) a network with dynamic traffic for which we present a heuristic con-nection admission control algorithm that prevents backup resource contention duringrecovery from a link failure. The former is useful in network design during the prede-ployment phase, and the latter is useful during postdeployment in an operational net-work.

The numerical results, from the ILP solutions for the static case and discrete eventsimulation for the dynamic case, quantify the gain in blocking probability for differentpartial protection scenarios. The mechanism proposed to counter backup contention isseen to provide an average of 120% reduction in the contention among backup pathsof connections traversing a link, especially when the number of wavelengths in eachlink is small.

The rest of the paper is organized as follows. Section 2 presents background mate-rial and related work. Section 3 describes the proposed partial protection model.Section 4 presents the formulation of the optimization problem for network design,given static traffic requests, and the experimental results obtained by solving the ILPfor a small network. The impractical nature of the ILP solutions for large networkswith dynamic traffic necessitates heuristics. Section 5 presents a heuristic approachfor large networks and studies the benefits of partial protection under dynamic trafficconditions. Section 6 presents the results of our performance evaluation studies.Finally, Section 7 concludes the paper.

2. Background and Related WorkAs mentioned earlier, most of the work on survivability for WDM networks has notconsidered traffic-groomed networks. An extensive review is omitted here due to spaceconstraints, but survey papers may be found in [4,5,12]. Survivability in traffic-groomed mesh networks supporting subwavelength granularity connections hasrecently received research attention. Some of this work is summarized below.

In [15], the authors studied the static traffic model for groomed mesh networkswith protection requirements. They modeled the problem as an ILP with the objective


function designed to reduce overall network costs. The traffic-grooming problem forsurvivable WDM networks was studied in [16] for shared protection and threeschemes, namely, protection-at-light path (PAL) level, mixed protection-at-connection(MPAC) level, and separate protection-at-connection (SPAC) level were proposed. Thesame problem was studied in [17] for dedicated protection and two approaches, PALlevel and protection-at-connection (PAC) level, were studied. Their study showed thatwhen lower bandwidth connections outnumber the higher bandwidth connections anda large number of grooming ports are available, PAC outperforms PAL while PAL per-forms better when ports are limited. The problem of provisioning dynamically estab-lished multigranularity traffic streams with protection requirements was studied in[18] and two schemes, namely, mixed primary-backup grooming policy (MGP) and seg-regated primary-backup grooming policy (SGP) were proposed. Simulation resultsshowed that MGP performs well in networks with good connectivity such as the mesh-torus, while SGP provides superior performance in ring networks, which have lowconnectivity and high load correlation.

Most survivability mechanisms proposed for optical WDM networks aim at provid-ing 100% failure recovery guarantee in the event of a single failure. The inefficientresource utilization with proactive approaches, however, reduces the network’s overallability to provision bandwidth request for more connections. QoP aims to bridge thegap between the two well-known protection grades, fully guaranteed andno-guaranteed connections. This can be achieved by using multiple protection gradesfor connections based on the amount of bandwidth utilized in protecting them(examples: guaranteed protection, best-effort protection, etc.). Upon a failure, theprobability that a connection will recover from a failure is determined by its desiredQoP.

The concept of QoP service classes has been considered in [6,7,9]. Four different ser-vice types are considered: assured restorability, best-effort, nonprotected, and pre-emptible services. The QoP design problem has been formulated using linear pro-gramming and solutions presented for different combinations of service classes. Asimilar idea of partial protection has been considered in [19]. However, that work didnot consider the static traffic design problem and also did not present a detaileddynamic traffic study, as done in this paper. A comprehensive discussion of such sur-vivable mechanisms that deal with differentiated reliability and QoP concepts is pre-sented in [8].

For ring networks, the idea of differentiated reliability (DiR) is presented in [10]. Intheir proposed system, the connection specifies a required minimum reliability degreethat is guaranteed by the network, in terms of a connection maximum failure prob-ability. The network uses a modified dedicated path protection mechanism. This workhas focused on WDM rings and full-wavelength bandwidth requests. The concept ofDiR has been enhanced to consider node failures with node availability included inthe determination of connection failure probability [11].

While QoP in wavelength-routed mesh networks has been addressed as describedabove, its implication on networks capable of carrying subwavelength granularity con-nections remains an open research question.

In terms of technologies to support traffic grooming, there are two options: elec-tronic traffic grooming and optical traffic grooming. In electronic traffic grooming,each switching node consists of an optical switching fabric and an electronic SONETgrooming fabric that consists of SONET add–drop multiplexers (SADMs) and elec-tronic switching fabrics. This type of grooming is feasible with current commerciallyavailable products but has the disadvantage of requiring optoelectronic conversion atintermediate grooming nodes. With optical traffic grooming, a single wavelength isorganized as a time-division multiplexed frame that consists of time slots [20]. Theswitching is done at the time-slot level entirely in the optical domain, and connectionsare assigned a set of time slots within each frame based on their specified requests.This technology allows end-to-end all-optical transmission but is still in the earlystages of development. The proposed work in this paper can work with both opticaland electronic grooming technologies.

