optimized for each new call and the better performance can be obtained. ... Nokia Research Center, 5 Wayside Rd. Burlington, MA 01803. 2. Dept. of CSE, State ...
A Joint Working and Protection Path Selection Approach in WDM Optical Networks Chunsheng Xin1,2, Yinghua Ye1, Sudhir Dixit1, Chunming Qiao2 1. Nokia Research Center, 5 Wayside Rd. Burlington, MA 01803 2. Dept. of CSE, State University of New York at Buffalo, Buffalo, NY 14260 follows. In section II, we describe our joint path selection approach for working and protection paths. In section III, we discuss the cost function of a link and a path respectively. In section IV, the emulation environment and assumption are described and, in section V, the numerical results are presented and the performance is evaluated and compared with the conventional approach.
Abstract: In survivable WDM optical networks, one of the critical issues is route computation. Although there is a possibility to optimize the route computation (together with the wavelength assignment) for static traffic pattern, it is impossible to perform such optimization for incremental and dynamic traffic. The conventional approach first computes the working path and then computes an edge-disjoint protection path using the shared risk link groups (SRLGs) information of the working path. In this paper, we propose a joint working and protection path selection approach. Our approach tries to find multiple pairs of candidate working and protection paths. Then the pair with the minimum cost sum is selected. We have evaluated the performance benefit gained from the joint path selection approach with a single service class dynamic traffic supporting 1:1 protection scheme.
II JOINT PATH SELECTION APPROACH The conventional path selection approach, named separate path selection (SPS), selects a route (in this paper, a route is an exchangeable terminology of a path) with minimum cost for the working path at first and, then, selects a route with minimum cost for the protection path. However, a point here is that the sum of the working and protection path costs may not be minimal. The motivation of the proposed joint path selection (JPS) approach is that, if the cost sum is minimized, the network resource utilization is individually optimized for each new call and the better performance can be obtained. JPS selects the working and protection paths between a source node and a destination node as follows:
I INTRODUCTION In WDM optical networks, one of the critical issues is path computation and selection to provide the survivability. For static traffic pattern (traffic arriving all at once), there are many studies in the literature to optimize the network resource utilization, such as linear programming. However, for incremental (no lightpath teardown) and dynamic traffic pattern, there is no such optimization approach. In [1], an approach is proposed to address the route and wavelength selection for incremental traffic. For dynamic traffic, generally, the working path is computed first and then the SRLGs information of the working path are built [2]. An edge-disjoint path is then selected as the protection path using the SRLGs information. The route computation of working and protection path is generally based on the shortest path first (SPF) algorithm, with the constraintsbased routing extension. This approach does not consider any optimization at all. It only attempts to find a best (lowest cost) path in each route computation. However, there is one possibility to perform a limited optimization for the dynamic traffic. Although the global optimization for all calls is impossible, we can perform the individual optimization for the working and protection path of each new call request. In this paper, we propose an approach to select the working and protection paths so as to minimize the cost sum of both. The rest of this paper is organized as
STEP 1: Compute K candidate routes with Wi representing the ith ( 1 ≤ i ≤ K ) route and CWi as the cost of Wi . Note that, in a given topology, it is possible that, between two specific nodes, the number of all possible routes is less than K. In such cases, then just compute all possible routes STEP 2: For Wi,, 1 ≤ i ≤ K , Compute an edge-disjoint route, represented as Pi, and the cost of Pi denoted as CPi STEP 3: Find h such that CWh + CPh = MIN( CWi + CPi),
1≤ i ≤ K STEP 4: Select Wh as the working path and Ph as the protection path In the case of SPF-based route computation, a simple method to find K routes between a source and a destination is to compute the shortest path, denoted as R1, at first. In practice, when K is small, e.g. K=2 or K=3, new routes can
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be computed by excluding each link of R1. Of course, some routes computed by this way are probably the same route.
