Carrier-Grade Performance Evaluation in Reliable Metro Networks Based on Optical Packet Switching

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1 Carrier-Grade Performance Evaluation in Reliable Metro Networks Based on Optical Packet Switching Ahmed Triki, Ion Popescu, Annie Gravey, Philippe Gravey and Takehiro Tsuritani Institut Mines Télécom, Télécom Bretagne, Brest, France, ( KDDI R&D Laboratories, Inc., Saitama, Japan, ( io-popescu, UMR CNRS 674 IRISA, France, UMR CNRS 6285 Lab-STICC, France Abstract In this paper we assess the performance delivered in a metro network by two optical packet switching architectures, enabling sub-wavelength switching granularity. We compare POADM (Packet Optical Add/Drop Multiplexer) with TWIN (Time-domain Wavelength Interleaved Network). These technologies are envisaged to be deployed in the metropolitan area in order to improve bandwidth utilization and minimize energy consumption, thanks to their excellent switching granularity. In order to perform a realistic performance assessment, the study was carried out over a large set of traffic demands, for which the candidate architectures were first dimensioned taking into account network reliability. Then, the delivered data plane performance was assessed by simulation in terms of electronic packet loss, jitter and insertion delay. Two routing scenarios (anyto-any and hub-and-spoke) are mapped on a physical topology inspired from a European operator network. Simulation results show that both architectures easily achieve performance targets set by the Metro Ethernet Forum, as long as the network is properly dimensioned. I. INTRODUCTION Telecommunication networks consist of three main segments: access, metro-backhaul and backbone. Metro-backhaul networks typically aggregate traffic flows from or towards access networks. The granularity of these flows is highly variable as some stem from data centers or server farms, while others carry backhaul mobile traffic from small cells or residential areas. According to a study done by Cisco [], the busy hour (peak) IP traffic will nearly quadruple between 24 and 29. In this context, metro-backhaul networks will need more bandwidth and flexible resource management to cope with the dynamic variation of the traffic. These trends will have an impact on how service providers have designed their metro-backhaul networks. Hence, they have to look for innovative and cost-effective solutions that enable agile, scalable and efficient transport of data. Sub-wavelength switching solutions based on optical packet switching are proposed in order to offer more flexibility than the currently deployed optical circuit switching transport networks. Classical solutions, such as C-OBS [2] and L- OBS [3], that consider sub-wavelength switching as an optical IP-like protocol, achieve low wavelength utilization when a low optical packet loss ratio is mandated. On the other hand, advanced sub-wavelength switching solutions can rely on smart control plane mechanisms to achieve fast and all-optical switching performance that aims to meet carrier-like levels of QoS, such as those set by the Metro Ethernet Forum [4]. Packet Optical Add/Drop Multiplexer (POADM) [5] and Time-domain Wavelength Interleaved Networking (TWIN) [6] are two such all-optical sub-wavelength switching architectures. Both solutions are based on synchronous time-slotted access to the medium. Each fixed-duration time slot is occupied by at most one optical packet. Optical packets are assembled at the source nodes and transit transparently (without Optical to Electrical conversion) through the intermediate nodes. One of the main challenges is to ensure an efficient utilization of available slots. POADM networks rely on a ring topology. Access to the slots on multiple wavelengths is opportunistic, thanks to a control channel on a separate wavelength, which carries occupancy information corresponding to each slot. On the other hand, TWIN is built on a mesh topology, and can be represented as the superposition of multipoint-to-point trees, each tree aggregating the traffic sent to a given destination. One wavelength is exclusively attributed to such a tree. In contrast to POADM, TWIN operation relies on a slot reservation scheme [7]. Studies related to POADM and TWIN [8], [9] show that the throughput can reach up to 9% in a properly dimensioned network. The present paper focuses on assessing the performance delivered in a metro network by both POADM and TWIN architectures, considering different traffic profiles and reliable network scenarios. Section II presents POADM and TWIN technologies and highlights their important features. Section III describes the network scenarios and discusses the obtained results and to what extent they satisfy QoS requirements. Section IV concludes the paper. II. POADM AND TWIN DESCRIPTION A. WDM rings operated with POADM As illustrated in Fig. [], a POADM node consists in one amplifier at the input and another at the output in order to manage the power budget and enable the cascade of several nodes. Incoming optical packets, after pre-amplification, are wavelength demultiplexed. Then, each optical packet passes through an optical coupler that splits it into two replicas. The first one is dropped towards a fixed-wavelength receiver (RX) that discards optical packets in transit and only processes the optical packets that should be received. The second replica crosses an optical gate which can be either in ON state to let transit traffic pass, or in OFF state to block optical packets that should not go beyond the node. The optical gate could consist of Semiconductor Optical Amplifier (SOA). New optical packets can be inserted on any available wavelength using a fast

