Different strategies for Dynamic Multicast Traffic ...

Different strategies for Dynamic Multicast Traffic Protection in Elastic Optical Networks Michał Aibin, Student Member, IEEE, and Krzysztof Walkowiak, Senior Member, IEEE

Abstract—Growing popularity of content-oriented services is a significant trend observed recently in communication networks. Due to large volumes of traffic related to these services, the network operators search for new solutions that allow to deliver content to end users in a cost-effective manner. Elastic optical network (EON) is a relatively novel solution for optical networks. The main advantages of EONs compared to traditional wavelength division multiplexing (WDM) optical networks are more efficient use of spectrum resources and support of flexible modulation format conversion. Moreover, there is a strong focus on multicasting, which is perceived as a much better approach for content delivery compared to unicast transmissions. In this paper we concentrate on dynamic multicast routing in survivable EONs. We compare various protection methods that may be applied to protect multicast sessions in EONs. For this purpose, we adapt two dynamic routing algorithms with additional survivability constraints and the possibility to change the modulation format at the regeneration nodes. Using realistic assumptions on EONs and representative network topologies, a wide range of simulations is run. First, we show the results to indicate advantages and disadvantages of various protection methods. In addition, we show gain of enabling partial protection of receivers in multicast trees. The results clearly show that various QoS levels for multicast protection allow to save optical network resources, thus, accept more incoming traffic in the network. Keywords—elastic optical networks, protection methods, dynamic routing, multicast, anycast

I.

I NTRODUCTION

The rapid growth in world-wide communications has significantly modified our way of life. This revolution has led to a fast increase in bandwidth consumption per year. The use of communication networks has become increasingly popular among users. Their usage patterns evolve to include a rise in bandwidth-intensive networking applications. An Elastic Optical Network (EON) technology has the potential to support the continued demands for communication bandwidth. The basic concept of EONs is to fragment the available spectral resources into tight, width-constant spectral slices (optical channels represented in a frequency domain) that correspond to different optical wavelengths. The slices are allocated over an optical path, according to source, destination and volume of a demand [1]. Depending on the traffic volume, an appropriate-sized optical spectrum is allocated to connections in EONs. By breaking the fixed-grid spectrum allocation limit of conventional Wavelength Division Multiplexing networks, M. Aibin and K. Walkowiak are with the Department of Systems and Computer Networks, Faculty of Electronics, Wroclaw University of Science and Technology, Wroclaw, Poland.

EONs increase the flexibility in the connection provisioning as demands may be served in a spectrum-efficient manner. Furthermore, the way we transmit data may enhance performance of optical networks. Instead of using traditional unicast, we may use content-oriented multicasting and anycasting. Multicasting is becoming increasingly important in todays networks. By eliminating the transmission of redundant traffic over certain links, multicasting may improve network performance. The upcoming requests may be realized using candidate lighttrees (CL) [2] or sets of unicast lightpaths (from the source to each destination). In this paper, we decided to use CL approach, as it is more efficient than establishing sets of unicast lightpaths. It was proven in [3]. While EONs provide a larger bandwidth to users and more revenue to service providers, they have potential problems. The most common complication is the failure of a network element (e.g., a link failure), which may cause huge data loss, resulting in a connection disruption in the network. In order to design a survivable optical network, we have to ensure protection. Several protection schemes have been proposed to provide partial or 100% protection against link failures in EONs. In [4], the authors propose a Dedicated Path Protection (DPP) method for static routing problems. In DPP, each connection has its own backup resources. It may result in higher bandwidth consumption, but on the other hand it will always provide 1+1 protection. In multicast, this approach may be achieved by establishing disjoint multicast tree for primary and backup transmissions. In [5], a Shared Backup Path Protection (SBPP) scheme is proposed. It allows working lightpaths to share backup spectrum in their common links, as long as their corresponding primary lightpaths do not share any common link. For multicast flows it will result in sharing lighttrees between different backup connections. There are also several tree protection techniques proposed for WDM networks. In [6], the authors propose segment disjoint protection scheme for Routing and Wavelength Assignment (RWA) problem. Each segment of a primary tree is protected by a disjoint segment in the backup tree, to share the edges or segment. In this paper, we extend three protection approaches (DPP, SBPP and segment protection) for the Routing, Modulation and Spectrum Assignment (RMSA) problem in EONs. Due to the possibility of modulation format (MF) change between the nodes with regenerators [7], the RMSA problem in EONs is more complex than the corresponding RWA problem in WDM networks. During the establishment of multicast sessions, we have to remember that parts of trees may be commonly used by various pairs of senders - receivers, so we need to pick MF wisely. In EONs, it is possible to use different distance-adaptive MFs, for instance BPSK, QPSK, and m-QAM, where m

