Routing Basics Quality of Service Routing Routing in Wireless Mesh Networks Research Challenges Projects

Transcription

1 11/03/2009 Oslo, NO Marília Curado Routing Basics Quality of Service Routing Routing in Wireless Mesh Networks Research Challenges Projects 4

2 Routing Basics Quality of Service Routing Routing in Wireless Mesh Networks Research Challenges Projects RIP OSPF BGP 5 6 Goals End-to-end d connectivity it Maximise network performance Fault tolerance Adaptation ti to dynamic topologies IG IG IG EG IG IG IG EG IG IG IG Sistema autónomo Building blocks Routing policies Routing information exchange Path computation Routing table maintenance Forwarding Sistema autónomo Core Network EG Sistema autónomo IG IG IG IG IG - Interior Gateway EG - Exterior Gateway IG 7 8

3 Protocol Exchange of routing information Algorithm (Shortest) Path computation V V V4 1 1 V V V6 Distance Vector Each router sends to its neighbors information about the distance to all the destinations it knows Link State Each router sends/floods information about the state of its links 9 10 Routing Information Protocol (RIP) Open Shortest Path First (OSPF) Border Gateway Protocol (BGP) Routing Information Protocol (RIP) Interior Gateway Routing Protocol (IGRP) Each router sends to its neighbors information about the distance to all the destinations it knows Based on the information received from its neigbors, each router computes the shortest path to all destinations Routing metric Number of hops Algorithm Bellman-Ford The routers are not aware of the topology of the network only the distance to the destinations 11 12

4 Open Shortest Path First (OSPF) Each router floods information about the state of its links Every router has a complete map of the network topology Routing metric Number of hops Value configured Algorithm Dijkstra Fast convergence without loops Flooding Coherent maps of the network in all nodes Support for multiple metrics One network map for each metric Support for multiple paths Load balancing QoS aware routing Scalability Hierarachical routing 15 16

5 Sistema autónomo ASBR Área A ABR Área C Área B ABR Category Information Maintained Communication Partners Information Distributed Distance vector Distance vectors for all destinations Neighbour nodes Distance vectors for all destinations Network weighted graph All nodes in the State of the Link state network individual links of each node ASBR Path Vector Protocols Border Gateway Protocol (BGP) Inter-Domain Routing Protocol (IDRP) Why not Link State or Distance Vector? Distance-vector Assumes all routers use the same routing metric Policy information is not distributed Link-state Metrics may vary in different autonomous system Flooding between different autonomous systems is very hard 19 20

6 Routing information Sequence of the autonomous systems to be traversed to reach the destination Policies may be used to choose autonomous system to favor or to avoid Without routing metrics No problem of inconsistency between autonomous systems No value for the cost to reach the destination Distributes information about the autonomous systems to be used to reach the destination Initially, BGP routers exchange the complete routing tables Afterwards, only updates are distributed to the neighbor autonomous systems Each message contains at least: Source of the information (RIP, OSPF, ) List of autonomous systems to reach the destination (AS-PATH) Next Hop If there are more than one path to the destination, i the autonomous systems traversed may me analysed and the best one selected according to policies Routing protocol Routing algorithm Routing metrics Routing Basics Quality of Service Routing Routing in Wireless Mesh Networks Research Challenges Projects Routing scope 23 24

7 Nowadays the Internet is used in almost all everyday situations, ranging from the simple exchange and web browsing, through videoconferencing and distributed games, up to distributed simulations and virtual reality. This wide variety of applications has brought up the limitations of the best-effort service provided by the original Internet. Why Quality of Service? For applications i Improved performance Seamless utilization For providers Resource Optimization Over-provisioning avoidance For users Cost control Utilization of modern applications IETF flavors Integrated Services Differentiated Services Signaling RSVP NSIS Technology IEEE e IEEE d IEEE e Quality of Service routing aims at selecting suitable paths for the different types of traffic generated by diverse applications based on information about the state of the network with the objectives of improving i the traffic performance and network resource utilization. The first objective concerns the level of service offered to the end-user. The second objective pertains to the revenue obtained by Internet Service providers