3. Partial Protection ModelIn this paper, we present the partial protection model in the context of a QoP frame-work for circuit-switched survivable WDM grooming networks. We consider the proac-


tive protection model where backup capacity is assigned when a connection is set up.Each connection is provided a primary path and a link-disjoint backup path that willbe used to protect against link failures along the primary path. We do not considernode failures in this paper.

To enable QoP, we consider the notion of partial protection that provisions surviv-able connections with varying protection grades in the network. With partial protec-tion, the primary paths are given the requested bandwidth, but the bandwidth pro-vided to protection paths will vary in accordance with the minimum protectionguarantee specified by each request.

The connection request for a given connection m (between a specified source anddestination) specifies a primary bandwidth requirement of dm units and a minimumprotection bandwidth of bm units. The actual assigned capacity on the backup pathwill be cm, where bm�cm�dm and cm represents the actual protection bandwidth pro-vided to this connection. The network will guarantee the minimum protection band-width when failure occurs and will attempt to provide additional protection band-width depending on current network conditions. The objective of this work is tomaximize cm for each connection, and thus, to optimize the QoP provided for each con-nection. Such a design would be extremely useful in cases where the network cannotafford full protection to every connection. We consider two different scenarios wherethis model can be applied.

For the static traffic scenario, the network designer is provided with the networktopology and a traffic matrix with all the connections and their bandwidth require-ments specified. The goal is then either to design the network minimizing overall costto support all the connections or to maximize the number of admitted connectionsgiven resource constraints (i.e., number of wavelengths on each link, etc.).

For the dynamic traffic scenario, traffic requests arrive dynamically based on somestochastic arrival process. The goal of the network is to allocate light-path resourcesfor each connection while meeting the primary and protection bandwidth require-ments. The objectives include maximizing the number of admitted connections byusing efficient routing and wavelength assignment techniques.

It is essential to consider both these traffic scenarios. Static-traffic-based study isextremely important for network design before the network is deployed. Dynamic-traffic-based study is essential to understand network performance in a dynamic set-ting and identify capacity needs to better handle a given traffic mix.

For networks that use electronic grooming, the proposed partial protection tech-nique will have a direct bearing on the port costs. With less protection bandwidthbeing used by protection paths, it will lead to better utilization of the grooming portsat the node. This is because the grooming capability available at the node can be usedfor admitting more connections into the network and in turn reduce the number ofneeded grooming ports at a node and hence the grooming port cost of the network.

4. Static Traffic ScenarioIn this section, we consider the network design problem for a network with a prespeci-fied traffic matrix.

4.A. Assumptions and Basic DesignThe network assumptions are the following:

1. The network is a single-fiber irregular mesh network.2. A connection request cannot be divided into several low-speed connection

requests and routed separately from the source to the destination. A connection’s datashould always follow the same route.

3. Wavelength continuity constraint applies, i.e., a given connection will be carriedon a light path on a single wavelength.

We next present the basic design strategy used in solving the problem. The study in[21] proposed two exact ILP formulations for survivable design in WDM grooming net-works, with one using primary-backup multiplexing and the other, dedicated backupreservation. These formulations can be modified to solve the partial protection prob-lem in grooming networks. However, a direct modification makes the formulationsnonlinear due to the fact that the capacity allocated to backups is unknown in thecase of partially protected connections. If we reconsider the motivation for partial pro-


tection in grooming networks, the problem can be solved differently. The main reasonfor adopting partial protection is that the network may not have enough wavelengthresources to provide full protection for each request. In other words, we may not wantto exploit an extra wavelength’s worth of capacity just to provide more than the mini-mum capacity required for protection. Based on the above fact, the partial protectionproblem can be divided into two subproblems as follows:

1. Resource Minimization: Given a network topology and a set of point-to-pointrequests (or demands) and their link-disjoint primary and backup routes, provisioneach connection request m with a primary capacity dm and a backup capacity bm insuch a way that the total number of wavelength links used is minimized.

2. Protection Maximization: Given the initial grooming solution from the abovestep, optimally distribute the residual network capacity to provide better protection tosome, if not all, of the requests.

Each subproblem can be formulated as an ILP optimization problem. For capacityallocation, both primary-backup multiplexing and dedicated backup reservation canbe applied. The study in [21] showed that while backup multiplexing is computation-ally expensive for WDM grooming networks, dedicated backup reservation performsfairly well and becomes affordable due to the fact that the wavelength utilization issignificantly improved by the grooming capability. Hence, we present a two-phase ILPformulation with a dedicated backup reservation scheme.

Link Primary Sharing. One simple and effective way of assigning backup capaci-ties is to reserve dedicated capacity for each backup path. While choosing primarypaths, instead of simply choosing the shortest path, we try to minimize the total linkprimary sharing (MLPS) when solving subproblem 1. Subproblem 2 relies on the con-venient placement of idle capacity in the backup path’s wavelength along its route.Minimizing MLPS tends to spread out the backup routes found in subproblem 1.Thus, in the process of solving subproblem 2, it is possible to tap the network’s sparecapacity to the fullest extent possible, yielding better results.

Let Pij denote the total number of primary paths that utilize link �i , j�. Then, thelink-primary-sharing index is defined as sij=max�0,Pij−1�. sij can be viewed as thepenalty assigned to link �i , j� when it is used by more than one primary path.