belongs to 8, 16, 32, 64. The selection of a particular MF is made according to a lightpath characteristic (e.g., path OSNR, path length, bit-rate). Moreover, the MFs may use various spectral efficiency (expressed in [bit/s/Hz]) [8]. It should be noted that with a larger value of spectral efficiency, less resources of spectrum are required to sustain a particular lightpath. Nevertheless, a higher value of an optical signal to noise ratio (OSNR) is required to detect the transmission. In our case, we define the segment as a lightpath between two nodes with regenerators. We describe our extensions in more details in Section II and Section III. There are three main contributions of this paper. First, we propose a new method for optimization of dynamic multicast flows in EONs: the segment-based multicast tree algorithm. According to the best of our knowledge, this is the first paper that addresses the issue of segment-based protection in EONs with the possibility to change MF inside the multicast tree. Second, is a comparison of protection methods in various scenarios (i.e. only multicast traffic; multicast, anycast and unicast traffic). The third contribution is the proposition of partial protection of multicast receivers. We may specify the group of receivers (end-nodes) to whom traffic in multicast sessions will be protected. The remaining of the paper is divided as follows. In Section II we describe the problem. Section III contains the algorithms description. In Section IV we present simulation setup and results, and finally in Section V we conclude our contributions. II.

N ETWORK MODEL

We use similar notations as in [9]. The physical network is modeled as graph G(V ,E,B,L) where V denotes a set of nodes and E is a set of fiber links. Each fiber link may accommodate B frequency slots at most, whereas L=[l(1),l(2),...,l(E)] represents link lengths for each e ∈ E. We assume that R data centers (DCs) are already located at some nodes of the network. We do not take the physical connection between the server and the backbone network node. There are two scenarios of requests considered in this paper. The first, we consider only multicast requests (one-tomany). In the second case, there are three types of request d: unicast (one-to-one), anycast (one-to-one of many) or multicast. The unicast request is described by source node s(d), destination node t(d) and bit-rate c(d). The anycast request is described by source (client) node s(d), downstream bit-rate cdown (d) and upstream bit-rate cup (d). Finally, the multicast request is described by the source node s(d), set of destination nodes T (d) and bit-rate c(d). Notice that in the case of a unicast request, the set of candidate paths include exactly k paths. Concerning anycast requests, the situation is different, i.e., for each downstream (upstream) request the set of candidate paths contains k|R| paths, since each DC node r ∈ R is considered. Furthermore, we assume that each anycast request may be assigned to each DC, because DCs provide the same service of content. For multicast requests, we calculate CLs on demand for each session. Moreover, we assume that various MFs may be used in the EON (Table I). Let M denote a set of available MFs.

According to the considered physical model from [10], for each MF m ∈ M and bit-rate c there are two constants: one that denotes the maximum distance that a particular MF may support; the second defining its Spectral Efficiency (SE). MFs with higher SE allow to use less spectrum, but the transmission distance is shorter than for MFs with lower SE. With a lot of free spectrum, we promote low MFs. However, when we possess a small amount of free spectrum, we promote high MFs to allocate requests more effectively in smaller slots, exposing a lack of available regenerators. In Table I we present example results for different MFs usage with the demand of 400 Gb/s. Finally, we do not allow grooming of the regenerators, therefore one regenerator serves one request at a time. III.