2 Fig. : POADM node structure (according to [2]) tunable transmitter (TX). Transit and add optical packets are then optically multiplexed and amplified. The control packet carried over the control channel is updated to report the occupancy status of each WDM slot. Several medium access control (MAC) protocols have been proposed in the literature for POADM []. In the present study, we adopt the solution presented in [9] that uses a totally opportunistic and distributed protocol to control resources. The opportunistic MAC allows each node to send a single optical packet whenever a slot is available. We consider a bi-directional POADM network, and each node selects the direction on which to send optical packets based on the shortest path in terms of distance. In the case of failure, the traffic is rerouted in the opposite direction [3]. To avoid the disruption of traffic, backup capacity should be provisioned in each direction during network dimensioning. A source POADM node builds optical packets called hereafter Protocol Data Units (PDUs) by assembling electronic packets from various client layers (e.g., Ethernet, IP) which are called hereafter Service Data Units (SDUs) and have to be forwarded to a given destination POADM node. The SDUs to be sent are electronically stored in virtual queues per destination. The PDU assembly mechanism is a well-studied topic in the literature as it has a significant impact on the performance of the network [4]. In this study, the PDU assembly process (Fig. 2) performs as follows: the source node checks whether at least one slot is available. If it is the case, the oldest SDU from the front of the queues is identified; if it is older than a given trigger time, a PDU is built with the available SDUs (it may be only partially filled), and is sent on the selected slot. If none of the waiting SDUs are older than the trigger time, the source node then checks all queues to see whether a full PDU can be built. If this is the case, a PDU is built and is sent on the selected slot, otherwise, no PDU is sent. Fig. 2: PDU assembly flow diagram Fig. 3: TWIN node structure B. Mesh WDM networks operated with TWIN In TWIN, a particular wavelength is attributed to the traffic sent to a specific node. When a source has an optical packet (i.e., PDU) to send to a given node, it tunes the laser to the wavelength attributed to that node for the duration of the PDU. Between the source and the destination node, PDU is transparently wavelength-routed (e.g., using WSS: Wavelength Selective Switches) by the intermediate nodes. WSS are used to reconfigure the multipoint-to-point trees, at network setup, when a failure occurs, or when a new branch is created. Fig. 3 illustrates the TWIN node structure with a fixed wavelength RX and a tunable TX. The fact that all sources share the same medium to reach a specific destination leads to possible collisions at each merging point of the tree. To resolve this problem, TWIN relies on a scheduler to coordinate sources transmission. The purpose of the scheduling is to assign the appropriate slot(s) to sourcedestination pairs in such a way that no collision occurs at the intermediate nodes. A schedule consists of a predefined number of slots. For each source node, the schedule sets the repetitive pattern that can be used to transmit PDUs to any destination node. The PDU assembly process in each source node is thus triggered by the schedule, even if the amount of SDUs to be sent does not fill the PDU. It is shown in [5] that a TWIN centralized control plane, where a single control entity manages resource allocation, is more adapted to a metropolitan area and achieves better performance than a distributed plane. Several mechanisms are proposed in the literature to compute schedules. In [6], the authors propose a-generic approach based algorithm to compute schedule patterns. This algorithm is a heuristic approach aiming to minimize the number of slots needed to complete the transmission of the entire traffic demand matrix. Another heuristic algorithm is developed in [7]. It simultaneously assesses the routing, scheduling and virtualization in order to overcome the computation complexity of the control plane. In [8], the authors propose an Integer Linear Programming (ILP) formulation enabling the computation of schedule patterns and the minimization of the number of used TXs/RXs. To ensure network reliability, the destination nodes are connected to the backup trees that use different paths and wavelengths from those used by the working trees. Accordingly, the burst emission schedules are recomputed taking into account the new propagation delays.

