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Research Issues on Routing and Wavelength Assignment for Wavelength Routed WDM Networks Qualifying Exam Hsu-Chen, Cheng PhD. Student Department of Information Management National Taiwan University 10/27/2003 Outline Introduction of Optical Networks Optical Network Design and Engineering WDM Technology Optical Network Control Plane IP/WDM Traffic Engineering Routing and Wavelength Assignment (RWA) Heuristics Optical Multicasting Multi-granularity Architecture of Optical Network Future Research Direction 2 The Trend of Network Technology Packet Switch Circuit Switch IP E ATM M SONET DWDM S IP /MPLSE SONET M S DWDM IP GMPLSE M Thin SONET IP GMPLS DWDM OXC DWDM OXC S E M S Time Introduction of Optical Networks 3 Optical Networks First Generation: FDDI Gigabit Ethernet Second Generation: WDM Local Area Network WDM Wide Area Network Passive Star Network Single-Hop WDM Network Wavelength routed Network OBS OPS Wavelength-routed optical networks are the most promising candidates for backbone high-speed WAN. Introduction of Optical Networks 4 Optical Network Technologies WDM Technology Fixed Point-to-Point Wavelength routed 300 λ x 40Gbps Optical Components OADM (Optical add/drop multiplexer) OXC (Optical cross-connect) Tunable Laser Amplifier Wavelength Converter Wavelength Splitter Introduction of Optical Networks 5 The Architecture of Wavelength Router Introduction of Optical Networks 6 Physical Topology and Logical Topology A physical topology is a graph representing the physical interconnection of the wavelength routing nodes by means of fiber-optic cables. A logical topology is a directed graph that results when the lightpaths are setup by suitably configuring the wavelength routing nodes. Optical Network Design and Engineering 7 The Architecture of Wavelength-routed Optical Network Introduction of Optical Networks 8 Optical Network Control Plane Apparatus IETF (Internet Engineering Task Force) ODSI (Optical Domain Service Interconnection) OIF (Optical Internetworking Forum) Issues Signaling Mechanism (UNI) Signaling and control protocol for dynamic lightpath establishment and traffic engineering Introduction of Optical Networks 9 Optical Network Control Plane (cont’d) Traffic Engineering Database •RSVP-TE Signaling Protocol Topology and Resource Discovery Topology and resource information •CR-LDP Lightpath Management Updates Route information Route Computation •Neighbor discovery •Link Monitoring •State distribution •LMP [J. P. Lang 2001] RWA algorithms/ traffic engineering Link-state routing protocol (OSPF) Introduction of Optical Networks 10 IP/WDM Traffic Engineering Overlay Model Peer Model Closer to classical IP and ARP over ATM scheme The IP and optical network are independent of each other Edge IP router interacts with its ingress OXC over a welldefined UNI The IP and optical network are treated together as a single network Augmented Model IP and optical networks use separate routing protocol, but information from one routing protocol is passed through the other routing protocol G. N. Rouskas and H. G. Perros, A Tutorial on Optical Networks, Networking 2002 Tutorials, vol. 2497, 2002, pp. 155-193. Introduction of Optical Networks 11 TE Model WDM Traffic Engineering Model MPLS Traffic Engineering Model Minimum average packet delay Maximize scale up capability Overlay model Virtual topology (LSPs) IP over WDM Traffic Engineering Model Virtual topology design Routing and wavelength assignment Introduction of Optical Networks 12 RWA constraints Wavelength continuity constraint Distinct wavelength constraint Optical Network Design and Engineering 13 Wavelength Conversion Wavelength converters translate wavelength fi to fk. They may be used as components of the wavelength routing nodes. λ1 λ1 λ1 λ1 λ2 λ2 λ2 λ2 λ3 λ3 λ3 λ3 (a) No conversion (b) Fixed conversion λ1 λ1 λ1 λ1 λ2 λ2 λ2 λ2 λ3 λ3 λ3 λ3 (c) Limited conversion (d) Full conversion Optical Network Design and Engineering 14 RWA Problem