DYNAMIC RMSA P ROBLEM FOR S URVIVABLE M ULTICAST F LOWS

In this section, we formulate the problem of dynamic RMSA in survivable EONs. The objective is to minimize Bandwidth Blocking Probability (BBP), defined as the volume of rejected traffic divided by the volume of all traffic offered to the network, while enabling network survivability. A. Problem formulation The procedures of dynamic RMSA with protection are as follows. First, we want to find the best route to establish a primary connection. When a demand d reaches the EON, the control plane of the network needs to find a feasible path and allocate sufficient spectrum resources. There are several constraints to be met: spectrum contiguity, spectrum continuity and slice opacity. In EONs, continuous spectrum resources to the specific demand need be assigned. In other words, a chosen set of slices have to be used over an entire end-toend optical path. If one frequency slice has been allocated to an existing request, this slice cannot be assigned to another request. We have to remember that different MFs have different transmission range and SE. Therefore, the designed RMSA algorithm must select a path and MF together, to reduce BBP. Constraints for backup path establishment depends on the selected approach. In order to use the DPP approach, each backup path/lighttree needs to be disjoint from its primary path. Moreover, the backup paths/trees cannot share spectrum. For unicast and anycast requests we achieve that by excluding primary paths from all candidate paths before establishing backup connection. With multicast demands we removed primary lighttree from the graph G, and then calculate CL for backup connection. In SBPP approach, backup paths/lighttrees may share resources. In this case, when we search for candidate paths/CL for backup connections, we prefer the links that are already used by different backup connections. The shared path might be shared partially or as a whole lightpath/lighttree. For the case of Segment Based (SB) approach, we calculate all backup paths for unicast, anycast and multicast requests in the same way. We protect each segment (path between two nodes with regenerators) and allow the network to switch from primary to backup path/tree segment in case of failure.

(a)

(b)

(c)

(d)

(e)

(f)

Fig. 1: Examples of creating multicast tree in RMSA problem in EON.

B. Algorithms for RMSA with protection In this subsection, we present methods that we use to evaluate different approaches for protection in EONs. We propose a new algorithm for dynamic multicast protection, as shown in Algorithm 1. For the sake of elaboration, we explain the execution of the algorithm with the help of an example, as shown in Figure 1. Before the arrival of each request, we update the available spectrum in each link. For example shown in Figure 1, the source of transmission is in node a and the receivers are in nodes e, h, i. In the next step, we calculate the processing order of connections between root node s(d) and receivers T (d) in a multicast tree. We sort (s(d), t(d) ∈ T (d)) pairs by the average length of path between (s(d), t(d) ∈ T (d)) in ascending order, based on 10 pre-calculated candidate paths for each (s(d), t(d) ∈ T (d)). After this calculation, we choose the first node pair to establish a connection as show in Figure 1b. The connection is established using one of two RMSA algorithms: Adaptive Modulation and Regenerator-Aware algorithm (AMRA), which

Algorithm 1: Segment-based multicast tree algorithm Data: Multicast session. Optical network with link utilization and regenerators usage. Result: true if primary/backup lighttrees are established, false if not. 1 Update available spectrum in each link; 2 Calculate the processing order of receivers T (d) for each multicast session; 3 Establish a connection between root node s(d) and the first receiver t(d) ∈ T (d) using the RMSA algorithm; 4 For the remaining pairs of (s(d), t(d)) find the best connection between the t(d) ∈ T (d) and the node that is already included in the multicast session tree; 5 Determine the MF and regeneration scheme for the tree creation; 6 For each segment of multicast tree created in steps 2-5 compute a backup path using disjoint links;

