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Wavelength Assignment Vs. Wavelength Converter Placement in Wavelength-Routed Optical WDM Networks
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Procedia Computer Science 00 (2019) 000–000 Procedia Computer Science 00 (2019) 000–000
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Procedia Computer Science 160 (2019) 766–771
The International Workshop on Emerging Networks and Communications The International Workshop on Emerging Networks and Communications (IWENC 2019) (IWENC 2019) Portugal November 4-7, 2019, Coimbra, November 4-7, 2019, Coimbra, Portugal
Wavelength Assignment Vs. Wavelength Converter Placement in Wavelength Assignment Vs. Wavelength Converter Placement in Wavelength-Routed Optical WDM Networks Wavelength-Routed Optical WDM Networks Amiyne Zakouni*, Hicham Toumi, Abdelali Saidi, Abdelfettah Mabrouk Amiyne Zakouni*, Hicham Toumi, Abdelali Saidi, Abdelfettah Mabrouk ESTSB, Chouaïb Doukkali University, 24000 El Jadida, Morocco ESTSB, Chouaïb Doukkali University, 24000 El Jadida, Morocco
Abstract Abstract In this paper, we deal with the wavelength assignment and the converter placement problem in wavelength-routed optical WDM In thisnetworks. paper, weOur dealobjective with the is wavelength assignment and theinconverter placement in wavelength-routed opticaltoWDM Mesh to try to assign wavelengths an efficient manner problem with/without wavelength conversion get a Mesh networks. Ourprobability objective isand to try to assign in of an the efficient manner with/without to get very low blocking optimize thewavelengths performance overall network. Thus, wewavelength implementconversion and compare thea very low blocking and optimize the performance of theWavelength overall network. Thus, weand implement and compare the performance of twoprobability proposed algorithms namely DWA “Dynamic Assignment” SWA “Static Wavelength performance two proposed algorithms. algorithms namely Assignment” SWAapproaches, “Static Wavelength Assignment” of with well-known We first DWA present“Dynamic a literatureWavelength review about previously and proposed and then Assignment” well-known algorithms. We first present literature review about previously proposed approaches, then we introduce with and evaluate our implemented approaches. Weaalso discuss the wavelength converter placement problemand in mesh we introduce evaluate our implemented approaches. We alsoextensive discuss the wavelength converter placement problem in mesh networks. We and finally corroborate our theoretical findings through simulations. networks. We finally corroborate our theoretical findings through extensive simulations. © 2019 The Authors. Published by Elsevier B.V. © 2019 The Authors. Published by Elsevier B.V. © 2019 The Authors. by Elsevier This is an open accessPublished article under the CC B.V. BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility the Conference Program Chairs. Peer-review under responsibility ofofthe Conference Program Chairs. Peer-review under responsibility of the Conference Program Chairs. Keywords: Routing and wavelength assignment (RWA); Wavelength converters; Blocking probability; Optimization; Converter placement; Metaheuristics; Wavelength divisionassignment multiplexing (WDM). Keywords: Routing and wavelength (RWA); Wavelength converters; Blocking probability; Optimization; Converter placement; Metaheuristics; Wavelength division multiplexing (WDM).
1. Introduction 1. Introduction The future of many applications such as video conferencing and e-Science will employ a massive amount of data. futurethese of many applications as video conferencing will employ a massive amount division of data. To The support applications, thesuch next-generation Internet and will e-Science be predicated on optical wavelength To support these applications, the next-generation Internet will be predicated on optical wavelength division multiplexing (WDM) networks that can afford immense amounts of bandwidth [1]. To meet growing bandwidth multiplexing (WDM) networks that can afford immense amounts of bandwidth [1]. To meet growing bandwidth
* Corresponding author. Tel.: +212697711172; fax: +0-000-000-0000 . E-mail address:author. [email protected] * Corresponding Tel.: +212697711172; fax: +0-000-000-0000 . E-mail address: [email protected] 1877-0509 © 2019 The Authors. Published by Elsevier B.V. This is an open access under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) 1877-0509 © 2019 Thearticle Authors. Published by Elsevier B.V. Peer-review under responsibility of the Conference Program Chairs. This is an open access article under CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs. 1877-0509 © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs. 10.1016/j.procs.2019.11.013
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demand, established carriers have built their optical WDM networks with Synchronous Optical Network / Synchronous Digital Hierarchy (SONET/SDH) ring architectures in many sites around the globe. But as we enter into next generation network era, these SONET rings will not be able to provide the required bandwidth [2]. Mesh networks, built on new-world optical cross connects (OXCs), exploit a combination of IP and SONET based mechanisms to bring dynamic provisioning and fast deterministic shared protection. In WDM networks, each fiber is divided into a number of wavelengths, each capable of transmitting data [3-4]. This allows each fiber to provide data transmission rates of terabits per second. When a connection request arrives at the network, the request must be routed over the network and assigned a wavelength. This is known as the routing and wavelength assignment (RWA) problem [5]. The union of a route and wavelength is identified as a lightpath. To establish a lightpath, it is