8 Simplicity: minimize the number of signalling messages and the memory needed d to store the routing tables Robustness: avoid forwarding errors that may lead to packet loss, loops and instability Fast convergence time: react promptly to network changes and provide rapidly all routers with a consistent vision of the network Stability: adapt in a limited manner to the dynamic of the network without causing routing oscillations Scalability: be able to scale to large networks and high traffic volumes Resiliency: support alternate paths / mechanisms to be used in case of failure to be used in case of failure How can we do it? How much does it cost? Do we need it? Is it feasible? Why not overprovisioning? It s all about metrics and algorithms! Anything else? Besides, it is about applications, topologies, users, types of networks, ISP policies, business models, technologies, IETF, QoS models, You name it! So, let s start smoothly 31 32

9 Traditional routing algorithms Compute the shortest path to the destination To select paths suitable for traffic with diverse requirements Improve network utilization All packets for a certain destination are forwarded to the same NH How to support different QoS needs? Traffic requirements Explicit QoS parameters Classes of service QoS parameters Delay Jitter Losses Nº hops Bandwidth Quality of Service Routing g(q (QoSR) Multi-Constrained Path Problem To find a path P between nodes s and d, d such as w ( P ) L, i = 1, 2,..., q i i q A B w i (P) - weight of path P for metric i L i maximum metric value for a path to be admissible P is an admissible path Restrictions (from A to B): Dl Delay (D) <= 25, Available bandwidth (BW) >=

10 Routing granularity Destination address Destination address, class of service Flow Routing decision Hop-by-hop Source-based Path computation Pre-computation On-demand d Hybrid Routing metric Number of hops Available bandwidth Delay Losses Algorithm Distance vector Link state Destination address All the packets for the same destination are forwarded to the same NH No alternate paths are used Destination address, class All the packets of the same class for the same destination are forwarded to the same NH Alternate paths per class + load balancing + state Flow + complexity All the packets of the same flow are forwarded to the same NH Hop-by-hop p + Scalability + Response time - Loops may occur - Complex QoS routing Signaling is needed Source + More complex algorithms can be used - Inaccuracy - Scalability Most used for QoSR 39 40

11 Pre-computation + Setup time - Path computation for all requirements and destinations On-demand + Network state is up-to-date + Only the needed path is computed - Processing overhead if the request arrival rate is high 1. Information distribution communication overhead 2. Metric selection path computation algorithm complexity 3. Routing table structure complexity and storage 4. Stability 5. Inaccuracy QoSR: on-demand or hybrid approaches Which information? Topology Resources available Congestion state How? LSAs extensions Probing Signaling When? Topology changes Network state t changes Periodically When needed QoSR causes communication resource consumption the increase in the amount of routing information exchanged the amount and size of routing messages the number of routers that must receive the routing messages Trade-off: up-to-date data/communication overhead Solutions Quantification: average, moving average Threshold h based emission i of updates Selective flooding Hierarchical organization 43 44

12 1. Information distribution communication overhead Applications have multiple requirements 2. Metric selection path computation algorithm complexity Paths must satisfy multiple requirements 3. Routing table structure complexity and storage 4. Stability The complexity of the path computation algorithm depends on the composition rule of the metrics used 5. Inaccuracy Metric composition rules Additive Multiplicative Concave m ( p ) = m ( l i ) n ( Number of hops i= 1 m ( p ) = m ( l i ) n i= 1 m ( p ) = min( li ), i = 1,2,..., n Losses Bandwidth Problem To find a path which satisfies two or more additive or multiplicative constraints is NP- complete What can we do?? 47 48

13 Algorithmic Approaches Exact Algorithms No complexity reduction, optimal solutions Heuristics Algorithms Complexity reduction, near optimal paths Hybrid Algorithms Flexible approach to be used under multiple circumstances Bandwidth Restricted Paths (BRP) Bandwidth + additive metric Metric ordering Sequential filtering Restricted Shortest Paths (RSP) 2 additive metrics Heuristics Metric ordering Metric combination Extensions to Bellman-Ford or Dijkstra algorithms Heuristics: i Reduce algorithm complexity/processing overhead Metric ordering To identify the most important metric To select the best path according the first metric In case of a tie, select the best path according to the second metric Sequential filtering To exclude all the links which have less bandwidth than a certain threshold Pruning policy On-demand path computation: the request depicts the value Path pre-computation: to establish value ranges Shortest-widest path Widest-shortest path Load balancing Better performance with light load Damages best-effort traffic performance Limit resource consumption Better performance with high load More resistent to routing information inaccuracy To select the shortest path according to the second metric on the pruned graph 51 52