4.B. NotationsGiven the following:

1. A physical topology G= �V ,E� consisting of a unidirectional graph, where V is theset of network nodes ��V � =N� and E is the set of physical links (edges). Nodes corre-spond to network nodes, and links correspond to the fibers between nodes.

2. The number of nodes in the network is N, the number of wavelengths carried byeach fiber is W, and the capacity of each wavelength is C (assuming each wavelengthhas the same capacity).

3. A traffic matrix DN�N= �dm�, where dm indicates the required capacity of low-speed traffic requests in units of OC-1 for request m.

4. A guaranteed backup capacity matrix BN�N= �bm�, where bm is the guaranteedbackup capacity, or in other words, the lower bound of the backup capacity for requestm.

5. The capacity weight of link �i , j�, denoted by wijc , is a positive real number and

can be regarded as a measure of capacity consumption per wavelength on the link.These weights are used to differentiate links from the capacity cost point of view.

The following notations are used to describe various entities:• i , j=1,2, . . . ,N: Number assigned to each node in the network.• m ,n=1,2, . . . ,N� �N−1�: Number assigned to each request (source–destination

pair). Let sm and tm be the source and the destination nodes of request m, respectively.• w=1,2, . . . ,W: Number assigned to each wavelength.• K=2: Number of alternate routes between every s–d pair.• p ,r=1,2, . . . ,KW: Number assigned to a path for each s–d pair. A path has an

associated wavelength (light path). Each route between every s–d pair has W wave-length continuous paths. The first 1�p ,r�W paths belong to route 1, and W+1�p ,r�2W paths belong to route 2.

The following notations are for path-related information:• �m,p: Path indicator that takes a value of 1 if path p is chosen as a primary path

for request m, 0 otherwise (binary variable).


• �m,r: Path indicator that takes a value of 1 if path r is chosen as a restorationpath for request m, 0 otherwise (binary variable).

• Lijm,p: Link indicator that takes a value of 1 if link �i , j� is used in path �m ,p�, 0

otherwise.• Ww

m,p: Wavelength indicator that takes a value of 1 if wavelength w is used by thepath �m ,p�, 0 otherwise.

The following variables are used to represent wavelength assignment in the groom-ing network:

• pij,wm : Binary variable, 1 if wavelength w on link �i , j� is used by primary path of

request m, 0 otherwise.• rij,w

m : Binary variable, 1 if wavelength w on link �i , j� is used by backup path ofrequest m, 0 otherwise.

• uij,w: Binary variable. Wavelength usage indicator. 1 if wavelength w on link �i , j�is used by any primary or backup path for any request, 0 otherwise.

• wi,jc is defined as the cost of sharing multiple primary paths on link �i , j�. When

wi,jc is set to 1, the objective function includes the total amount of link sharing on pri-

mary paths. When wi,jc is set to 0, the effect of sharing a primary path on a link is not

considered in the optimization. Increasing the value of wi,jc can help reduce the

instance of having too many primary paths sharing a particular link, thereby reduc-ing the worst-case effects when a single link failure occurs.

• �ij: nonnegative integer, total number of wavelengths required on link �i , j�.• xij,w counts the number of primary and backup paths that use wavelength w on

link �i , j�.• �ij,w: nonnegative integer, total capacity assigned to primary paths on wavelength

w on link �i , j�.• �ij,w: nonnegative integer, total capacity reserved for backup paths on wavelength

w on link �i , j�.• cm: capacity assigned to the backup path for request m.

4.C. ILP Formulation I: Resource MinimizationObjective: Minimize the total wavelength links as well as total link primary sharing:

min� ��i,j��E

wijc � �ij + wij

s � sij� . �1�

Constraints1. On physical route variables.A light path can carry traffic for a s–d pair only if it is in the physical route of this

request:

pij,wm = �

p=1

KW

�m,pLijm,pWw

m,p,

rij,wm = �

r=1

KW

�m,rLijm,rWw

m,r. �2�

2. On path indicators.One and only one path will be assigned as a primary (backup) path for each

request:

�p=1

KW

�m,p = 1, �r=1

KW

�m,r = 1. �3�

3. On topology diversity of primary and backup paths.Primary and restoration paths of a given request should be link disjoint:

�p=1

W

�m,p = �r=W+1

KW

�m,r,

�p=W+1

KW

�m,p = �r=1

W

�m,r. �4�


4. On wavelength capacity variables.Primary capacities are aggregated. Backup capacities are aggregated when dedi-

cated backup reservation is applied:

�ij,w = �m

dm � pij,wm ; �ij,w = �

mbm � rij,w

m . �5�

For each wavelength, the sum of primary capacities and backup capacities should notexceed the total wavelength capacity:

�ij,w + �ij,w � C. �6�

5. On fiber capacity constraints.The number of wavelengths used on a fiber should not exceed the total number of

wavelengths carried by the fiber. The second set of equations [Eq. (8)] together setuij,w=1, if xij,w�1, and 0 otherwise. Recall that we consider single-fiber links:

xij,w = �m

�rij,wm + pij,w

m �, �7�

uij,w � xij,w, KN�N − 1�uij,w � xij,w, �8�

�ij � �w

uij,w �ij � W. �9�

6. On link primary sharing.Recall the definition of sij in Subsection 4.A; sij is nonnegative and is given as fol-

lows:

sij � �m

�w

pij,wm − 1, sij � �

m�w

pij,wm . �10�

4.D. ILP Formulation II: Protection MaximizationAfter solving the ILP formulation in Subsection 4.C, it is guaranteed that eachrequest m is allocated a primary with bandwidth dm and its minimum protectionrequirement bm. However, it is still possible that there are fractional wavelengthresources unused in parts of the network. The second step is then to optimally allo-cate the residual capacity to the connections so that some if not all the requests canobtain better protection than their minimum requirements. In addition to the pathand wavelength indicator variables, the new input variable here is