Static RWA Topology Subproblem Lightpath routing subproblem Wavelength assignment subproblem Traffic routing subproblem Dynamic RWA Route Computation Wavelength Assignment Optical Network Design and Engineering 15 Physical Topology Design This step includes – Sizing the links (no. of wavelength channel, capability of each channel) Sizing the OXCs Placement of resources (Amplifiers, Converters, Splitters) Dealing with link or OXC failures Placement of converters [J. Iness, 1999] Static RWA Sparse location of wavelength converters Sharing of converters (Nodal Design) Limited-range wavelength conversion [R. Ramaswami and G. H. Sasaki, 1998] 16 Virtual Topology Design A solution to the static RWA problem consists of a set of long-lived ligthpaths which create a logical topology among the edges node. It is not possible to implement fully connected virtual topologies. N(N-1) lightpaths Objective Static RWA Minimize the maximum congestion level Minimize the average weighted number of hops Minimize the average packet delay 17 Wavelength Assignment 4 λ1 λ0 1 2 1 2 3 5 8 3 λ1 λ2 7 4 λ2 λ0 7 8 6 Graph-coloring problem NP-complete 6 5 λ1 λ0 Sequential graph-coloring algorithms Static RWA 18 Route Computation Static algorithm and adaptive algorithm Lightpath routing Constraint algorithm Adaptive unconstrained routing (AUR) Hybrid routing Fixed routing algorithm Fixed alternative algorithm Least to most congested AUR has better improvement on call blocking probability[A. Mokhtar and Murat Azizoğlu, 1998] Dynamic RWA 19 Candidate Paths The candidate paths for a request are considered in increasing order of path length (or path cost). Path length is defined as the sum of the weights assigned to each physical link along the path. K-shortest path K-minimum hop paths K-minimum distance paths Pair-wise link disjoint Dijkstra algorithm Physical constraints (attenuation, dispersion et al.) Constraint-based shortest path first algorithm [B. Davie, 2000] Dynamic RWA 20 Wavelength Assignment [H. Zanf et al., 2000] Random Wavelength Assignment (R) First-Fit (FF) Single-fiber Least-Used (LU) Most-Used (MU) Min-Product (MP) Least-Loaded (LL) Multi-fiber MAX-SUM (MΣ) Relative Capacity Loss (RCL) Wavelength Reservation (Rsv) Protecting Threshold (Thr) Dynamic RWA 21 General Model of Virtual Topology Design Mixed Integer Linear Programming [B. Mukherjee et al., 1994] [B. Mukherjee et al., 1996] [R.Ramaswami and K. N. Sivarajan, 1996] [R. Krishnaswamy and K. N. Sivarajan, 1998] [R. Krishnaswamy and K. N. Sivarajan, 2001] Objective min( max ) General Model 22 Congestion Congestion may be viewed as a function of the various parameters of the network such as the traffic matrix, number of wavelengths the fiber can support, resources at each node (number of transmitters and receivers), the hop lengths of the logical links, the multiplicity restrictions on the logical topology, the multiplicity restrictions on the physical topology, symmetry/asymmetry restrictions, the propagation delay. General Model 23 Objective min( max ) The motivation for choosing this objective is that the electronic processing (switching speed) requirement is proportional to the congestion. If the switching speeds at the nodes are limited, then minimizing congestion would be appropriate as it would enable the traffic carried per wavelength to increase. If there is heavy traffic between some source–destination pair, then there is a logical link between them; this is a desirable property. This happens because of the objective function, i.e., if there is heavy traffic between node i and node j then because of the objective there would tend to be an edge in the logical topology. General Model 24 Notations s,d source and destination of a packet, when used as superscripts; i,j originating and terminating node of a logical link (lightpath); l,m endpoints of a physical link; k wavelength number, when used as a superscript. General Model 25 Parameters Physical Topology: GP (V , EP ) Link Indicator: Plm Virtual