3 Fig. 4: Network topology C. High-level comparison between POADM and TWIN An appealing and common characteristic of both POADM and TWIN is that traffic is electronically processed only at the source and the destination nodes when inserting or extracting the PDUs. Traffic grooming is transparently performed at intermediate nodes, while PDU collision is avoided thanks to control plane features. However, POADM and TWIN have different ways to manage the optical resources: in TWIN, each wavelength is exclusively attributed to traffics sent to a given node, while in POADM, wavelengths are used as data channels accessible by all the nodes. The overlaid trees that make up the TWIN network provide flexibility with regard to the physical topology. However, this is achieved at the expense of complex schedule computation. Moreover, the assignment of a specific (set of) wavelength(s) to each edge node may lead to scalability issues and to fiber link underutilization. In POADM, the simple ring structure leads to a simpler opportunistic MAC protocol. However, the coverage of large physical network topologies by a ring may lead to longer paths and may require relying on several POADM rings interconnected by electronic hubs. POADM bidirectional ring enables a simple and fast recovery in the case of failure by rerouting the traffic in the opposite direction [3]. For TWIN, network reliability is more complex to ensure since the failure of a single link can impact one or several trees, thus, the schedules must be recomputed [9]. III. DIMENSIONING AND PERFORMANCE COMPARISON A. Framework of the study We dimension the network taking into account scenarios where the architectures are protected against link and TX/RX failures. In order to assess the required resources in terms of wavelengths (WLs), TXs and RXs for both architectures, we rely on heuristical methods. For TWIN, the sent/received traffic by one TX/RX, in the working and backup modes, should not exceed 8% [8] of the total capacity of each element and for POADM, the WL utilization should not exceed 8% []. The number of TXs (T ) and RXs (R) used in the working mode of TWIN, are computed based on the Eqs. and 2, respectively. The number of WLs is equal to the number of RXs. f i,j is the traffic load from i to j that in some cases could be equal to zero, and function maps a real number to the smallest following integer. To ensure protection, we double the number of TXs and RXs in each node. One WSS is needed at each node s input port to conduct wavelength to the right output port. Furthermore, one WSS is required at the input/output of the emission/reception side to enable the node to send/receive traffic to/from several trees (including the backup trees). N N N j=;j i T = Tx i = f i,j ().8 C j= N N N ;i j R = Rx j = f i,j (2).8 C j= The number of TXs (T ) and WLs (W ) needed for the working mode of POADM are computed based on the Eqs. 3 and 4, respectively. fi,j d is the traffic load from i to j using the direction d and fi d is the traffic load exiting the node i that includes the added and the bypassed traffic. The number of RXs in the working mode depends on the number of WLs to which the node have access. For the protection issue, the number of TXs, RXs and WLs are doubled. At each node, an SOA is needed by wavelength and two SOAs are needed by each TX/RX to enable the access to the backup and the working links. T = = N ( N ( W = 2 max ( TX i +TXi 2 ) N j=;j i f i,j max i N.8C + N j=;j i f2 i,j.8c ) (3) ( ) ( )) f i.8c, max f2 i i N.8C In the performance study, backup resources are not used because they may skew performance results. The considered performance targets are those applied to metropolitan QoS requirements according to MEF [4]: SDU delay must be less than ms, SDU jitter must be less than 3 ms and SDU loss must be less than.% (i.e., 4 ). In all simulations, an SDU is considered lost only if it remains in the source edge node for a duration larger than or equal to 8 ms. Indeed neither TWIN nor POADM drop PDUs once they are sent towards a destination node. SDU latency is composed of propagation time, insertion time and in principle extraction time. Propagation time is directly derived from distances between source and destination nodes, which are shown in the next section to be less than 2 km (i.e., propagation time corresponds to less than ms). Therefore, the simulation focus on computing the insertion time, as extraction time is zero for TWIN and has been shown to be negligible for POADM in previous studies [2]. Lastly, jitter is computed as the difference between the st percentile and the99 th percentile of the SDU latency distribution. (4)