was introduced in [9] or Shortest Path First (SPF), which was used as a baseline solution in many papers i.e [11]– [13]. For the remaining pairs we calculate the best connection between the t(d) and the node, that is already in multicast tree. Example is shown in Figure 1c. The shortest links to connect to the existing multicast tree are between e — d and i — g. In the next step (line 5) we need to determine the MF and regeneration scheme in lightpaths. When there are free regenerators, we promote spectrum-efficient MF (i.e., 32QAM or 64-QAM), regenerating the signal in the nodes with regenerators. On the other hand, when we lack regenerators, less efficient MF is used to achieve the connection between nodes in the network (line 5). Note that MF between the nodes may be changed [7]. If we decide to regenerate signal/change MF, the MF needs to be the same for all links on the output of the node until next node with regenerator (Fig. 1d). Finally, we need to ensure protection for multicast tree. In our paper, we compare three approaches. In the first one, we create disjoint multicast tree with Dedicated Path Protection as shown in Fig. 1e. In order to create a disjoint tree, we remove the paths used for primary connections from the graph. That approach provides 100% protection but it consumes a lot of spectrum resources. In the second approach we use SBPP to ensure protection, as described in subsection IIA. In the third approach (Algorithm 1), we calculate paths to protect all the segments of the tree, but the resources are shared by various primary and backup paths. Therefore, we may protect only single link failures. If for example, the link between g – i is broken, we will immediately use link from h – i as shown in Fig. 1f. This is possible because we established shared backup connections for lighttree segments. In addition, each unicast demand d has ensured dedicated or shared path protection, in regards to the considered scenario. For anycast demands we also ensure dedicated or share path protection, with two differences. First we need to establish a backup for downstream and upstream connections, and the second the backup connections have to be connected to the same DC as the primary connection. IV. R ESULTS DISCUSSION The main goal of our experiments is to compare the performance of different protection approaches in the context of dynamic routing with various traffic flows in EONs using different MFs. In this Section we provide the simulation setup, followed by the discussion of achieved results. A. Simulation setup For the experiments, we use two representative networks: United States backbone network US26 (26 nodes, 84 directed links), and pan-European backbone network Euro28 (28 nodes, 82 directed links). The bit-rate of multicast demands is selected in a range 10-100 Gb/s. The average number of receivers in a multicast demand is set to 10. The volume of multicast traffic is calculated as the traffic obtained by all receivers. In particular, if the multicast session bit-rate is 100 Gb/s and the session includes 8 receivers, it makes 800 Gb/s of traffic. We assume that 7 DCs are located in each network. The network has

three interconnection points to other networks used to carry the international traffic. The data provided by DataCenterMap.com determines the location of DCs and interconnection points. We take into consideration the physical impairment of the links and we use regenerators to amplify the signal in the links that require higher MFs. The location of the regenerators is set on the initiation of the simulation. We set a fixed regenerator number per node, equal to 100 for both networks. The number of available slices in each link is set to 640, which is equal to 4 Thz of bandwidth, similar as in currently deployed WDM technology. The model of traffic is created under the forecast in ”Cisco Visual Networking Index” and ”Cisco Global Cloud Index” reports; it shares the traffic forecasts from year 2016. We assume that requests have some lifetime after which they are torn down. In addition, we assume that the requests arrive one-by-one based on a Poisson distribution with the mean arrival rate of λ requests per unit time while their lifetime is exponentially distributed with the mean 1/γ. Hence, the traffic load is λ/γ Erlangs. The number of requests in the simulation scenarios is 105,000. We do not consider the first 5,000 requests because the network loads did not reach a steady-state. In the first set there are only multicast requests. In the second scenario, the distribution of requests is: 35% multicast, 25% anycast, and 40% unicast requests. The main performance metric is BBP defined as the volume of rejected traffic divided by the volume of all traffic offered to the network. In our experiments, we assume that the number of k-shortest paths is 10. The lightpath requests, end nodes, and bit-rate are generated at random using a uniform distribution to provide the percentage share of each traffic type. We use the concept of the physical model of EON as in paper [14]. In detail, we use EON with BV-Ts to implement the PDM-OFDM technology with multiple MFs, selected adaptively between BPSK, QPSK, and m-QAM, where m belongs to 8, 16, 32, and 64. Polarization Division Multiplexing (PDM) allows for doubling the spectral efficiency. The spectral efficiency is set to 1,2,...,6 [b/s/Hz], respectively for these MFs; EON operates within a flexible ITU-T grid of 6.25 GHz granularity. The three types of BV-Ts are applied with different bit-rate limit, 40 Gbps, 100 Gbps, and 400 Gbps. We use a transmission model from [10]. B. Results The main goal of the simulations is to compare different approaches of protection to achieve the lowest BBP. In the first scenario, as shown in Table II and Table III, we compare algorithms execution with multicast requests for Euro28 and US26 networks, respectively. Traffic loads are low to moderate, as we use only multicast requests, which results in faster utilization of network resources. The considered approaches are: No protection (NP), DPP, SBPP and SB. In the second scenario, as shown in Table IV, we compare the same approaches, with anycast, unicast and multicast requests. Traffic loads for this scenario are moderate to high. We skip low traffic loads, as all the algorithms performed well, achieving 0% of BBP. Based on the results found in Tables II to IV, we may draw the following conclusions:

-

-

-

-

-

Moreover, we run simulations to check how different number of receivers in multicast sessions affects protection methods. In more details we examined the influence of multicast sessions size over all proposed path protection methods. The results are shown in Table V. Due to limited space we presented results only for AMRA algorithm, which outperformed SPF method. For low traffic loads in Euro28 network, all methods resulted in good outcomes for the average of 5 and 10 receivers. Moreover, AMRA with SB approach resulted in 0% of BBP and only 0.01% with DPP for the average of 20 receivers. The trend is similar for US26 network. The only difference is that the results have higher BBP. As it was mentioned before, due to larger distances between nodes than in the Euro28, the MFs that are chosen by RMSA algorithms have lower SE, which results in higher utilization of network resources. The differences between various number of receivers are even more clear with moderate traffic. SB protection with average of 15 receivers provide almost 50% better results than DPP approach. In addition, using SB and AMRA algorithm allows to achieve acceptable BBP (≤ 1%) with 10 receivers, which is not possible with other algorithms/protection methods.

40 Average Gain (%)

-

The AMRA algorithm performed better than the SPF algorithm in all scenarios. The advantages of the AMRA algorithm are adaptive penalties for using MFs and constant penalties for using regenerators which result in more efficient usage of network resources such as spectrum and regenerators. We skip presentation of SPF results in US26 network, due to the lack of space. Enabling protection increases the BBP, especially when using spectrum consuming DPP. DPP uses more resources than other methods with low and moderate traffic loads, but provides 1+1 protection. It means that we are always protected in case of singlelink failure, and we are also protected in some multilink failures. The only case of a non-protected multi-link failure is when the primary and backup path/tree of one request are broken at the same time. Moreover, with high traffic loads, other methods achieve poorer results than DPP. DPP always establishes disjoint backup paths/trees, which results in a better distribution of connections in network. Other methods overuse the same resources to establish backup connectivity, especially at the beginning of simulations. It causes congestion around particular nodes in the network, with high traffic loads, and thus increase the BBP. SBPP is about 10%-20% better than DPP in terms of BBP, especially with low and moderate traffic loads. The reason is that the backup paths/trees in SBPP tend to have fewer hops than in DPP. The network operators may decide to protect only single link failures but accept more incoming traffic with this approach. SB protection approach provides the best results with low and moderate traffic loads. It ensures single link protection in the network as SBPP. We may protect optical networks for the majority of link failure scenarios and achieve 10%-15% better results in comparison to SBPP and 20%-25% in comparison to DPP, using SB protection method. This effect is more visible in the scenario, when we have only multicast requests. The general idea of SB protection is more suitable for the multicast sessions, which uses lighttrees, as these are more complex routing structures than paths used for unicast and anycast requests. The trends are similar for both networks. The only difference is that the performance of all protection methods in US26 network is inferior to their performance in the Euro28 network. The nodes are concentrated in the East and the West Coasts in the US26 network while in the Euro28 network are more centralized. Hence, because of larger distances in US26 network, different decisions more significantly affect the network performance. Routing with only multicast requests results in higher spectrum utilization and higher BBP. It is easy to observe, that protecting unicast and anycast requests is less spectrum consuming, than multicast sessions. The network operators should consider load balancing of requests to provide higher efficiency of the routing. This may be achieved by installing Software Defined Controller (SDN) as a central network distribution element.