Degree: n Traffic Matrix: [(sd ) ] Allowed Physical Hop: General Model H [hij ] 26 Variables Lightpath Indicator: bij (k ) c Lightpath wavelength Indicator: ij Link-lightpath Wavelength Indicator: cij( k ) (l , m) ) Traffic intensity variables: (sd ij General Model 27 Constraints- Degree Constraints b ij l , i l , i j b ji j bij 0,1 and i 0,1,2,...N 1. The above constraint ensures that the number of logical links originating (out-degree) and terminating (in-degree) at node is less than or equal to the number of transmitters and receivers at that node. General Model 28 Constraints- Traffic Constraints Traffic routing constraints ij max , (i, j ) ij (ijsd ) , (i, j ) sd (ijsd ) bij( sd ) , (i, j ), (s, d ) Flow Conservation ( sd ) ij j (jisd ) j ( sd ) if s i ( sd ) , if d i, 0, if s i and d i ( s, d ) The above first two equations ensure that the load on any logical link is no greater than the maximum load, which is being minimized. General Model 29 Constraints- Wavelength Continuity Constraints Unique wavelength constraints: W 1 (k ) c ij bij , (i,j) k 0 This ensures that if logical link exists, then only one wavelength is assigned to it, among the possible choices. cij( k ) (l, m) cij( k ) , (i, j ), (l , m), k This equation ensures that only those Cl(.km) (l , m) could be (k ) nonzero for which the corresponding C (i, j ) variables are nonzero. General Model 30 Constraints- Wavelength Continuity Constraints Wavelength clash constraints (k ) c ij (l , m) 1, (l , m), k ij Conservation of wavelength constraints bij , if m j (k ) (k ) C ( l , m ) P C ( m , l ) P b , if m i , ij (i, j), m ij lm ij m ,l k 0 l k 0 l 0, if m i and m j. W 1 F 1 Let logical link bij use wavelength k. Then by conservation of wavelength constraints there is a path in the physical topology from node i to node j with wavelength assigned to it. General Model 31 Constraints- Hop Bound Constraints Hop bound Constraints (k ) C ij (l, m) hij , (i,j ),k lm General Model 32 Heuristics Subproblems: Topology Subproblem: bij (k ) Lightpath routing subproblem: cij (l , m) (k ) c Wavelength assignment subproblem: ij (sd ) Traffic routing subproblem: ij Some of above subproblem are NP-hard. Solving the subproblems in sequence and combining the solutions may not result in the optimal solution for the full integrated problem. RWA Heuristics 33 Lower Bound on Congestion Physical topology independent bound (p.43) max (1 / El ) ij rH / El ij Minimum flow tree bound (MFT) (p.43) max rH min / El Iterative LP-relaxation bound (p.43) Aggregate formulation Cutting Plane Independent topologies bound (p.43) Uniform traffic: 5% - 10% tighter than the bound obtained from MFT Nonuniform traffic: up to 50% higher than MFT bound RWA Heuristics 34 Lower Bound on the Number of Wavelength Physical topology degree bound (p.45) Derived from the Simple consideration that he node with the minimum physical degree. l p Physical topology link bound (p.46) Assuming that each node sources lightpaths to exactly those node it can be reach with the minimum number of hops. (1/ 2 E p ) li ( l ) i Lagrangian relaxation bound 顏宏旭 (2001) RWA Heuristics 35 Regular Topologies Regular topologies such as hypercube have several advantages as virtual topologies. They are well understood, and results regarding bounds and averages are comparatively easier to derive. Two subproblem Node Mapping Subproblem Path Mapping Subproblem RWA Heuristics 36 Pre-specified Topologies The topology in terms of a list of lightpaths with their source and destination nodes is supposed to be given for each instance of problem. The lightpath routing and wavelength assignment subproblems can be viewd as having goals defined purely in terms of lightpaths. Static Lightpath Establishment problem [I. Chlamtac, 1995] Maximize wavelength utilization [C. Chen, 1995] Randomized rounding and graph coloring [D. Banerjee 1996] RWA Heuristics 37 Arbitrary Topologies [R. Ramaswami, 1996] HLDA (Heuristic topology design algorithm) MLDA (Minimum-delay logical topology