• cm: capacity assigned to the backup path of request m.Objective. Protection OptimizationAs stated before, we use cm−bm to indicate the quality of the protection, where bm

�cm�dm. wmp is the weight assigned to the request m, if there is a need to differenti-

ate between different customers’ requests; normally, this is set to 1:

max��m

wmp � �cm − bm�� . �11�

Constraints

1. On wavelength capacity variables.Primary and backup capacities are aggregated:

�m

�dm � pij,wm + cm � rij,w

m � � C, bm � cm � dm. �12�

4.E. Experimental ResultsWe use CPLEX LINEAR OPTIMIZER 7.0 [22] to solve the two ILP formulations developedabove. The experiments are performed on a 10-node network topology with 14 biuni-directional links shown in Fig. 1. The capacity of each wavelength is OC-48�2.488 Gbits/s�.

Experiment I: For the first experiment, we use the traffic matrix shown in Table 1,which consists of 23 randomly generated requests. We also assume that each link hasa single fiber that carries two wavelengths. As presented in the study in [21], with full


protection, a total of 33 wavelength links in the network are needed for carrying thistraffic. We present the detailed solution here in Table 2. As can be seen, although twowavelengths are used in the network, wavelength 2 is only used by two requests ontheir primary paths. As a result, wavelength 2 is not fully utilized on those corre-sponding links.

For partial protection, the minimum backup capacity required for each connectionis given by bm=dm�Pratio, where 0Pratio�1, is referred to as the protection ratio. Inthis experiment, Pratio=0.6. The paths and the wavelengths selected are given inTable 3. With partial protection, a total of 28 wavelength links are required. Further,only one wavelength is used in the network. Note that some of the requests are fullyprotected (indicated in boldface) or are provided with capacity greater than their mini-mum requirement.

Experiment II: For the second experiment, 50 requests were randomly generatedas shown in Table 4. When the number of wavelengths per link is 3, there is no solu-tion for full protection �Pratio=1�. When the protection ratio is reduced to 0.5 �Pratio=0.5�, ILP-I (resource minimization) gives a solution of 59 wavelength links with allbackup paths given their minimum capacity of 6. Based on the results obtained fromresource minimization, we performed protection maximization to try to distribute theresidual capacity among the backup paths. The results show that some of the requestswere able to obtain full protection when the residual capacity was optimally distrib-uted. The connection requests that obtained full protection are shown inTable 5.

5. Design for Dynamic TrafficThe two-phase ILP formulation presented in Section 4 is designed for use with a statictraffic model. The formulation on the resource minimization subproblem can beviewed as a general version of the ILP formulation proposed in [21], which has beenshown to be impractical for use with larger networks that have dynamic traffic

Table 1. Traffic Matrix for the 10-Node 14-Link Network: 23 Requests

1 2 3 4 5 6 7 8 9 10

1 0 0 0 12 1 0 0 0 0 02 1 0 0 0 0 0 0 0 0 123 0 3 0 0 0 0 0 0 0 04 0 0 0 0 3 1 0 3 12 125 0 0 0 0 0 0 0 0 1 06 0 0 3 0 0 0 0 0 0 07 0 0 0 0 0 0 0 0 3+1 08 1 0 12+12 0 0 0 1 0 0 09 0 3 0 0 12 33 0 0 0 0

10 3 0 0 0 0 0 0 0 0 0

1

2 3

4

67

9

8 105

Fig. 1. Physical topologies used in experiments.


Table 2. Solution with Full Protection: 33 Wavelength Links Are Needed

Primary Path Backup Path

s–dPair Path w Cap Path w Cap

9-2 9-10-8-5-1-2 w1 3 9-7-6-2 w1 33-2 3-2 w1 3 3-4-7-6-2 w1 37-9 7-9 w1 3 7-8-10-9 w1 38-7 8-7 w1 1 8-6-7 w1 19-6 9-7-6 w1 3 9-10-8-6 w1 32-1 2-1 w1 1 2-6-1 w1 11-4 1-6-7-4 w1 12 1-2-3-4 w1 124-9 4-7-9 w1 12 4-3-2-6-8-10-9 w1 1210-1 10-9-7-6-1 w1 3 10-8-5-1 w1 34-8 4-7-8 w1 3 4-3-2-6-8 w1 34-5 4-7-8-5 w1 3 4-3-2-1-5 w1 38-1 8-5-1 w1 1 8-6-1 w1 19-5 9-7-8-5 w1 12 9-10-8-6-1-5 w1 125-9 5-8-7-9 w1 1 5-1-6-8-10-9 w1 18-3 8-7-4-3 w2 12 8-6-2-3 w1 127-9 7-9 w1 1 7-8-10-9 w1 12-10 2-6-8-10 w1 12 2-3-4-7-9-10 w1 129-6 9-7-6 w1 3 9-10-8-6 w1 34-6 4-7-6 w1 1 4-3-2-6 w1 16-3 6-2-3 w2 3 6-7-4-3 w1 38-3 8-6-2-3 w1 12 8-7-4-3 w1 121-5 1-5 w1 1 1-6-8-5 w1 14-10 4-7-8-10 w1 12 4-3-2-6-7-9-10 w1 12