4 PDU length ratio [%] Traffic emitted by the node [Gb/s] (a) mean PDU length ratio SDU insertion time [ms] Traffic emitted by the node [Gb/s] (b) mean SDU insertion time Fig. 5: Any-to-any scenario SDU jitter [ms] 3 2 QoS Threshold Traffic emitted by the node [Gb/s] (c) mean SDU jitter B. Simulation scenarios To compare the performance between TWIN and POADM, we implemented them on the same OMNET++ simulator using the same network topology, the same traffic matrices and similar methods to design the simulator internal modules. For both TWIN and POADM, the slot duration is equal to µs, including 2 ns of guard time between two successive PDUs. Accordingly, the maximum size of the assembled SDUs is equal to 225 bytes, corresponding to 9.8 µs on a Gb/s channel. The generation of traffic is performed on the basis of SDU granularity, where the inter-arrival times between successive SDUs follow the exponential distribution and the mean SDU size is equal to 8 bytes. 5% of SDUs are set equal to 4 bytes and the remaining 5% are set equal to 2 bytes [2]. For the PDU assembly in POADM (see Section II-A and Fig. 2), the timer value and the upper threshold of the PDU size used to trigger the assembly process are equal respectively to 5 µs and 25 bytes (9% of the maximum PDU size). The network topology is inspired from a European core network containing 7 nodes and 25 links. The POADM logical topology consists in one ring that crosses all the nodes as depicted in Fig. 4. The minimum, average and maximum distance between POADM node pairs is 5 km, 98 km and 97 km, respectively. The TWIN network consists in overlaid trees built based on the shortest path. The minimum, average and maximum distance between TWIN node pairs is 5 km, 69 km and 58 km, respectively. The schedule pattern of TWIN is composed of slots and is computed using the ILP formulation presented in [8]. We consider two scenarios: any-to-any and hub-andspoke. In the any-to-any scenario, each node sends/receives traffic to/from all the other nodes. Traffic flows are symmetric and uniformly distributed. Several load factors between and Gb/s are considered. In the hub-and-spoke scenario, the traffic is concentrated at a specific node, referred in the following as hub, that sends/receives traffic to/from all the other edge nodes. All connections between edge nodes have to pass through the hub. This scenario is inspired from the current metropolitan network where the concentration node is responsible for ensuring connection between the metropolitan area nodes and the core network. For this scenario, we assume that the upstream traffic load (from the edge nodes to the hub) is equal to the third of TABLE I: Amount of resources in the any-to-any scenario POADM TWIN Conf # #2 #3 #4 Conf # #2 TEN [Gb/s] TEN TX TX RX RX WL WL SOA WSS the downstream traffic load. Several load factors are tested for this scenario, allowing the variation of the total traffic load from to 3 Gb/s in the downstream direction and from to Gb/s in the upstream direction. C. Results and discussion ) Any-to-any scenario: Tab. I shows the requested amount of resources in terms of number of TXs/RXs/WLs, as well as the number of SOAs and WSSs for POADM and TWIN networks respectively. We checked that the heuristic dimensioning methods ensure either zero or a negligible SDU loss factor: SDU loss ratio is zero for TWIN and roughly 5 for POADM. In this scenario, four different configurations (Conf) are needed by POADM according to the traffic load emitted by the node (referred in the table as TEN) ranging from to Gb/s. The number of TXs is stable, however, the number of WLs increases once the load becomes more important. The number of RXs and SOAs follows the evolution of the number of WLs resulting from the POADM node architecture. Unlike POADM, only two configurations are needed for TWIN. The number of TXs/RXs/WLs used for traffic below than 8 Gb/s is doubled when the traffic is