normally required that the same wavelength be assigned on all the links along the path. This limitation is known as the wavelength continuity constraint. There are two variants of the RWA problem [6]: static and dynamic RWA [7]. The path chosen to establish a connection reflects the current use of links in the network, and a request is blocked if there is no available route to carry it [8]. As a matter of fact the main aim of many researches is to realize efficient algorithms for establishing lightpaths that reduce the blocking probability in the network [6][9]. The aim of this paper is to present convincing evidence that wavelength assignment issue and wavelength converter placement need to be considered jointly, and calls for reexamination of these two issues. The rest of this paper is organized as follows. In section 2, we review the related work necessary for this paper. Section 3, proposes our two assignments algorithms. Section 4 experimental results and a comparison between the proposed approaches are presented. Finally, conclusions and future work of this article are drawn in section 5. 2. Related Work In recent times, much research related to Wavelength-Routed Optical WDM Networks in metropolitan areas focused on Ring topologies [10-12]. As Mesh networks become the most popular topologies in metropolitan networks, most networking operators are shifting from ring to mesh topology [13]. Generally, wavelength assignment schemes were mostly dynamic in nature [6][14][15]. In contrast, static assignment schemes have not been studied in any depth. In fact, wavelength assignment is regarded as one of the primary factors that can affect the blocking probability and thereby the overall performance of a network. In Random wavelength assignment, the node keeps a list of free wavelengths at every instant, whenever a request is generated the node randomly selects a free wavelength λi from the set of wavelengths and assigns that wavelength to that request [15]. The set of free wavelengths is updated by removing λi from the free list. Upon completion of the request, wavelength λi is eliminated from the list of used wavelengths and is added to the set of free wavelengths. The random selection of a wavelength makes contention for the wavelength low thereby leading in higher blocking rate. First-fit wavelength assignment approach is implemented by predefining an order on the wavelengths. The list of used and free wavelengths is maintained. The assignment approach always chooses the lowest indexed wavelength λj from the list of free wavelengths and assigns it to the request [15]. When the request is completed the wavelength λj is added again to the free wavelength list. The disadvantage of this strategy is that lower indexed wavelengths are much more heavily used compared to others which results in a higher blocking probability. Thus, proper assignment of wavelengths can lead to decreased or no use of wavelength converters which can significantly minimize the cost [6]. Moreover, most of the research was confined to limiting the number of wavelength converters and to choosing optimal converter placement for a fixed number of converters as to enhance the network efficiency [16]. Hence, a network in which few nodes are equipped with full or limited wavelength conversion capability is more practical. Such a network is referred to as a sparse wavelength conversion network. Thus, the problem of choosing the appropriate nodes to place the converters in the network becomes significant. This problem is referred to as the converter placement problem [17-18]. 3. Proposed Algorithms We assume that having an effective wavelength assignment method can outperform networks with/without wavelength converters while lowering costs. We propose static and dynamic assignment techniques for mesh topologies based on a XY routing technique. Our approaches attempt to use available wavelengths in such a way that
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contention for the same wavelength is reduced. In order to show that our approaches work well, we had to rely on extensive simulations.
3.1. Dynamic Wavelength Assignment “DWA” We propose an implemented dynamic wavelength assignment named DWA strategy for mesh topologies. Under this strategy, the wavelengths are indexed and the assignment algorithm begins by assigning the first numbered wavelength for the first requested lightpath at that node. When a subsequent request arrives, the node selects the next numbered wavelength and so on. This method continues in a circular way. After all the wavelengths in the available set have been assigned, the first wavelength is reached again. In this manner, each wavelength is used for wavelength assignment at some point. Therefore, we try to use available wavelengths at all the nodes in the network to the maximum extent possible, so as to reduce the blocking probability. 3.2. Static Wavelength Assignment “SWA” In our implemented static assignment strategy, each node will be allocated a specific wavelength. Whenever a request is generated at a node, it allocates the designated wavelength to that request. For every lightpath request that is generated at any time at a given node, that node will use the same designated wavelength. A possible assignment scheme for an 8*8 mesh topology with 16 wavelengths is shown in Fig. 1. Here it is assumed that there are an equal numbers of wavelengths per fiber that are also equal to the number of nodes in each dimension. In this scheme each node is assigned to utilize the wavelength whose index equals to the node column number. If we assume dimension (order XY) routing, then it can be seen from the figure that during routing no request can be blocked in the row. Blocking happens only on the columns.
Fig. 1: A possible static assignments in 2D mesh topology with 16 wavelengths.