Table 3. Solution with Partial Protection „Pratio=0.6…: 28 Wavelength LinksAre Needed



9-2 9-7-6-2 w1 3 9-10-8-5-1-2 w1 33-2 3-2 w1 3 3-4-7-6-2 w1 37-9 7-9 w1 3 7-8-10-9 w1 38-7 8-7 w1 1 8-6-7 w1 19-6 9-10-8-6 w1 3 9-7-6 w1 32-1 2-1 w1 1 2-6-1 w1 11-4 1-2-3-4 w1 12 1-6-7-4 w1 124-9 4-7-9 w1 12 4-3-2-6-8-10-9 w1 810-1 10-9-7-6-1 w1 3 10-8-5-1 w1 34-8 4-7-8 w1 3 4-3-2-6-8 w1 24-5 4-7-8-5 w1 3 4-3-2-1-5 w1 28-1 8-5-1 w1 1 8-6-1 w1 19-5 9-7-8-5 w1 12 9-10-8-6-1-5 w1 125-9 5-8-7-9 w1 1 5-1-6-8-10-9 w1 18-3 8-6-2-3 w1 12 8-7-4-3 w1 87-9 7-9 w1 1 7-8-10-9 w1 12-10 2-6-8-10 w1 12 2-3-4-7-9-10 w1 99-6 9-7-6 w1 3 9-10-8-6 w1 34-6 4-7-6 w1 1 4-3-2-6 w1 16-3 6-2-3 w1 3 6-7-4-3 w1 38-3 8-7-4-3 w1 12 8-6-2-3 w1 121-5 1-5 w1 1 1-6-8-5 w1 14-10 4-7-8-10 w1 12 4-3-2-6-7-9-10 w1 12


demands. This section deals with an algorithm that can be used for partial protectiondesign in WDM grooming networks with dynamic traffic patterns. As mentioned ear-lier, the static ILP formulation is useful in predeployment design, while the dynamicformulation is useful in understanding network performance behavior and redesign-ing the network capacity.

For the dynamic traffic scenario, the network topology and the number of wave-lengths per link are provided. Connection requests arrive at the network based on astochastic process. Each request specifies the primary bandwidth and the minimumprotection bandwidth. The network attempts to provision each connection requestbased on the current network resource availability. The goal is to minimize the con-nection blocking probability, i.e., maximize the number of admitted connections. Thesystem performance is determined by several factors including routing, wavelengthassignment, grooming policy, and grooming capabilities of the nodes. In Subsections5.A–5.C, we present our proposed mechanisms for handling dynamic traffic requests.

5.A. Route Selection HeuristicThe proposed heuristic is designed to better locate the additional backup bandwidthrequired by each connection affected by a failure. In addition to minimizing overallbackup capacity requirements, there are two important factors to be considered:

• Restoration speed: This refers to the amount of time needed to find the addi-tional protection bandwidth since the occurrence of the failure. The delay is com-pounded by the fact that the number of connections affected by a failure could be largesince each wavelength may carry multiple subwavelength capacity connections.

• Backup path contention: This refers to the amount of contention (sharing)between the backup paths of a primary traversing a link. When a failure occurs, find-ing additional spare capacity for one affected light path might affect the chances ofanother. This could happen when the backup paths of those light paths share thesame link(s). Hence, the order in which the light paths are restored becomes signifi-cant. One way to address this is to consider the amount of contention between thebackup paths of the primaries traversing each link.

Table 4. Traffic Matrix for the 10-Node 14-Link Network: 50 Requests

1 2 3 4 5 6 7 8 9 10

1 0 0 0 12 12 0 12 0 0 122 0 0 0 12 0 0 0 0 0 12+123 12+12 12 0 0 12 12+12 0 12 12+12 04 0 12 0 0 0 0 12 12 12 125 12+12 0 0 0 0 12 12+12 0 0 06 0 0 12 12 0 0 0 12+12 12+12 07 0 0 0 12 0 0 0 0 12+1212 128 12 12 12 0 0 0 12 0 0 09 0 0 12+12 0 0 0 0 0 0 0

10 12 0 12+12 12 0 12 12 0 12 0

Table 5. Solution with Partial Protection „Pratio=0.5…: Connection RequestsThat Achieved Full Protection after Protection Maximization



10-9 9-7-6-2 w3 12 10-8-7-9 w2 127-10 7-9-10 w1 12 7-8-10 w1 128-1 8-6-1 w2 12 8-5-1 w1 126-8 6-8 w1 12 6-7-8 w3 121-7 1-6-7 w1 12 1-5-8-7 w3 126-3 6-2-3 w1 12 6-7-4-3 w3 123-5 3-2-1-5 w3 12 3-4-7-8-5 w1 12


We consider fixed alternate path routing where the set of K link-disjoint pairsbetween every s–d pair is precomputed. A modified version (suited to groomed net-works) of Suurballe’s algorithm was used to select the disjoint routes. Alternately, thelink-disjoint pairs could also be computed dynamically; we choose fixed alternate rout-ing for simplicity. However, the main objective of this paper was to show the effective-ness of partial protection in groomed networks, and the formulation merely serves asa proof to the concept. It can be optimized with respect to the routing algorithm used,but that is beyond the scope of the paper. However, as we do show in the route selec-tion algorithm for the dynamic case, selecting routes based on the contention factorrather than the fixed alternate path routing improves performance.