design algorithm) TILDA (Traffic Independent logical topology design algorithm) LPLDA (LP-relaxation logical topology design algorithm) RLDA (Random logical topology design algorithm) [D. Banerjee, 2000] Maximizing Single-Hop Traffic Maximizing Multihop Traffic RWA Heuristics 38 Optical Multicasting Multicasting at IP layer Optical Multicasting 39 Optical Multicasting Multicasting by Lightpaths Optical Multicasting 40 Optical Multicasting Multicasting at WDM Layer (Light Tree Architecture) Optical Multicasting 41 Light Tree Architecture Application Optical multicast Enhanced virtual connectivity Traffic grooming Steiner Tree Problem Shortest path-based heuristic (SPH) Spanning tree-based heuristic (STH) Metaheuristics Optical Multicasting 42 WDM Multicast Mode [Y. Yang et al., 2000] Multicast with same wavelength (MSW) Multicast with same destination wavelength model (MSDW) Multicast with any wavelength model (MAW) Optical Multicasting 43 MC-RWA MC-RWA bears many similarities to the RWA problem. The tight coupling routing and wavelength assignment remains and becomes stronger. Physical topology design problem Resources placement [M. Ali and J. Deogun, 2000] Virtual topology design problem Minimize call blocking probability Minimize the number of transceiver needed Minimize average packet hop distance Optical Multicasting 44 MC-RWA Researches (1/2) [L. H. Sahasrabuddhe, 1999] An optimum light tree-based virtual topology has a lower value of average packet hop distance than that of an optimum lightpath-based virtual topology An optimum light tree-based virtual topology requires fewer opto-electronic components Light forest [X. Zhang et al., 2000] Reroute-to-Source Reroute-to-Any Member-First Member-Only Optical Multicasting 45 MC-RWA Researches (2/2) [Y. Sun et al., 2001] Optical Multicasting The USCH1 algorithm gives the worst network throughput The wavelength continuity constraint limits the performance of the MSCH1 algorithm The best approach is the MSCH2 if the wavelength converters are not available 46 Super-Lightpath RWA WDM + OTDM Optical Multicasting 47 Tree Shared Multicast [D. N. Yang and W. Liao, 2003] A light tree can carry data of multiple multicast streams, and data of a multicast stream may traverse multiple light-trees to reach a receiver. Multicast routing and wavelength assignment of light-trees Design of light-tree based logical topology for multicast streams [郭至鈞,民國92] Multicasting group aggregation and MC-RWA Source-based tree aggregation Maximize the total revenue Lagrangian relaxation Optical Multicasting 48 Tree-Sharing Strategies Given the set Mi at edge router i, we consider a strategy to decompose Mi into a number of MSCs (Multicast Sharing Class) Perfect Overlap (PO), Super Overlap (SO), and Arbitrary Overlap (AO) Optical Multicasting 49 Optical Waveband Switch WBS has attracted attention for its practical importance in reducing port count, associates control complexity, and cost of photonic cross-connect. In WBS networks, several wavelengths are grouped together as a band and switch as single entity using single port. MG-OXC not only switch traffic at multiple granularities such as fiber, band, and wavelength, but also add and drop traffic at multiple granularities . Multi-granularity Optical Networks 50 Multilayer MG-OXC 1 1 Fiber Cross-connect (FXC) n BTF Mux Bdrop FXC layer FTB Demux Waveband Crossconnect (BXC) BTW Demux Fadd n WTB Mux Wavelength Crossconnect (WXC) Wdrop Wadd Badd BXC layer WXC layer Fdrop TX/RX block Multi-granularity Optical Networks 51 Single Layer MG-OXC 1 1 FXC 2 2 BXC n n WXC m Fadd Badd Wdrop Wadd Bdrop Fdrop TX/RX block Multi-granularity Optical Networks 52 Lightpath Grouping Strategy End-to-end grouping: One-end grouping: Grouping the traffic (lightpaths) with same source-destination only Grouping the traffic between the same source (or destination) nodes and different destination (or source) nodes Subpath grouping: Grouping traffic with common subpath (from any source to any