4. Numerical Results and Analysis We developed a simulator to implement wavelength assignment in Mesh topologies. The simulator accepts input parameters such as the dimensions of the mesh network, number of wavelengths per fiber, and converter placement. The ratio of the total number of requests blocked to the total number of requests that arrived at all the nodes in the network is defined as the blocking probability. The output of the simulator is the blocking rate for the specified parameters. The simulator assumes that the origin and the destination of the arrived request must be available in order to establish the lightpath for that request. If either is busy then that request is not counted in calculating the blocking probability. First, we compare the dynamic assignment strategies varying the parameters for the mesh and the traffic. Then, we present the results obtained for some static assignment strategies. Additionally, we compare proposed dynamic assignments with proposed static assignments. Wavelength converter placement is also discussed for mesh topology with different converter placements. 4.1. Dynamic Wavelength Assignment “DWA” All wavelengths are used equally in the DWA technique. This helps in reducing the blocking probability considerably. Fig. 2 compares the outcomes of the three assignment approaches.
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Fig. 2: Blocking Probability for Dynamic assignments.
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Fig. 3: Blocking Probability for Different Number of Wavelengths.
From figure 2 it is evident that First-Fit assignment performs poorly when compared to the other assignment methods. The Random assignment scheme works better than First-Fit as it attempts to use the wavelengths in a better way. However, it can be seen that our implemented DWA algorithm performs better than the others for different arrival rates. Depending on the arrival rate, the improvement over Random assignment varies from 8% to 18%. Improvement of 65% to 75% is obtained over first-fit assignment. When the rate of arrival is lower, requests at the nodes are fewer and hence contention for an identical wavelength is less. As the arrival rates increase, the number of requests increases, contention for wavelengths becomes higher, and blocking probability increases. Figure 3 it is noted that the increase in blocking probability for higher arrival rates is negligible for DWA techniques. 20% to 40% improvement is obtained using 16 wavelengths with DWA over 8 wavelengths. DWA performs better than Random assignment, even with 16 wavelengths. We noted also a 15% to 30% improvement over random assignment for different arrival rates. In figure 4, as mesh size grows, the average distance between source and destination is increased which implies a boost in the number of links. The number of requests also increases. The change in mesh size can result in higher blocking probability as the network size increases for a fixed number of wavelengths. It can be seen, for instance, that as the size increases from 8*8 to 12*12, the blocking probability increases by 20% with DWA, whereas the increase is 30% with random assignment and 42% with first-fit assignment.
Fig. 4: Blocking Probability for Different Mesh Dimensions.
Fig. 5: Static Wavelength Assignment.
4.2. Static Assignment Strategy From figure 5 it is observed that as the number of wavelengths is increased, the blocking probability gets lower due of the availability of a larger number of wavelengths, which leads to a reduced contention for the same wavelength. However, as the arrival rate is increased the number of requests increases, thereby increasing the blocking probability. As it can be seen, the increase in blocking probability (as the arrival rate increases) is smaller for 16 wavelengths compared to 8 wavelengths. We observed a 30% to 50% reduction in blocking probability with 16 wavelengths compared to 8 wavelengths.
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4.3. Comparison of Dynamic and Static Assignment Strategies Improvement in performance of dynamic assignments is not considerable even when we increase the number of wavelengths. Conversely, static assignments perform much better as the number of wavelengths increases. It can be observed from figure 6, for the 8 wavelength case that the static assignment performs better than the dynamic assignments for the same set of parameters. We noticed a 50% to 60% reduction in blocking probability using SWA schemes with 8 wavelengths compared to the best DWA scheme. Even as the arrival rate increases, in comparison with dynamic schemes, the increase in the probability of blocking is less for the static method. For the case with 16 wavelengths, we observed that the blocking probability is very low for the SWA method. It almost remains constant even at higher arrival rates. Availability of more wavelengths in SWA schemes reduces the contention for the same wavelength. This results in a very low blocking probability. A 55%-65% performance improvement is obtained with 16 wavelengths using the SWA scheme when compared to the DWA method. 4.4. Wavelength Converter Placement problem In this section we propose to investigate the placement of the wavelength converter on a mesh network. According to the heuristics reported in the literature [7][17] placing the converters at the nodes where maximum traffic takes place may be a better option. In mesh topology most of the traffic is concentrated at the center. Figure 7 shows our proposition for different converter placements in an 8*8 mesh network. Simulations are run for the specified converter placements for different assignments strategies.
Fig. 6: Comparison of static and dynamic wavelength assignments (8 & 16 Wavelengths).
Fig. 7: Different converter placements in 8*8 mesh.