When a connection request arrives, the first link-disjoint pair between the sourceand the destination can be used. However, this does not take into consideration thepossible backup resource contention as described above. Therefore, we have designeda heuristic that will minimize contention among backup paths of connections using alink. The proposed heuristic also tries to avoid the delay that would be caused inresolving the backup path contention after the occurrence of a failure and thus indi-rectly reduces the restoration time for the affected connections.

5.B. Resistance FactorThe heuristic is based on the notion of resistance factor. The resistance factor isdefined for each link that a light path traverses and for the light path itself. For a newincoming connection m, the resistance offered by each link �l� in the chosen primarypath to this new connection models the increase in contention among the backuppaths corresponding to those primary paths that traverse link l. In other words, theresistance factor is a measure of the number of backups that will contend for addi-tional bandwidth if link l fails.

When a connection request arrives, the heuristic will select a link-disjoint pair foreach incoming connection that is offered the minimum resistance from the links of itsprimary. By handling the issue of backup contention at connection setup time, theheuristic also manages to avoid the delay that would have occurred if it was solvedafter the occurrence of a link failure.

The disadvantage of this heuristic is that it is likely to increase the hop length ofthe primary and backup paths chosen for a connection. Furthermore, each link needsto store information on the links used by backups of connections traversing them.

To calculate the resistance factor, each link in the network maintains the conten-tion list, a set that consists of links that are used by backups of one or more primariespassing through it. A counter that tracks the number of backups that use it is associ-ated with each link. Links in the contention list of a link l that have a countervaluegreater than 1 will represent the backup paths that will contend for bandwidth incase link l fails. We first define the notations used to describe various entities in Sub-section 5.C.

5.C. ImplementationIn order to implement the above mechanism, each link maintains the following vari-ables and data structures once a connection is established. Let k denote the index ofthe link-disjoint pair selected for a given connection m:

• �mk �l�: if the primary of the kth link-disjoint pair of a connection m passes through

link l, �mk �l�=1, otherwise, �m

k �l�=0.• �m

k �l�: if the backup of the kth link-disjoint pair of a connection m passes throughlink l, �m

k �l�=1, otherwise, �mk �l�=0.

• nl : is defined for each link in the network and denotes the number of backups of

primaries traversing link n that traverse link l. For instance, assume that a connec-tion request m was assigned to the kth link-disjoint pair traversing link n. For link n, n

l is incremented by 1, if �mk �n�=1 and �m

k �l�=1. If no primary traversing link n hasa backup that traverses link l, n

l =0. Note that, if nl �1, it implies that the backups

sharing that link would contend if link n fails.• Contention list �CL�n��: The contention list for a link n is a set that consists of all

the links l such that l �1, given by
n


CL�n� = �∀l � L: l � n ∧ nl � 1�.

In other words, the contention list captures the status of backup contention that willoccur when link n fails.

• Contention factor �CF�n��: The contention factor for each link is the number oflinks in its contention list, i.e., CF�n�= �CL�n��.

Path Selection: When a new connection request m arrives in the network, theresistance offered to each link-disjoint pair k��K� between its source and destinationis calculated in the form of a resistance factor, as follows. For each link n in the pri-mary route of path k of the request [i.e., �m

k �n�=1], the resistance that link n offers tothe primary of the kth link-disjoint pair of m is calculated as the link resistance fac-tor, given by

RFmk �n� = �CL�n��.

Here, each link l�CL�n� is such that �mk �l�=1 and n

l �1. In other words, the resis-tance offered by each link is the number of links that are common between those inthe backup route of the kth link-disjoint pair of connection m and the contention listof n (the links that are in the backup route of some connection whose primary uses n).

The path resistance factor for the kth link-disjoint pair of connection m is thengiven by

RFmk = �

n: �mk �n�=1

RFmk �n�.

When a connection request arrives, the resistance factor for each of the k link-disjoint pairs of the connection are calculated, and the one with the least value is cho-sen for the connection. The result of the algorithm is an implicit specification of thelink-disjoint pair that best fits the constraints imposed in the problem statement. Thelink-disjoint pair with the least resistance factor value is chosen, and the wavelengthson the appropriate links are set to be busy. Among the two paths in the link-disjointpair, the one with the smaller hop length is chosen as the primary, and the other ischosen as the backup. Also, the contention list of each link in the primary is updatedto reflect the establishment of a new connection.