between 8 and Gb/s, while the number of WSSs remains constant. TWIN and POADM require almost the same number of TXs. At high traffic load, TWIN needs only 25% of the number of POADM RXs, while POADM saves almost 75% of WLs compared to TWIN. This is due to the fact that POADM enables the sharing of WLs among all the flows, contrary to TWIN that shares the WL only among flows destined to the same node. These different behaviors impact the mean PDU filling ratio as illustrated in Fig. 5a. In fact, in the case of TWIN, the PDU length linearly increases with traffic load until the Conf#2 is used. As the only condition to trigger the assembly of PDU in TWIN is the availability of slot, some slots are not fully filled. The PDU filling ratio is larger in the case of POADM, and at high loads, the PDU is filled up to 95%. Accordingly,

5 PDU length ratio [%] 5 TWIN: Conf3 TWIN: Conf4 2 3 Traffic emitted by the hub [Gb/s] (a) mean PDU length ratio SDU insertion time [ms].5 TWIN: Conf3 TWIN: Conf4 2 3 Traffic emitted by the hub [Gb/s] (b) mean SDU insertion time Fig. 6: Hub-and-spoke scenario SDU jitter [ms] 3 2 TWIN: Conf3 TWIN: Conf4 QoS Threshold 2 3 Traffic emitted by the hub [Gb/s] (c) mean SDU jitter TABLE II: Amount of resources in the hub-and-spoke scenario POADM TWIN Conf # #2 #3 #4 Conf # #2 #3 #4 TEH [Gb/s] TEH[Gb/s] TX TX RX RX WL WL SOA WSS at high loads, the PDU assembly process of POADM depends more on the upper size threshold (9% of the maximum size of PDU) than on the timer threshold. Furthermore, the timer value is chosen large enough to allow a high filling ratio. The opportunistic POADM MAC insertion process and the accessibility of WLs by all the flows enable better filling ratio and limit the number of necessary WLs compared to TWIN. Fig. 5b shows the insertion time in POADM and TWIN, which represents the period of time between the arrival of the SDU and its sending in a PDU. The insertion time in both technologies is less than.5 ms. In addition to the insertion time, we assess the propagation time in order to compare the total end-to-end delay. In this scenario, the propagation time between the farthest source-destination pair in POADM network is equal to 985 µs and the mean propagation time for all the flows is almost equal to 495 µs. However, in the case of TWIN, the propagation time between the farthest sourcedestination pair is equal to 79 µs and the mean propagation time for all the pairs is almost equal to 345 µs. Hence, the difference in average paths length between POADM and TWIN is 5 µs, which is not significant giving that the delay QoS threshold considered in this study is equal to ms [4]. Fig. 5c illustrates that the mean SDU jitter in POADM and TWIN are similar and are close to.5 ms. This value is significantly less than the QoS threshold set to 3 ms. The sending pattern of PDUs in TWIN is shaped by the schedule pattern that guarantees periodic opportunities. In POADM, the low jitter is led by the timer and PDU size upper threshold. 2) Hub-and-spoke scenario: In the hub-and-spoke scenario, we checked that the heuristic methods used for dimensioning provide SDU transport with zero loss ratio for POADM/TWIN networks. Tab. II shows that the number of TXs needed by TWIN and POADM is almost equal. The number of WLs in POADM scales faster in accordance to the traffic load. However, it is lower (one third) than the number of WLs needed by TWIN that remains almost stable with respect to the traffic emitted by the hub (TEH). The number of RXs in POADM is significant and is 66% higher than those of TWIN. In fact, each POADM node must be able to receive data from any wavelength belonging to a given direction. Thus, the node must be equipped with as many RXs as the number of WLs in this direction. The increasing number of RXs in POADM leads to a substantial number of SOAs. Similarly to the evolution of TX, RX and WL, the number of WSSs in TWIN is stable with respect to the traffic load. We will focus in the following on the performance of a flow in the downstream direction (from the hub to one edge node). Fig. 6a shows that in each dimensioning configuration of TWIN, the filling ratio linearly increases with respect to the traffic load until it reaches 9%. In fact, when the number of TXs is upgraded, the number of attributed