Fig. 8: Blocking Probability with Different Number of Converters
In figure 8, as expected, the blocking probability is lower when converters are used. It can be noted from the same figure that even with converters, static assignment still works better than dynamic assignment. It is also noted that even with converters, the improvement obtained is not significant when we take costs into consideration. Hence, it
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can be concluded that assignment strategies affect the blocking probabilities more than the number of converters. So, choosing a good assignment strategy rather than going for converters can be more favorable. As shown in Figure 8, the values on the x-axis represent the number of converters used in an 8*8 mesh. The 16u corresponds to placing the converters uniformly. The 21u corresponds to uniform placement with 21 converters as shown in Figure 7.d. The figure 8 shows also that uniform placement does not yield better results. Even using 21 converters with uniform placement does not yield better results when compared to placing 16 converters at the center. This supports the hypothesis that converters are better utilized when placed at nodes with high traffic. 5. Conclusion and Future work In this article we analyzed wavelength assignment and optimal wavelength converter placement in wavelengthrouted optical WDM Mesh networks. We demonstrated that wavelength assignment is the main factor affecting the blocking probability in regular networks. We proposed and implemented dynamic and static assignment strategies that outperformed techniques previously reported in the literature. The proposed dynamic assignment called “DWA” has a very low blocking probability when compared to Random assignments and First-fit. A performance improvement of around 20% is obtained when compared with Random assignment. When compared with First-fit assignment, the improvement exceeds 70%. The wavelength converters do help in minimizing the blocking probability. However, we have shown that wavelength assignment plays a more significant role than converters in affecting blocking probability. Thus, we conclude that proper assignment of wavelengths yields more favorable results than the utilization of converters alone. Our work has concentrated on regular mesh networks. Further research on more meta-heuristics algorithms in irregular topologies should be conducted. References [1] Upadhyay, K. (2019) “An Improved Routing and Wavelength Assignment Algorithm for WDM Optical Networks.” Available at SSRN 3376495. [2] Gajendran, E., Pradeep, M., & Prabhu, B. (2017) “Systematic Analysis of Congestion Control in WDM Mesh Networks.” Asian Journal of Applied Science and Technology (AJAST) Volume, 1. [3] Zakouni, A., Luo, J., & Kharroubi, F. (2017) “Genetic algorithm and tabu search algorithm for solving the static manycast RWA problem in optical networks.” Journal of Combinatorial Optimization, 33(2), 726-741. [4] Koganti, R. T., & Sidhu, D. (2014) “Analysis of routing and wavelength assignment in large WDM networks.” Procedia Computer Science, 34, 71-78. [5] Kharroubi, F., He, J., Tang, J., Chen, M., & Chen, L. (2015) “Evaluation performance of genetic algorithm and tabu search algorithm for solving the Max-RWA problem in all-optical networks.” Journal of Combinatorial Optimization, 30(4), 1042-1061. [6] Chen, C., & Banerjee, S. (1995) “A new model for optimal routing in all-optical networks with scalable number of wavelength converters.” In Proceedings of GLOBECOM'95 Vol. 2, pp. 993-997. IEEE. [7] Ramamurthy, B., & Mukherjee, B. (1998) “Wavelength conversion in WDM networking.” IEEE Journal on selected areas in communications, 16(7), 1061-1073. [8] Zang, H., Jue, J. P., Sahasrabuddhe, L., Ramamurthy, R., & Mukherjee, B. (2001) “Dynamic lightpath establishment in wavelength routed WDM networks.” IEEE Communications Magazine, 39(9), 100-108. [9] Zakouni, A., Luo, J., & Kharroubi, F. (2016) “Solving the static manycast RWA problem in optical networks using evolutionary programming.” In International Conference on Intelligent Computing. pp. 147-157. Springer, Cham. [10] Triay, J., Cervelló-Pastor, C., & Vokkarane, V. M. (2013) “Analytical blocking probability model for hybrid immediate and advance reservations in optical WDM networks. IEEE/ACM Transactions on Networking,” 21(6), 1890-1903. [11] Chatterjee, B. C., Sarma, N., & Sahu, P. P. (2013). “Review and performance analysis on routing and wavelength assignment approaches for optical networks.” IETE Technical Review, 30(1), 12-23. [12] Randhawa, R., & Sohal, J. S. (2010) “Blocking probability analysis of survivable routing in WDM optical networks with/without sparsewavelength conversion.” Optik-International Journal for Light and Electron Optics, 121(5), 462-466. [13] Zang, H. (2012) “WDM mesh networks: management and survivability.” Springer Science & Business Media. [14] Paira, S., & Bhattacharya, U. (2018) “Efficient dynamic survivable multicasting in WDM mesh networks.” In 2018 10th International Conference on Communication Systems & Networks (COMSNETS) (pp. 525-527). IEEE. [15] Zang, H., Jue, J. P., & Mukherjee, B. (2000). A review of routing and wavelength assignment approaches for wavelength-routed optical WDM networks. Optical networks magazine, 1(1), 47-60. [16] Wason, A., & Kaler, R. S. (2011) “Blocking in wavelength-routed all-optical WDM network with wavelength conversion.” OptikInternational Journal for Light and Electron Optics, 122(7), 631-634. [17] Shimizu, S., Arakawa, Y., & Yamanaka, N. (2006). Wavelength assignment scheme for WDM networks with limited-range wavelength converters. Journal of Optical Networking, 5(5), 410-421. [18] Patil, P. R., & Patil, B. V. (2015) “Routing and re-routing scheme for cost effective mechanism in WDM Network.” Procedia Computer Science, 49, 155-161.