20

0 400

450

500

550 600 Traffic load (Erlang)

650

700

650

700

(a)

40 Average Gain (%)

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20

0 400

450

500

550 600 Traffic load (Erlang)

(b) DPP - 50% protection

DPP - 25% protection

SBPP - 50% protection

SBPP - 25% protection

SB - 50% protection

SB - 25% protection

Fig. 2: Gains of partial protection in multicast sessions in a) Euro28 and b) US26 networks in comparison to traditional 100% protection using AMRA algorithm.

Finally, we test scenarios with partial protection for multicast sessions. The results are shown in Figure 2. This case will be particularly useful, when network operators want to achieve different level of QoS for end-users. For example, we may protect transmission only for users that paid for a premium service. The premium users may be hospitals that provide e-Health services, police stations, and other various institutions that are required to have 100% of service protection. Alternative users will not have this protection, as it may not be crucial for them. Moreover, we decide to use only AMRA algorithm, as it provides better results than SPF. First observation is that the gain is most significant for the case of DPP. We may achieve 30%-50% better BBP, if we protect only 25% multicast receivers. The gain for 50% of protected users is still high, ranging approximately between 10% and 20%. The big impact of partial protection for DPP may be observed due to a larger decrease of backup connections, than for the other methods that share some backup resources. Partial protection in SBPP and SB results in 5%-10% of gain with 50% of protected traffic. The difference is visible when we protect 25% of multicast receivers only. The gain in SBPP is equal to 20%-30%, whereas for SB is around 10%. That phenomena proves to be a more efficient utilization of backup resources when using SB than the other approaches. The gain is lower, as we have already created efficient path segments to protect as many multicast lighttrees as possible, with minimum optical resources usage. The gains for the US26 network are lower than for the Euro28 network. The routing in the network with larger distances provides poorer results, thus it lowers also the gains of partial protection in multicast sessions. V. C ONCLUSION In this paper, we focused on survivability of multicast transmissions in EONs. We showed how to adapt dynamic routing algorithms, developed for unicast and anycast transmissions in EONs, to account for multicasting. We introduced additional protection schemes and an opportunity to change the modulation format at the regeneration nodes. With the use of these algorithms, we compared three approaches for survivable multicasting in EONs, these are: Dedicated Path Protection, Shared Backup Path Protection and Segment-Based Protection. It should be stressed that our work is the first that addresses the issue of segment-based protection in EONs with the possibility to change MF inside the multicast tree. Extensive simulations show the pros and cons of different protection methods. Network operators may decide to use the DPP methods that provide 1 + 1 protection, using more spectrum and reducing the traffic loads in the network. On the other hand the SBPP method increases the traffic load in the same network, but does not guarantee 1+1 protection. Therefore, the most effective method of protecting multicast trees for small and medium traffic loads is our proposed SB protection. It provides the same protection as SBPP, indicating the highest efficiency in spectrum use. In addition, in order to reduce BBP and operate more customers, network operators may opt for partial protection. The results show that with different levels of QoS, we are able to reduce BBP up to 30%40%. For future projects, we plan to develop cross-stratum

optimization scenarios, with simultaneous optimization of DC and optical resources. ACKNOWLEDGMENT The work of M. Aibin and K. Walkowiak was supported by the Polish National Science Center (NCN) under Grant DEC2012/07/B/ST7/01215 and statutory funds of the Department of Systems and Computer Networks, Wroclaw University of Science and Technology. R EFERENCES [1]

[2]