Example. Consider the example shown in Fig. 2. Figure 2(a) shows two primaries(P1 and P2) using link (2, 3) and their backups (B1 and B2) that share link (5, 6). Iflink (2, 3) fails, both B1 and B2 would contend for backup resources on link (5, 6).However, if the connection admission algorithm used the resistance factor to computethe link-disjoint pair, the two backups would use the paths as shown in Fig. 2(b). Thisis because the path resistance factor is set to 1 for the results presented in Fig. 2(a)and 0 for those presented in Fig. 2(b). Since the backups are link disjoint, when link(2, 3) fails, the backups will not contend for backup capacity.

P1 −> 2 − 3

B1 −> 2 − 5 − 6 − 3

P2 −> 1 − 2 − 3 − 4

B2 −> 1− 5 − 6 − 4 B1 −> 2 − 8 − 9 − 3

P2 −> 1 − 2 − 3 − 4

B2 −> 1 − 5 − 6 − 4

P1 −> 2 − 3

55

1

6

2 3

4 1

6

2 3

4

7 7

8 9

10

8 9

10

(a)(b)

Fig. 2. Reducing backup contention with a resistance factor.


6. Performance EvaluationIn this section, we present the results of the performance evaluation of the proposedheuristic.

6.A. Simulation ModelWe consider a network with dynamic traffic, where the session request arrival processat a node is modeled as a Poisson process; each request’s destination is selected fromthe set of all other nodes, based on a uniform distribution. Session durations are nega-tive exponentially distributed with a mean of 1/�. For the simulations, we selectedthe load values such that the blocking probability is less than 10−1. For the NationalScience Foundation network (NSFNet), the load was fixed to 65 (arrival rate of 6.5and �=10) Erlangs. We also ran simulations for the case when �=6.5 and an arrivalrate of 10; this corresponds to more numbers of connections that are held for a smalleramount of time. Since the results showed a similar trend, we do not present themhere. The network topology considered is the 14-node NSFnet. Each link is bidirec-tional and is implemented as two unidirectional links. Fixed alternate path routing isused to precompute the primary and backup pairs for each source–destination pair.The number of wavelengths per link �W� is varied between 8 and 32 and the first-fitalgorithm is used for wavelength assignment. All wavelengths are assumed to havethe same capacity T=OC-48 �2.488 Gbits/s�. The primary bandwidth required by theconnection requests �dm� is assumed to be uniformly distributed with mean Gav anddefined as follows:

• For 1�Gav�T /2, dmunif�1,2Gav−1�.• For T /2Gav�T, dmunif�2Gav−T ,T�.For example, Gav=12 indicates that dmunif�1,23� and Gav=36 indicates that

dmunif�24,48�.The minimum backup bandwidth required by each connection is referred to as the

protection ratio, defined earlier as Pratio=bm /dm. This ratio is fixed for each simulationrun and is varied between 0.5 and 1, which are equivalent to 50% and 100%, respec-tively, protection bandwidths. For the dynamic traffic study, the number of link-disjoint paths �K� was set to 5.

For each system parameter combination, simulations were run with ten differentrandom number seeds with each run having 106 requests. The average values areplotted here, with the confidence values less than 5%. We conducted simulations forthe 14-node NSFnet topology and the 20-node Advanced Research Projects AgencyNetwork (ARPANET). Here, we only present results from the NSFnet topology, sincesimilar trends were seen for the other topology. Complete details of the dynamic traf-fic study is available in [23].

6.B. Effect of Pratio on Blocking PerformanceWe first quantify the effect of providing partial protection on the blocking performanceof the network under dynamic traffic conditions. The simulations were run for thecases where the number of wavelengths per link was 8, 16, and 32. As all the casesshow a similar trend, we only present the cases where the number of wavelengths perlink is 16 and 32. The load in the network is varied for each case in such a way as tokeep the blocking probability in the proximity of 10−1.

Figure 3 plots the blocking performance for various values of the protection ratio�Pratio�, for the case when W=16 in Fig. 3(a) and for the case when W=32 in Fig. 3(b).In each case, the blocking performance has been plotted for different values of Gavvaried between OC-12 and OC-48. As expected, the figures show that there is a sig-nificant improvement in the blocking performance for small values of Pratio. Forinstance, as can be seen in Fig. 3(b), there is almost an order of magnitude improve-ment in blocking when Pratio is reduced from 1 to 0.5 for the case when Gav=12. Theimprovement, however, is restricted to the case when Gav is less than two thirds of thewavelength capacity. When Gav approaches the wavelength capacity, there is notmuch improvement in the blocking performance even if the protection ratio is reducedto 0.5. This is also expected since a single connection almost completely occupies awavelength for large values of Gav. Thus, the residual capacity on wavelengths is toosmall for future connections to find enough bandwidth, even if the protection ratio issmall.


6.C. Effect of Pratio on Primary and Backup UnavailabilityWe next present the effect of Pratio on primary and backup blocking performance forthe case when W=16 and Gav=24 in Fig. 4(a) and Gav=36 in Fig. 4(b). In particular,it shows the number of connections that were blocked due to primary and backupunavailability for varying values of Pratio.

As the figures show, the number of connections that were blocked due to both pri-mary and backup unavailability increase with increasing values of Pratio for all valuesof Gav. However, the decrease in blocking due to backup unavailability shows a signifi-cant drop compared to the decrease due to primary unavailability. This is againexpected since, with decreasing backup bandwidth requirements, more connectionsare likely to be found with small values of Pratio. Similar results can also be seen inFigs. 5(a) and 5(b), where the percentage of connections blocked due to primary andbackup unavailability for W=32 are shown for Gav=24 and Gav=36, respectively.