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Procedia Computer Science 160 (2019) 766–771
The International Workshop on Emerging Networks and Communications The International Workshop on Emerging Networks and Communications (IWENC 2019) (IWENC 2019) Portugal November 4-7, 2019, Coimbra, November 4-7, 2019, Coimbra, Portugal
Wavelength Assignment Vs. Wavelength Converter Placement in Wavelength Assignment Vs. Wavelength Converter Placement in Wavelength-Routed Optical WDM Networks Wavelength-Routed Optical WDM Networks Amiyne Zakouni*, Hicham Toumi, Abdelali Saidi, Abdelfettah Mabrouk Amiyne Zakouni*, Hicham Toumi, Abdelali Saidi, Abdelfettah Mabrouk ESTSB, Chouaïb Doukkali University, 24000 El Jadida, Morocco ESTSB, Chouaïb Doukkali University, 24000 El Jadida, Morocco
Abstract Abstract In this paper, we deal with the wavelength assignment and the converter placement problem in wavelength-routed optical WDM In thisnetworks. paper, weOur dealobjective with the is wavelength assignment and theinconverter placement in wavelength-routed opticaltoWDM Mesh to try to assign wavelengths an efficient manner problem with/without wavelength conversion get a Mesh networks. Ourprobability objective isand to try to assign in of an the efficient manner with/without to get very low blocking optimize thewavelengths performance overall network. Thus, wewavelength implementconversion and compare thea very low blocking and optimize the performance of theWavelength overall network. Thus, weand implement and compare the performance of twoprobability proposed algorithms namely DWA “Dynamic Assignment” SWA “Static Wavelength performance two proposed algorithms. algorithms namely Assignment” SWAapproaches, “Static Wavelength Assignment” of with well-known We first DWA present“Dynamic a literatureWavelength review about previously and proposed and then Assignment” well-known algorithms. We first present literature review about previously proposed approaches, then we introduce with and evaluate our implemented approaches. Weaalso discuss the wavelength converter placement problemand in mesh we introduce evaluate our implemented approaches. We alsoextensive discuss the wavelength converter placement problem in mesh networks. We and finally corroborate our theoretical findings through simulations. networks. We finally corroborate our theoretical findings through extensive simulations. © 2019 The Authors. Published by Elsevier B.V. © 2019 The Authors. Published by Elsevier B.V. © 2019 The Authors. by Elsevier This is an open accessPublished article under the CC B.V. BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility the Conference Program Chairs. Peer-review under responsibility ofofthe Conference Program Chairs. Peer-review under responsibility of the Conference Program Chairs. Keywords: Routing and wavelength assignment (RWA); Wavelength converters; Blocking probability; Optimization; Converter placement; Metaheuristics; Wavelength divisionassignment multiplexing (WDM). Keywords: Routing and wavelength (RWA); Wavelength converters; Blocking probability; Optimization; Converter placement; Metaheuristics; Wavelength division multiplexing (WDM).
1. Introduction 1. Introduction The future of many applications such as video conferencing and e-Science will employ a massive amount of data. futurethese of many applications as video conferencing will employ a massive amount division of data. To The support applications, thesuch next-generation Internet and will e-Science be predicated on optical wavelength To support these applications, the next-generation Internet will be predicated on optical wavelength division multiplexing (WDM) networks that can afford immense amounts of bandwidth [1]. To meet growing bandwidth multiplexing (WDM) networks that can afford immense amounts of bandwidth [1]. To meet growing bandwidth
* Corresponding author. Tel.: +212697711172; fax: +0-000-000-0000 . E-mail address:author. [email protected] * Corresponding Tel.: +212697711172; fax: +0-000-000-0000 . E-mail address: [email protected] 1877-0509 © 2019 The Authors. Published by Elsevier B.V. This is an open access under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) 1877-0509 © 2019 Thearticle Authors. Published by Elsevier B.V. Peer-review under responsibility of the Conference Program Chairs. This is an open access article under CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs. 1877-0509 © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs. 10.1016/j.procs.2019.11.013
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demand, established carriers have built their optical WDM networks with Synchronous Optical Network / Synchronous Digital Hierarchy (SONET/SDH) ring architectures in many sites around the globe. But as we enter into next generation network era, these SONET rings will not be able to provide the required bandwidth [2]. Mesh networks, built on new-world optical cross connects (OXCs), exploit a combination of IP and SONET based mechanisms to bring dynamic provisioning and fast deterministic shared protection. In WDM networks, each fiber is divided into a number of wavelengths, each capable of transmitting data [3-4]. This allows each fiber to provide data transmission rates of terabits per second. When a connection request arrives at the network, the request must be routed over the network and assigned a wavelength. This is known as the routing and wavelength assignment (RWA) problem [5]. The union of a route and wavelength is identified as a lightpath. To establish a lightpath, it is normally required that the same wavelength be assigned on all the links along the path. This limitation is known as the wavelength continuity