14 Metric ordering To find feasible paths according to one constraint Select the best/optimal path according to the second constraint Metrics combination Given two additive i metrics delay d(e) and cost c(e) for a link e Where α and β are the relative weights of each metric Example: Delay-Constrained Least Cost (DCLC) problem Network: G(V,E) Edge e = (u,v) E has two associated metrics: Cost - c(e) and Delay - d(e) Given a source node s and a destination node d, P(s, d) is the set of all paths from s to d. c ( Pi ) = c( e) d ( Pi ) = d( e) e P i e P i ' P ( s, d ) : d ( P ) Δ DCLC : i dl delay min c( P) ' Pi P ( s, d ) i 53 w ( e ) = α c ( e ) + β d ( e ) w( P) = e P w( e) Do you find any problems with this approach? Information distribution communication overhead 2. Metric selection path computation algorithm complexity Large routing table Long lookup Limited scalability What to do? 3. Routing table structure complexity and storage 4. Stability Store only the best path Use a normal routing table for BE and on-demand path computation for QoS flows Use class-based routing 5. Inaccuracy 55 56

15 Basic forwarding does destination-based packet classification and a corresponding Forwarding Information Base lookup 1. Information distribution communication overhead QoS-aware packet classification depends on the traffic classification used in the network Flow classification - there is the need to keep in the FIB one entry for each flow MPLS networks - a layer two lookup is done and the classification is only made using a label 2. Metric selection path computation algorithm complexity 3. Routing table structure complexity and storage Solutions Efficient packet classification Fast hardware lookup methods of commercial routers 4. Stability 5. Inaccuracy Instability occurs when reaction is excessive Sources of instability Congestion based metrics Update distribution policies Network topology Traffic patterns Mobility Approaches to avoid instability Distribution of quantified metrics Load balancing Hybrid routing Long duration flows: on-demand Short duration flows: pre-computation Route-pinning Class-pinning 59 60

16 Advertisement of metrics that are quantified instead of advertising instantaneous values Contributes to routing stability, but Reduces the dynamic nature and the adaptation capabilities of the routing protocol Hybrid routing (1) Long duration flows: on-demand Short duration flows: pre-computation It is necessary to configure the mechanism of metrics quantification in order to achieve a fruitful trade-off between routing stability and routing adaptation Two timescales for metrics evaluation Long-term timescale, end-to-end delay information is used for path pre-computation Short-term t timescale, local l queuing delay information is used to adjust the pre-computed paths to handle temporary traffic bursts without the need of computing all the paths in the network Dynamic routing is only used for long-lived flows reduces communication and processing overhead Long lived flows avoid successive path computations contributing to stability Hybrid routing (2) Long duration flows: smoothed metric Short duration flows: actual metric Information distribution communication overhead 2. Metric selection path computation algorithm complexity It is desirable that the state kept at all routers remains up-to-date and that it reflects the complete and detailed state of the network However, is this possible? 3. Routing table structure complexity and storage 4. Stability 5. Inaccuracy 63 64

17 Sources Reduced frequency of updates Information aggregation in hierarchical networks Delay introduced in large networks Utilization of estimates Due to this wide range of factors, the global state that is kept by each router is just an approximation of the real actual state When the path computation algorithms use this inaccurate information as if it was exact, their performance can be highly damaged Approaches State of the network represented as probability functions Probing instead of flooding State of the network represented as probability functions QoS routing algorithms that cope with inaccuracy in routing information need to be adapted to make path computation based on information that is neither complete nor exact. Multiple-path routing 67 68