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M. Jinno, H. Takara, and B. Kozicki, “Concept and enabling technologies of spectrum-sliced elastic optical path network (slice),” in Asia Communications and Photonics Conference and Exhibition, 2009. L. Sahasrabuddhe and B. Mukherjee, “Light trees: optical multicasting for improved performance in wavelength routed networks,” IEEE Communications Magazine, vol. 37, no. 2, pp. 67–73, 1999. S. Sankaranarayanan and S. Subramaniam, “Comprehensive performance modeling and analysis of multicasting in optical networks,” IEEE Journal on Selected Areas in Communications, vol. 21, no. 9, pp. 1399– 1413, 2003. M. Klinkowski and K. Walkowiak, “Offline rsa algorithms for elastic optical networks with dedicated path protection consideration,” in International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, 2012, pp. 670–676. G. Shen and M. Zukerman, “Spectrum-efficient and agile co-ofdm optical transport networks: architecture, design, and operation,” IEEE Communications Magazine, vol. 50, no. 5, pp. 82–89, 2012. A. K. Pradhan and T. De, “Survivable of multicast traffic grooming against single link failures in wdm mesh networks,” in International Conference on the Applications of Digital Information and Web Technologies (ICADIWT), 2014. B. J. M. Simmons, “Optical network design and planning,” Springer Publishing Company, no. 2nd Edition, pp. 1–7, 2014. M. Jinno, B. Kozicki, H. Takara, A. Watanabe, Y. Sone, T. Tanaka, and A. Hirano, “Distance-adaptive spectrum resource allocation in spectrum-sliced elastic optical path network,” IEEE Communications Magazine, vol. 48, no. 8, pp. 138–145, 2010. M. Aibin and K. Walkowiak, “Adaptive modulation and regeneratoraware dynamic routing algorithm in elastic optical networks,” in IEEE International Conference on Communications (ICC), 2015, pp. 5138 – 5143. C. T. Politi, V. Anagnostopoulos, C. Matrakidis, a. Stavdas, A. Park, M. Heath, and U. Kingdom, “Dynamic operation of flexi-grid ofdm-based networks,” Optical Fiber Communication Conference and Exposition and the National Fiber Optic Engineers Conference (OFC/NFOEC), vol. 1, p. OTh3B.2, 2012. Z. Zhu, S. Member, W. Lu, L. Zhang, and N. Ansari, “Dynamic service provisioning in elastic optical networks with hybrid single- / multi-path routing,” Journal of Lightwave Technology, vol. 31, no. 1, pp. 15–22, 2013. N. Wang and J. P. Jue, “Holding-time-aware routing, modulation, and spectrum assignment for elastic optical networks,” Global Communications Conference (GLOBECOM), 2014 IEEE, pp. 2180–2185, 2014. Y. Wang, X. Cao, and Y. Pan, “A study of the routing and spectrum allocation in spectrum-sliced elastic optical path networks,” Proceedings - IEEE INFOCOM, pp. 1503–1511, 2011. M. Klinkowski and K. Walkowiak, “On the advantages of elastic optical networks for provisioning of cloud computing traffic,” Network, IEEE, vol. 27, no. 6, pp. 44–51, 2013.

A PPENDIX TABLE I: Example of spectrum usage and transmission reach for the 400 Gb/s demand and different MFs. Modulation Format

SE [b/s/Hz]

Number of slices

Range [km]

Modulation Format

SE [b/s/Hz]

Number of slices

Range [km]

BPSK QPSK 8-QAM

1 2 3

34 18 14

1912 1200 989

16-QAM 32-QAM 64-QAM

4 5 6

10 10 8

779 569 359

TABLE II: Comparison of BBP levels in different protection approaches in Euro28 network with multicast flows only. SPF SPF SPF SPF