constraint. There are two variants of the RWA problem [6]: static and dynamic RWA [7]. The path chosen to establish a connection reflects the current use of links in the network, and a request is blocked if there is no available route to carry it [8]. As a matter of fact the main aim of many researches is to realize efficient algorithms for establishing lightpaths that reduce the blocking probability in the network [6][9]. The aim of this paper is to present convincing evidence that wavelength assignment issue and wavelength converter placement need to be considered jointly, and calls for reexamination of these two issues. The rest of this paper is organized as follows. In section 2, we review the related work necessary for this paper. Section 3, proposes our two assignments algorithms. Section 4 experimental results and a comparison between the proposed approaches are presented. Finally, conclusions and future work of this article are drawn in section 5. 2. Related Work In recent times, much research related to Wavelength-Routed Optical WDM Networks in metropolitan areas focused on Ring topologies [10-12]. As Mesh networks become the most popular topologies in metropolitan networks, most networking operators are shifting from ring to mesh topology [13]. Generally, wavelength assignment schemes were mostly dynamic in nature [6][14][15]. In contrast, static assignment schemes have not been studied in any depth. In fact, wavelength assignment is regarded as one of the primary factors that can affect the blocking probability and thereby the overall performance of a network. In Random wavelength assignment, the node keeps a list of free wavelengths at every instant, whenever a request is generated the node randomly selects a free wavelength λi from the set of wavelengths and assigns that wavelength to that request [15]. The set of free wavelengths is updated by removing λi from the free list. Upon completion of the request, wavelength λi is eliminated from the list of used wavelengths and is added to the set of free wavelengths. The random selection of a wavelength makes contention for the wavelength low thereby leading in higher blocking rate. First-fit wavelength assignment approach is implemented by predefining an order on the wavelengths. The list of used and free wavelengths is maintained. The assignment approach always chooses the lowest indexed wavelength λj from the list of free wavelengths and assigns it to the request [15]. When the request is completed the wavelength λj is added again to the free wavelength list. The disadvantage of this strategy is that lower indexed wavelengths are much more heavily used compared to others which results in a higher blocking probability. Thus, proper assignment of wavelengths can lead to decreased or no use of wavelength converters which can significantly minimize the cost [6]. Moreover, most of the research was confined to limiting the number of wavelength converters and to choosing optimal converter placement for a fixed number of converters as to enhance the network efficiency [16]. Hence, a network in which few nodes are equipped with full or limited wavelength conversion capability is more practical. Such a network is referred to as a sparse wavelength conversion network. Thus, the problem of choosing the appropriate nodes to place the converters in the network becomes significant. This problem is referred to as the converter placement problem [17-18]. 3. Proposed Algorithms We assume that having an effective wavelength assignment method can outperform networks with/without wavelength converters while lowering costs. We propose static and dynamic assignment techniques for mesh topologies based on a XY routing technique. Our approaches attempt to use available wavelengths in such a way that
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contention for the same wavelength is reduced. In order to show that our approaches work well, we had to rely on extensive simulations.
3.1. Dynamic Wavelength Assignment “DWA” We propose an implemented dynamic wavelength assignment named DWA strategy for mesh topologies. Under this strategy, the wavelengths are indexed and the assignment algorithm begins by assigning the first numbered wavelength for the first requested lightpath at that node. When a subsequent request arrives, the node selects the next numbered wavelength and so on. This method continues in a circular way. After all the wavelengths in the available set have been assigned, the first wavelength is reached again. In this manner, each wavelength is used for wavelength assignment at some point. Therefore, we try to use available wavelengths at all the nodes in the network to the maximum extent possible, so as to reduce the blocking probability. 3.2. Static Wavelength Assignment “SWA” In our implemented static assignment strategy, each node will be allocated a specific wavelength. Whenever a request is generated at a node, it allocates the designated wavelength to that request. For every lightpath request that is generated at any time at a given node, that node will use the same designated wavelength. A possible assignment scheme for an 8*8 mesh topology with 16 wavelengths is shown in Fig. 1. Here it is assumed that there are an equal numbers of wavelengths per fiber that are also equal to the number of nodes in each dimension. In this scheme each node is assigned to utilize the wavelength whose index equals to the node column number. If we assume dimension (order XY) routing, then it can be seen from the figure that during routing no request can be blocked in the row. Blocking happens only on the columns.
Fig. 1: A possible static assignments in 2D mesh topology with 16 wavelengths.