These results present one of the primary advantages of using partial protection:with partial protection, we would be blocking a significantly less number of connec-tions due to the unavailability of backup paths than we would when full protection isused. This makes sense because the protection paths are only used if there is a failurein the primary path, and hence, by blocking connections that do not find 100% protec-tion we would not only be reducing the number of connections admitted, we wouldalso end up reserving more backup resources that may never be utilized.

6.D. Effect of Pratio on Quality of ProtectionFigure 6 presents the percentage of connections that were provided full protection fordifferent values of Pratio and Gav: for the case when W=16 in Fig. 6(a) and for the casewhen W=32 in Fig. 6(b).

Fig. 3. Blocking performance versus protection ratio for NSFnet topology.


Note that with Pratio=1, connections are accepted only if they can be given full pro-tection, and hence, all accepted connections will have full protection. As can be seen inFig. 6(a), even with Pratio=0.5, approximately 98% of the connections get full (100%protection bandwidth) protection. As expected, when Gav increases, the restorabilityalso increases due to the lack of resources in the network (although the reduction isnot significant). Also, with increasing Pratio, the percentage of connections restoredincreases due to the fact that the amount of capacity that needs to be restored is lesscompared to that with lesser values of Pratio. There are however, certain cases wherethere is a slight decrease in the percentage of connections that receive 100% protec-tion [Gav=24 Fig. 6(a) and Gav=36 in Fig. 6(b)]. One possible reason for this is therandom nature of failure generation, which might sometimes occur on links wherethere are more affected light paths, and it may so happen that one of those light pathscould not be restored with full protection. This is especially true when there are veryfew connections that receive less than 100% protection, and the addition of even asingle connection to that list would affect the result. Note that with Gav=OC-48, thereis almost 100% restorability for most cases. This is because with Gav=OC-48, everyconnection requests a complete wavelength, and hence, the bandwidth saved with par-tial protection is never utilized by other connections. Similar trends of results areseen for the case when W=32 as illustrated in Fig. 6(b). These results represent theforemost advantage of using partial protection in groomed networks, whereby connec-tions not only experience less blocking but are also able to survive failures whileobtaining close to 100% protection against single link failures. For instance, for thecase when Gav=36 and W=32, we can notice that the percentage of connections thatget 100% protection changes from 98% to close to 100% when P is changed from

Fig. 4. Blocking performance versus primary/backup unavailability.

ratio

Fig. 5. Protection ratio versus primary/backup unavailability.


Fig. 6. Protection ratio versus percent connections with full protection.


0.5 to 1. At the same time, we can notice from Fig. 3(b) that for the same case theblocking performance improves from 0.05 to 0.007 (an improvement of 86%) whenPratio is changed from 1 to 0.5.

6.E. Effect of Resistance Factor on Backup ContentionWe finally plot the effect of choosing link-disjoint paths based on the resistance factorexplained in Subsection 5.A. Figure 7 plots the percentage increase in average conten-tion per link �Cav� as a function of Gav, the average primary bandwidth required perconnection for varying values of W. The average link contention indicates the averagenumber of connections that would contend for backup capacity when a link randomlychosen from the links in the network fails. The figure shows the percentage improve-ment (reduction) in average link contention when the resistance factor is taken in toaccount for selecting the link-disjoint pair for a connection as opposed to the casewhen the first available link-disjoint pair is chosen.

As can be seen in the figure, when the resistance factor is taken into account, theaverage link contention is reduced for all values of Gav and W. The improvement ismore pronounced for smaller values of W. For instance, for W=8, around 120% reduc-tion in average contention is seen for most values of Gav. This justifies the use of theproposed heuristic for the route selection process.

7. ConclusionsIn this paper, we studied the problem of enabling partial protection in the design ofsurvivable WDM grooming networks. With partial protection, the backup capacityreserved for a connection would be a fraction of the primary bandwidth requirement.The objective of our design was to admit as many connections as possible with mini-mum protection requirements before exploiting more wavelengths for additional pro-tection capacity. We considered networks with static and dynamic traffic demands.For static traffic, we decomposed the design problem into two subproblems, namely,resource minimization and protection maximization, and formulated each as an inte-ger linear programming optimization problem. For dynamic traffic, we presented aheuristic technique that combined the advantages of both proactive and reactiveapproaches to survivability while trying to maximize the quality of protection offeredto each connection. Further, the technique was designed in such a way as to minimizethe backup contention that would arise when light paths affected by a failure searchfor additional backup capacity in the residual network. The results for both static anddynamic traffic scenarios show that partial protection is a useful compromise whenthe network resources are limited and hence not sufficient to provide full protectionfor every request.

AcknowledgmentsPart of the research was supported by National Science Foundation (NSF) grantsANI-0322959, ANI-0306007, and ANI-0434872. Part of the work was presented at the

Fig. 7. Impact of the resistance factor on the backup contention.


IEEE DSN 2005 Conference and at the BroadNets 2006 Conference. Mahesh Sivaku-mar is currently with Cisco Systems, San Jose, California, USA.

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design and analysis of partial protection mechanisms in groomed optical wdm mesh networks

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