slots per couple increases significantly yielding to the drop of the filling ratio that approaches the value of 6%. In the case of POADM, the filling ratio sharply increases when the load is less than 4 Gb/s, for higher loads it reaches a steady value of 98%. This value is mainly imposed by the upper PDU size threshold. Fig. 6b shows that the mean insertion time in POADM is smaller than the one in TWIN for all traffic loads. Although the POADM hub shares WLs with other nodes, it dominates the medium because it has more load which gives him more opportunities to send traffic. However, the TWIN hub has to wait the granted slot before sending which delays the sending time for few hundred of micro-seconds compared to POADM. In both cases the insertion time is still lower than.5 ms. Taking into consideration all flows, calculations show that the propagation time between the farthest source-destination pair in the case of POADM is equal to 955 µs and the mean propagation time for all the pairs is equal to µs. The propagation time between the farthest source-destination pair in the case of TWIN is equal to 585 µs and the mean propagation time for all the pairs is equal to µs. In this scenario, the difference in average paths length between POADM and TWIN is 272.5µs. Consequently, the two technologies achieve almost the same end-to-end delay performance. Moreover, obtained values are substantially lower than the QoS threshold ( ms according to [4]).

6 Fig. 6c illustrates the mean PDU jitter. POADM accomplishes better jitter performance than TWIN that has a jitter around ms. For both technologies, jitter values are lower compared to the jitter QoS requirement threshold and they decrease as more resources are available. In fact, despite of the increase in the traffic load, the availability of more resources gives to the hub more flexibility to manage its resource and serve SDU in shorter time. IV. CONCLUSION In this paper, we have assessed the performance delivered in a metro network by two optical packet switching architectures, enabling sub-wavelength switching granularity. We compared POADM with TWIN. These two technologies are designed to be deployed over WDM network. However, the way they use the WDM spectrum is different. The conception of TWIN, based on overlaid trees, makes it more adapted to physically meshed networks while the ring structure of POADM network facilitates wavelength reuse. The applicability of TWIN to any type of network is achieved at the expense of the complexity of its control plane, based on the computation of a global packet emission schedule for all nodes. The control plane in POADM is less complex since it relies on an opportunistic insertion process. In order to perform a realistic performance assessment, the study is carried out over a large set of traffic demands, for which the candidate architectures are first dimensioned using heuristics that takes into consideration the reliability of the network. TWIN and POADM require almost the same number of TXs, while TWIN needs more wavelengths and POADM needs more RXs. We compare TWIN and POADM by considering two routing scenarios (any-to-any and hub-and-spoke) that are mapped on a physical topology inspired from a European operator network, by using the same simulation tool. For each traffic demand, data plane performance is assessed. Simulation results show that TWIN and POADM achieve high performance in terms of SDU end-to-end delay, SDU jitter and SDU loss ratio. The latency penalty generated by POADM logical ring topology does not affect the QoS. Both architectures easily achieve performance targets set by the Metro Ethernet Forum, as long as the network is properly dimensioned. However, it seems quite clear that the optical components used to design POADM node scale faster according to the traffic load than those used for TWIN node. ACKNOWLEDGMENT This work was partly supported by the French government in the framework of the N-GREEN project (ANR-5-CE25-9-2). The authors gratefully acknowledge the help given by Dr. Yvan Pointurier from Nokia Bell Labs and Dr. Esther Le Rouzic from Orange Labs. REFERENCES [] Cisco Systems, Cisco visual and index: Forecast and methodology, 24-29, White Paper, 25. [2] C. Qiao and M. 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