4. Numerical Results and Analysis We developed a simulator to implement wavelength assignment in Mesh topologies. The simulator accepts input parameters such as the dimensions of the mesh network, number of wavelengths per fiber, and converter placement. The ratio of the total number of requests blocked to the total number of requests that arrived at all the nodes in the network is defined as the blocking probability. The output of the simulator is the blocking rate for the specified parameters. The simulator assumes that the origin and the destination of the arrived request must be available in order to establish the lightpath for that request. If either is busy then that request is not counted in calculating the blocking probability. First, we compare the dynamic assignment strategies varying the parameters for the mesh and the traffic. Then, we present the results obtained for some static assignment strategies. Additionally, we compare proposed dynamic assignments with proposed static assignments. Wavelength converter placement is also discussed for mesh topology with different converter placements. 4.1. Dynamic Wavelength Assignment “DWA” All wavelengths are used equally in the DWA technique. This helps in reducing the blocking probability considerably. Fig. 2 compares the outcomes of the three assignment approaches.
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Fig. 2: Blocking Probability for Dynamic assignments.
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Fig. 3: Blocking Probability for Different Number of Wavelengths.
From figure 2 it is evident that First-Fit assignment performs poorly when compared to the other assignment methods. The Random assignment scheme works better than First-Fit as it attempts to use the wavelengths in a better way. However, it can be seen that our implemented DWA algorithm performs better than the others for different arrival rates. Depending on the arrival rate, the improvement over Random assignment varies from 8% to 18%. Improvement of 65% to 75% is obtained over first-fit assignment. When the rate of arrival is lower, requests at the nodes are fewer and hence contention for an identical wavelength is less. As the arrival rates increase, the number of requests increases, contention for wavelengths becomes higher, and blocking probability increases. Figure 3 it is noted that the increase in blocking probability for higher arrival rates is negligible for DWA techniques. 20% to 40% improvement is obtained using 16 wavelengths with DWA over 8 wavelengths. DWA performs better than Random assignment, even with 16 wavelengths. We noted also a 15% to 30% improvement over random assignment for different arrival rates. In figure 4, as mesh size grows, the average distance between source and destination is increased which implies a boost in the number of links. The number of requests also increases. The change in mesh size can result in higher blocking probability as the network size increases for a fixed number of wavelengths. It can be seen, for instance, that as the size increases from 8*8 to 12*12, the blocking probability increases by 20% with DWA, whereas the increase is 30% with random assignment and 42% with first-fit assignment.
Fig. 4: Blocking Probability for Different Mesh Dimensions.
Fig. 5: Static Wavelength Assignment.
4.2. Static Assignment Strategy From figure 5 it is observed that as the number of wavelengths is increased, the blocking probability gets lower due of the availability of a larger number of wavelengths, which leads to a reduced contention for the same wavelength. However, as the arrival rate is increased the number of requests increases, thereby increasing the blocking probability. As it can be seen, the increase in blocking probability (as the arrival rate increases) is smaller for 16 wavelengths compared to 8 wavelengths. We observed a 30% to 50% reduction in blocking probability with 16 wavelengths compared to 8 wavelengths.
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4.3. Comparison of Dynamic and Static Assignment Strategies Improvement in performance of dynamic assignments is not considerable even when we increase the number of wavelengths. Conversely, static assignments perform much better as the number of wavelengths increases. It can be observed from figure 6, for the 8 wavelength case that the static assignment performs better than the dynamic assignments for the same set of parameters. We noticed a 50% to 60% reduction in blocking probability using SWA schemes with 8 wavelengths compared to the best DWA scheme. Even as the arrival rate increases, in comparison with dynamic schemes, the increase in the probability of blocking is less for the static method. For the case with 16 wavelengths, we observed that the blocking probability is very low for the SWA method. It almost remains constant even at higher arrival rates. Availability of more wavelengths in SWA schemes reduces the contention for the same wavelength. This results in a very low blocking probability. A 55%-65% performance improvement is obtained with 16 wavelengths using the SWA scheme when compared to the DWA method. 4.4. Wavelength Converter Placement problem In this section we propose to investigate the placement of the wavelength converter on a mesh network. According to the heuristics reported in the literature [7][17] placing the converters at the nodes where maximum traffic takes place may be a better option. In mesh topology most of the traffic is concentrated at the center. Figure 7 shows our proposition for different converter placements in an 8*8 mesh network. Simulations are run for the specified converter placements for different assignments strategies.
Fig. 6: Comparison of static and dynamic wavelength assignments (8 & 16 Wavelengths).
Fig. 7: Different converter placements in 8*8 mesh.