-

NP DPP SBPP SB

AMRA AMRA AMRA AMRA

-

NP DPP SBPP SB

300 Erlangs

350 Erlangs

400 Erlangs

450 Erlangs

500 Erlangs

550 Erlangs

600 Erlangs

650 Erlangs

700 Erlangs

0.00% 0.00% 0.00% 0.00%

0.10% 0.18% 0.16% 0.11%

0.24% 0.43% 0.35% 0.27%

0.66% 1.34% 1.09% 0.79%

1.17% 1.92% 1.55% 1.30%

1.46% 2.55% 2.16% 1.82%

1.99% 3.24% 2.70% 2.34%

2.95% 3.54% 4.96% 4.65%

3.02% 4.27% 6.09% 9.74%

0.00% 0.00% 0.00% 0.00%

0.00% 0.00% 0.00% 0.00%

0.13% 0.21% 0.20% 0.15%

0.42% 0.75% 0.70% 0.52%

0.81% 1.25% 1.02% 0.90%

1.03% 1.99% 1.81% 1.27%

1.39% 2.31% 1.85% 1.65%

2.33% 2.69% 3.10% 3.83%

2.70% 2.91% 3.25% 6.67%

TABLE III: Comparison of BBP levels in different protection approaches in US26 network with multicast flows only. AMRA AMRA AMRA AMRA

-

NP DPP SBPP SB

300 Erlangs

350 Erlangs

400 Erlangs

450 Erlangs

500 Erlangs

550 Erlangs

600 Erlangs

650 Erlangs

700 Erlangs

0.00% 0.00% 0.00% 0.00%

0.00% 0.04% 0.01% 0.00%

0.20% 0.51% 0.42% 0.25%

0.50% 0.98% 0.77% 0.62%

0.80% 1.45% 1.12% 1.00%

1.10% 1.99% 1.81% 1.38%

2.00% 2.54% 2.50% 2.05%

2.65% 3.82% 3.69% 2.93%

3.04% 5.10% 4.88% 5.81%

TABLE IV: Comparison of BBP levels in different protection approaches in Euro28 network with all types of flows. SPF SPF SPF SPF

-

NP DPP SBPP SB

AMRA AMRA AMRA AMRA

-

NP DPP SBPP SB

500 Erlangs

550 Erlangs

600 Erlangs

650 Erlangs

700 Erlangs

750 Erlangs

800 Erlangs

850 Erlangs

900 Erlangs

0.87% 0.50% 0.40% 0.04%

1.15% 1.12% 1.01% 0.10%

1.43% 1.46% 1.27% 0.38%

1.71% 1.95% 1.70% 0.97%

1.99% 2.45% 2.15% 1.28%

2.53% 2.94% 3.18% 2.27%

3.07% 3.44% 3.75% 3.10%

3.61% 3.60% 4.28% 4.58%

4.15% 5.74% 7.12% 7.48%

0.00% 0.04% 0.04% 0.03%

0.00% 0.10% 0.08% 0.08%

0.00% 0.38% 0.33% 0.32%

0.00% 0.70% 0.78% 0.69%

0.00% 0.89% 1.10% 0.89%

0.00% 1.71% 1.42% 0.99%

0.12% 1.99% 1.73% 2.44%

0.24% 3.27% 3.24% 3.75%

1.36% 5.70% 4.75% 5.27%

TABLE V: Comparison of BBP under different protection approaches with different number of receivers in a multicast session. Low Traffic - 300 ER

Moderate Traffic - 500 ER

Number of Receivers in Multicast Session

5

10

15

20

Number of Receivers in Multicast Session

5

10

15

20

AMRA-DPP-Euro28 AMRA-SBPP-Euro28 AMRA-SB-Euro28

0.00% 0.00% 0.00%

0.00% 0.00% 0.00%

0.00% 0.00% 0.00%

0.01% 0.00% 0.00%

AMRA-DPP-Euro28 AMRA-SBPP-Euro28 AMRA-SB-Euro28

0.19% 0.11% 0.04%

1.25% 1.11% 0.90%

2.89% 2.19% 1.41%

8.12% 6.32% 4.92%

AMRA-DPP-US26 AMRA-SBPP-US26 AMRA-SB-US26

0.00% 0.00% 0.00%

0.00% 0.00% 0.00%

0.11% 0.09% 0.07%

0.62% 0.38% 0.31%

AMRA-DPP-US26 AMRA-SBPP-US26 AMRA-SB-US26

1.02% 0.69% 0.47%

1.45% 1.12% 1.00%

3.91% 3.19% 2.41%

11.21% 7.12% 6.18%