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III COST FUNCTION
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A. Link Cost There are many definitions for link cost in the literature, which can be generally classified into topology-based, resource usage based, or topology and resource usage integrated. The topology based link cost definitions include hop count, link mileage, reliability, etc. The resource usage based link cost definitions include the available λ’s, available λ’s weighted by the total λ’s, etc. The integrated link cost definitions generally integrate both topology information and resource usage information into the cost. In most scenarios, the hop counts and the available λ’s are combined and weighted to form the link cost. In this paper, we propose an integrated link cost definition in the following:
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Fig. 1 The 15-node Mesh Sample Network IV EMULATION We have used emulations to evaluate and compare the performance of JPS and SPS. The emulator is based on the optical control plane proposed in [3]. The sample network [4] contains 15 optical nodes without λ conversion capability, shown in Fig. 1. Each optical node is attached by one single IP/MPLS router which generates call requests. Each link contains two uni-directional fibers, one in each direction. The traffic pattern is dynamic (i.e. the call is established and torn down dynamically) in a single service class with 1:1 shared protection and the Poisson process is used for traffic arrival. The destination of each call is uniformly distributed and the holding time is exponentially distributed. Note that if the holding time of every call is long enough, the traffic pattern become incremental (i.e. no teardown). Currently, we have used the hop count as the link cost and, when all λ’s on a fiber have been used, this fiber (i.e. one direction of the associate link) is considered as disconnected while running SPF algorithm. The first-fit algorithm is used for the wavelength assignment.
LC (l ) = Wu × f (λused , λtotal ) + Wh × 1 where λused is the total used λ’s and λtotal is the total λ’s, Wu and Wh are weights, and f(x, y) is a control function to control the effect of λused , λtotal in the cost. One can simply use identity function for f(x, y). The more complex functions, such as log, polynomial and exponential can be used for them to introduce non-linear effects to the cost. B. Path Cost Generally, for the working path, the path cost is the sum of the link cost at each hop. However, for the protection path, there are two possible scenarios. In the first scenario, similar to the case of working path, the protection path cost is defined as the sum of the link cost. In the second scenario, the λ sharing effect is considered and, thus, the protection path cost is more related to the resource consumption, not only the link cost. Therefore, during the route computation and wavelength assignment, if the protection path will share a λ in an individual link with other protection path(s), the contribution of this specific link cost to the path cost should be significantly reduced. We define the working path cost CW and the protection path cost CP as
V NUMERICAL RESULTS The numerical results are introduced in two parts. The subsection A shows the results where the cost function does not consider the resource sharing among the protection paths and the subsection B shows the results where the cost function has considered such resource sharing. Our intention is not to compare the performance between those two cases, but to compare the performance of JPS and SPS in both cases.
CW ( p ) = ∑ LC (l )
A. The Results Without the Consideration of the Protection Path λ Sharing
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CP ( p ) = ∑ φ ( LC (l ), l )
In this scenario, the λ sharing is not considered during the protection path cost computation. Thus, as in the case of working path, the protection path cost consists of the sum of link cost.
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φ ( LC (l ), l )
equals to LC (l ) when p has no λ sharing with other protection path(s) and is a compression function to shrink the contribution of LC (l ) to CP( p ) .
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Fig. 2 shows the number of the increased accepted calls (IAC) versus the arrival rates using JPS compared with SPS, with 30 seconds average holding time. In the figure, “20call_40LMD” means each node generates 20 calls and each fiber has 40 λ’s. Depending on the traffic volume and the network resource abundance, the number of IAC varies from as low as 6 through as high as 51. However, in our emulations, JPS consistently
Fig. 3 Performance Improvement versus the Number of λ’s Without the λ Sharing Consideration the number of λ's. One may note that the performance improvement of “20call_rate2”, i.e. 20 calls have been generated with the rate of 2 calls per second by each node, decreases from 50 λ's per fiber to 60 λ's per fiber. As explained before, this is due to the abundant λ resource such that both JPS and SPS can satisfy almost all calls. Therefore, there is only a small margin for the performance improvement with 60 λ's per fiber for “20call_rate2”.
Fig. 2 Performance Improvement versus the Arrival Rates Without the λ Sharing Consideration performs better than SPS in all scenarios. In most cases with reasonable amount of resource and traffic, JPS accepts significantly more calls than SPS. Of course, with a low arrival rate and/or adequate resource, e.g. the arrival rate 1 (call/sec), JPS can only obtain minor improvement because almost all calls have been satisfied by both JPS and SPS. From the figure, we can also see that the performance improvement by JPS only has minor fluctuation over the different arrival rate except the arrival rate 1 (the exception has been explained above). This implies that JPS is in favor of the high arrival rates since, as the arrival rate increases, the overall blocking probability increases and, thus, the calls accepted by either JPS or SPS decrease. Therefore, the percentage performance improvement (i.e. IAC divided by the accepted calls by SPS) is greater with the high arrival rates. This implies that JPS can obtain more benefit with a high arrival rate and is thus scalable with the more dynamic traffic.