Fig. 8: Blocking Probability with Different Number of Converters
In figure 8, as expected, the blocking probability is lower when converters are used. It can be noted from the same figure that even with converters, static assignment still works better than dynamic assignment. It is also noted that even with converters, the improvement obtained is not significant when we take costs into consideration. Hence, it
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can be concluded that assignment strategies affect the blocking probabilities more than the number of converters. So, choosing a good assignment strategy rather than going for converters can be more favorable. As shown in Figure 8, the values on the x-axis represent the number of converters used in an 8*8 mesh. The 16u corresponds to placing the converters uniformly. The 21u corresponds to uniform placement with 21 converters as shown in Figure 7.d. The figure 8 shows also that uniform placement does not yield better results. Even using 21 converters with uniform placement does not yield better results when compared to placing 16 converters at the center. This supports the hypothesis that converters are better utilized when placed at nodes with high traffic. 5. Conclusion and Future work In this article we analyzed wavelength assignment and optimal wavelength converter placement in wavelengthrouted optical WDM Mesh networks. We demonstrated that wavelength assignment is the main factor affecting the blocking probability in regular networks. We proposed and implemented dynamic and static assignment strategies that outperformed techniques previously reported in the literature. The proposed dynamic assignment called “DWA” has a very low blocking probability when compared to Random assignments and First-fit. A performance improvement of around 20% is obtained when compared with Random assignment. When compared with First-fit assignment, the improvement exceeds 70%. The wavelength converters do help in minimizing the blocking probability. However, we have shown that wavelength assignment plays a more significant role than converters in affecting blocking probability. Thus, we conclude that proper assignment of wavelengths yields more favorable results than the utilization of converters alone. Our work has concentrated on regular mesh networks. Further research on more meta-heuristics algorithms in irregular topologies should be conducted. References [1] Upadhyay, K. (2019) “An Improved Routing and Wavelength Assignment Algorithm for WDM Optical Networks.” Available at SSRN 3376495. [2] Gajendran, E., Pradeep, M., & Prabhu, B. (2017) “Systematic Analysis of Congestion Control in WDM Mesh Networks.” Asian Journal of Applied Science and Technology (AJAST) Volume, 1. [3] Zakouni, A., Luo, J., & Kharroubi, F. (2017) “Genetic algorithm and tabu search algorithm for solving the static manycast RWA problem in optical networks.” Journal of Combinatorial Optimization, 33(2), 726-741. [4] Koganti, R. T., & Sidhu, D. (2014) “Analysis of routing and wavelength assignment in large WDM networks.” Procedia Computer Science, 34, 71-78. [5] Kharroubi, F., He, J., Tang, J., Chen, M., & Chen, L. (2015) “Evaluation performance of genetic algorithm and tabu search algorithm for solving the Max-RWA problem in all-optical networks.” Journal of Combinatorial Optimization, 30(4), 1042-1061. [6] Chen, C., & Banerjee, S. (1995) “A new model for optimal routing in all-optical networks with scalable number of wavelength converters.” In Proceedings of GLOBECOM'95 Vol. 2, pp. 993-997. IEEE. [7] Ramamurthy, B., & Mukherjee, B. (1998) “Wavelength conversion in WDM networking.” IEEE Journal on selected areas in communications, 16(7), 1061-1073. [8] Zang, H., Jue, J. P., Sahasrabuddhe, L., Ramamurthy, R., & Mukherjee, B. (2001) “Dynamic lightpath establishment in wavelength routed WDM networks.” IEEE Communications Magazine, 39(9), 100-108. [9] Zakouni, A., Luo, J., & Kharroubi, F. (2016) “Solving the static manycast RWA problem in optical networks using evolutionary programming.” In International Conference on Intelligent Computing. pp. 147-157. Springer, Cham. [10] Triay, J., Cervelló-Pastor, C., & Vokkarane, V. M. (2013) “Analytical blocking probability model for hybrid immediate and advance reservations in optical WDM networks. IEEE/ACM Transactions on Networking,” 21(6), 1890-1903. [11] Chatterjee, B. C., Sarma, N., & Sahu, P. P. (2013). “Review and performance analysis on routing and wavelength assignment approaches for optical networks.” IETE Technical Review, 30(1), 12-23. [12] Randhawa, R., & Sohal, J. S. (2010) “Blocking probability analysis of survivable routing in WDM optical networks with/without sparsewavelength conversion.” Optik-International Journal for Light and Electron Optics, 121(5), 462-466. [13] Zang, H. (2012) “WDM mesh networks: management and survivability.” Springer Science & Business Media. [14] Paira, S., & Bhattacharya, U. (2018) “Efficient dynamic survivable multicasting in WDM mesh networks.” In 2018 10th International Conference on Communication Systems & Networks (COMSNETS) (pp. 525-527). IEEE. [15] Zang, H., Jue, J. P., & Mukherjee, B. (2000). A review of routing and wavelength assignment approaches for wavelength-routed optical WDM networks. Optical networks magazine, 1(1), 47-60. [16] Wason, A., & Kaler, R. S. (2011) “Blocking in wavelength-routed all-optical WDM network with wavelength conversion.” OptikInternational Journal for Light and Electron Optics, 122(7), 631-634. [17] Shimizu, S., Arakawa, Y., & Yamanaka, N. (2006). Wavelength assignment scheme for WDM networks with limited-range wavelength converters. Journal of Optical Networking, 5(5), 410-421. [18] Patil, P. R., & Patil, B. V. (2015) “Routing and re-routing scheme for cost effective mechanism in WDM Network.” Procedia Computer Science, 49, 155-161.