destination) Multi-granularity Optical Networks 53 WRN vs. WBS WRN WBS Minimum the number of wavelengths Minimum wavelength hops Minimum the number of ports Waveband conversion λ0 λ0 λ1 λ1 λ2 λ2 λ3 λ3 b0 b1 Multi-granularity Optical Networks λ0 λ0 λ1 λ1 λ2 λ2 λ3 λ3 b0 b1 54 WBS Failure Recovery Band Merging λ0 λ1 λ2 λ3 λ4 λ5 b0 b1 Band Swapping λ0 λ1 λ2 λ3 λ4 λ5 b0 b1 Multi-granularity Optical Networks 55 Hierarchical Routing Model Network node architecture Sequence of routing and waveband aggregation Route Computation Integrated routing Separate routing H Online routing Offline routing Multi-granularity Optical Networks us o e e n rk g o wo om net s ou e e n rk g o o er etw t He n 56 Integrated routing Separate routing Researches of M. Lee et al. Online routing Offline routing s ou ne k e r og o m etw Ho n us eo n ge rk ro o t e e tw e n H Multi-Layer MG-OXC The waveband is formed by grouping lights with the same destination in a network ILP formulation Maximize the reduction gain of crossconnect size with the minimum number of wavelengths Results The introduction of waveband leads to a very large reduction in crossconnect requirements for large-scale networks. A large reduction of crossconnect requirements can still be expected even at nonoptimal wavelength granularity. The reduction depends on network topology, traffic demand and traffic pattern. Multi-granularity Optical Networks 57 Integrated routing Separate routing Researches of Y.Suemura et al. Online routing Propose and analyze two heuristic routing and aggregation algorithms (online and offline) to be used for homogeneous networks in separate routing framework. Minimum the routing cost Offline routing s ou ne k e r og o m etw Ho n us eo n ge rk ro o t e e tw e n H Assume that all the ports (OEO and optical ones) have the same cost. The cost of routing is the total number of used ports. The simulations demonstrate a significant cost reduction by employing hierarchical routing (from 33% in online algorithm to almost 60% in offline one) Multi-granularity Optical Networks 58 Integrated routing Separate routing Researches of X. Cao et al. Online routing This research show that WBS is different from traditional wavelength, and thus techniques developed for wavelengthrouted networks cannot be directly applied to effectively WBSrelated problem. The objective is to route lightpaths and assign appropriate wavelength to them so as the minimum the total number of prots required by the MG-OXCs. Static offline problem (Network Planning) Balanced Path Routing with Heavy Traffic (BPHT) Dynamic real-time problem (Network Servicing) Offline routing s ou ne k e r og o m etw Ho n us eo n ge rk ro o t e e tw e n H Maximum Overlap Ratio (MOR) Results BPHT: 50% fewer total ports than using ordinary OXCs MOR: 35 % saving in the number of ports Multi-granularity Optical Networks 59 Integrated routing Separate routing Researches of P. Ho et al. Online routing Dynamic tunnel allocation (DTA) Use fixed alternative routing with k-shortest paths to inspect networks along each alternative path for dynamically setting up lightpaths. Capacity-balanced static tunnel allocation (CB-STA) Offline routing s ou ne k e r og o m etw Ho n us eo n ge rk ro o t e e tw e n H Fiber and waveband tunnels are allocated into networks at the planning stage according to weighted network link-state. Simulation Results DTA is outperformed by CB-STA in the same network environment duo to a well-disciplined approach for allocating tunnels with CBSTA. The mix of the two approaches yields the best performance given the same network environment apparatus. Multi-granularity Optical Networks 60 Future Research Topics New optical component application Optical Multicasting WBS QoS Multicasting Tree Aggregation Problem Call Admission Control Converter and Splitter Placement Waveband Multicasting Heterogeneous WBS Network Survivability Optical Packet Switch and Optical Burst Switch Passive Optical Network- EPON and GPON After the Optical Bubble? 61 Q&A