18 Problem Scheme Metrics Algorithm Bandwidth- Logarithmic-BCP-ISI Logarithmic function of the probability Shortest-Path Constrained Path that t a link can accommodate a (e.g. Dijkstra) under Inaccurate State Information (BCP-ISI) Relaxed-BCP-ISI connection Mean and variance of the bandwidth available in the link Modified Dijkstra Safety-Based-Routing(SBR) Safety metrics: estimation of the Safest-Shortest S test maximum change of bandwidth until the next update Path or Shortest Safest Path Delay-Constrained Path under Basic-Delay-Constraint (BDC) p.d.f of the minimum delay the link can provide plus the propagation delay Link-State for special cases Inaccurate State Information (DCP- ISI) Bandwidth-Delay Constrained Path under Inaccurate State Information (BDCP-ISI) Random-Basic-Delay-Constraint (RBDC) Transformed-Delay-Constraint (TDC) Association of Relaxed-BCP-ISI and Random-Basic-Delay-Constraint Transformation of the mean and variance of the queuing delay p.d.f of the available residual rate on the link Modified Dijkstra Algorithm min- PR Mean and variance of the bandwidth Link-State for available in each link and transformation special cases of the mean and variance of the queuing delay Probing instead of flooding The utilization of probing avoids the staleness of link-state information because the probes gather the most recent state information Multiple-path routing Scheme Metrics Algorithm Random-Safety-Based-Routing (R-SBR) Safety metrics Randomized extension to Safest- Shortest Path (Modified Bellman- Ford) Randomized Bandwidth-Delay Constrained path (R-BDC) Safety metrics and delay (transformed in number of hops) Randomized Multiple-path Shortest-K-Widest Path (SKWP) Bandwidth Pruned K-Shortest Path (Modified Dijkstra) Widest-K-Shortest Path (WKSP) Bandwidth Pruned K-Shortest Path (Modified Dijkstra) Random-K-Widest Path (RKWP) Bandwidth Pruned K-Shortest Path (Modified Dijkstra) Bypass Based Routing (BBR) Proportional Sticky Routing (PSR) Obstruction metrics Flow blocking probability Shortest-Obstruct-Sensitive Path (SOSP) and the Obstruct-Sensitive- Shortest-Path (OSSP) Weighted-Round-Robin-Like Path (WRRLP) QoSR-DiffServ QoSR complements DiffServ by selecting different paths for different traffic classes Traffic differentiation in routers performed by DiffServ mechanisms QoSR-IntServ QoSR selects paths for PATH messages RSVP reserves resources QoSR-MPLS QoSR selects paths MPLS uses LDP to establish LSPs 71 72

19 Intra-domain QoSR Single administrative control Flexible, efficient Inter-domain QoSR Multiple administrative control Simple, stable and inter-operational BGP extensions QoS support Traffic control schemes Internet-wide Overlays End-system Multi-homing Smart routing Different requirements! QoS BGP extensions New QoS attributes distributed in BGP UPDATE messages Inband signalling results in low converge and instability problems Dynamic changes on network state are not considered Traffic control schemes Overlay network-based mechanisms A large number of overlay entities is placed across several ASes The role of these nodes is to periodically monitor the performance and availability of paths between them However, since overlays do not control de beahaviour of the underlying infrastructure, t QoS support may not be ensured 75 76

20 Traffic control schemes Multi-homing Consists on the increase of Internet connectivity by contracting multiple broadband lines Smart Route Controller (SRC) 1 Destination prefixes: p1, p2, p3, p4 INC3 INP1 4 5 Used by multi-homed stub ASes, as they 2 provide a INP2 holistic way to solve local end-to-end traffic INP3 challenges through shifting some traffic between ISPs in short timescales 3 INP4 INP5 6 Pros: To find paths suitable for different types of traffic Improve network utilization Cons: Communication, processing and storage overhead Complex implementation Instability may occur SRC INC1 SRC INC Routing Basics Quality of Service Routing Routing in Wireless Mesh Networks Research Challenges Projects Routing Protocols Routing metrics Quality of Service Routing Protocols 79 80

21 AKA table driven - From the wired world : Paths are pre-computed Updates are exchanged periodically For networks with low mobility and frequent data transmission + Response time - Communication overhead - Processing overhead due to frequent path computation and computation of useless paths to destinations which are not popular DSDV - Highly Dynamic Destination-Sequenced Distance-Vector Routing OLSR - Optimized Link State Routing protocol AKA on demand From the signalling world Paths are determined d upon request For networks with high mobility and infrequent data transmission + Node lifetime + Bandwidth since requests are only sent on demand - Bandwidth when flooding is used - Response time due to the route discovery mechanism DSR- Dynamic Source Routing Protocol AODV- Ad Hoc On-Demand Distance Vector DYMO - Dynamic MANET On-demand A combination of pro-active and reactive Typically proactive in defined d zones and reactive outside + The best of both worlds - Creation and management of zones/clusters MAC parameters Traffic load Interference Noise Topology Has routing anything to do with these? ZHLS - Zone-based Hierarchical Link State ZRP - Zone Routing Protocol CBRP - Cluster Based Routing Protocol MAC performance can be considerably impacted by routing decisions MAC / Routing Cross-layer metrics 83 84