B. The Protection Path Cost Computation With the Consideration of Path Sharing In this scenario, we consider the λ sharing effect on an individual link while computing the protection path cost. It is possible to use a cost decaying function, constrained by the sharing degree, to apply on the link cost when the protection path shares a λ with other protection path(s) on that link. For the simplicity, in our emulations, we count the cost of such a link as 0 for the protection path cost, except the first protection path.
Fig. 3 shows the performance gain of JPS over SPS against the number of λ’s with 30 sec mean call holding time. In the figure, “20call_rate2” means each node generates 20 calls with the rate of 2 calls/sec (the arrival rate). The emulation results have been obtained with different number of λ's on each fiber. From the figure, we can see that JPS has good scalability in terms of network resource abundance. The performance improvement smoothly increases by an asymptotically linear function, with 1 as the slope, against
Fig. 4 Performance Improvement versus the Arrival Rate With the λ Sharing Consideration
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Fig. 4 presents the benefit gained by JPS in terms of the number of IAC against the call arrival rate. We can see that the performance gain is similar to the case without the λ sharing consideration. Compared with the results in subsection A (Fig. 2), the performance gains have larger fluctuations over different arrival rates. However, all fluctuations are within some certain range and there is no increasing or decreasing trend. Thus the analysis and conclusion from Fig. 2 in subsection A still hold for Fig. 4.
Fig. 6 Performance Improvement versus the Number of NFPC VI CONCLUSION In this paper, we have proposed a joint working and protection path selection approach (JPS) for the dynamic traffic pattern. Our approach attempts to optimize the network resource utilization of each call through minimizing the cost sum of the working and protection paths. The performance is evaluated and compared with the conventional approach (SPS) using emulations. We have considered two cases for the protection path cost function, with or without considering the effect of path sharing. Our results show that JPS is substantially better than SPS in both cases. JPS also scales very well in terms of the network resource abundance and traffic dynamics. We believe that this is resulted from the individual optimization by JPS. The future work will include the more extensive examination of JPS under different link cost functions, e.g. load modified link cost, and multiple classes of traffic, such as a mix of 100% protected and no-protected traffic.
Fig. 5 Performance Improvement versus the Number of λ’s With the λ Sharing Consideration Fig. 5 reveals the performance improvement of JPS versus the number of λ's. The results (IAC and the changing trend) are similar to Fig. 3, with slightly higher IAC in average. Fig. 6 shows the performance improvement of JPS against the number of non-first pair choices (NFPC). As discussed in section II, JPS computes a list of candidate working and protection path pairs, represented as {} with 1 ≤ i ≤ K . Then JPS chooses one pair with minimal cost sum. On the other hand, SPS always selects the first pair, i.e. , as the working and protection path. When the pair chosen by JPS is not the first pair in the list, we call it as a NFPC. We have collected two resulted values, the number of NFPC and IAC from various emulations with a variety of traffic and resource parameters. Then we draw the minimum and maximum gain (in terms of IAC) against the number of NFPC. We can see that JPS obtains the greater benefit when the number of NFPC increases. Thus, when more calls arrive and more NFPC appears in the working and protection path selection, the better performance is gained.
VII REFERENCES 1. 2. 3.
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V. Anand, C. Qiao, "Dynamic Establishment of Protection Paths in WDM Networks", ICCCN 2000 B. Rajagopalan, etc. “IP over Optical Networks: A Framework”, Internet Draft, work in progress. C. Xin, T. Wang, Y. Ye, M. Yoo, S. Dixit and C. Qiao, "On Design and Architecture of an IP over WDM Optical Network Control Plane", ONDM 2001, Feb, 2001, Vienna, Austria. J. Jue, G. Xiao, "An Adaptive Routing Algorithm for Wavelength-Routed Optical Networks with a Distributed Control Scheme", IEEE Computer Communication and Networks 2000