22 Hop count + Easy computation - Does not consider the characteristics of wireless environments (different link transmission rates, loss ratios) - Does not consider congestion level Expected Transmission Count Metric (ETX) + Takes into consideration link loss ratios and interference between the successive links of a path - Does not consider different transmission rates - Does not include link utilization Expected Transmission Time (ETT) Intra-flow interference: Inter-flow interference: + Evolution of ETX Interference + Takes of into adjacent account links link Interference loss ratio between and multiple bandwidth flows using the same channel from one or multiple sources - Does not consider channel interference Weighted Cumulative ETT (WCETT) + Computes ETT over a path + Considers intra-flow interference - Does not consider inter-flow interference Metric of Interference and Channel Switching (MIC) + Considers intra-flow interference channel diversity + Considers inter-flow interference ETT weighted by the number of nodes it interferes with - Overhead needed to maintain up to date information - Does not consider traffic load in each node QoS extensions for AODV (QAODV) QoS extensions to OLSR (QOLSR) QoS extension to DYMO (DYMOQoS) Multiple-path routing metrics Channel Aware Multipath (CAM) Weighted Interference Multipath (WIM) 87 88

23 Routing Basics Quality of Service Routing Routing in Wireless Mesh Networks Research Challenges Projects Routing & mobility Routing for resilience Routing & cross-layer design Routing and forwarding security in MANETs Routing scalability Wireless networks dissemination Network types Cellular Networks (with infrastructure) Ah Hoc Networks Sensor Networks Different technologies UMTS Bluetooth Integration of technologies 3rd and 4th Generation networks Challenges Limitation of devices Low processing Low resources Low memory Low autonomy (energy) Radio interference High mobility Inaccurate path information No centralized management 91 92

24 In networks failures may occur: Due to: hardware degradation malicious attacks maintenance operations human errors accidents natural disasters topology changes (mobility) For variable amounts of time: short-termed (transient failures) medium-termed failures (updates/reboots) long-termed failures (fibber cut) Check this paper: Ian F. Akyildiz, Xudong Wang, Cross-Layer Design in Wireless Mesh Networks, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 57, NO. 2, MARCH Routing Basics Quality of Service Routing Routing in Wireless Mesh Networks Research Challenges Projects Study of Routing Mechanisms for Mobile Adhoc Networks David Palma QoS Routing in Wireless Mesh Networks Vinicius Borges Interference-aware Routing Metrics for Wireless Mesh Networks Daniel Pereira Analysis of Clustering Schemes for Mobile Ad-Hoc Networks Luis Conceição Routing and Forwarding Security in WMNs Viviane Lima and Vitor Ruivo 95 96

25 Q3M - QoS Architecture for Multi-user Mobile Multimedia Sessions in 4G Systems EuQoS End-to-End E d QoS Support Over Heterogeneous Networks WEIRD WiMAX Extensions to Isolated Data Research Networks Research Networks GINSENG Performance Control in Wireless Sensor Networks Use of WSNs in industrial environments where performance assurances are critical. MICIE Tool for systemic risk analysis and secure mediation of data exchanged across linked CI information infrastructures To design and implement e a so-called "MICIE alerting system" that identifies, in real time, the level of possible threats induced on a given CI by "undesired" events happened in such CI and/or other interdependent CIs David Palma, Marilia Curado: "NODRoP, Nature Optimized Deferred Routing Protocol", INFOCOM'09, 28th Annual Joint Conference of the IEEE Computer and Communications Societies - Student Workshop, 2009 Alexandre Fonte, Marilia Curado, Edmundo Monteiro, Interdomain quality of service routing: setting the grounds for the way ahead, Annals of Telecommunications, Springer Paris, ISSN , Volume 63, Numbers / December, 2008, pp David Palma, Marilia Curado, Inside-out OLSR Scalability Analysis, submitted to the 7th International Conference on Wired / Wireless Internet Communications, University of Twente, The Netherlands, May 27-29, 2009 Daniel Pereira, Alicia Trivino Cabrera, Marilia Curado, Analysis of Metrics for Routing Optimization in Wireless Mesh Networks, International Workshop on Traffic Management and Traffic Engineering for the Future Internet (FITraMEn 08), Porto, Portugal, December, 2008 Alexandre Fonte, José Martins, Marilia Curado, Edmundo Monteiro: Stabilizing Intelligent Route Control: Randomized Path Monitoring, Randomized Path Switching or History- Aware Path Switching?. In Proc. of MMNS 2008, Samos, Greece, September 2008 Viviane Lima, Vitor Ruivo, Marilia Curado, Securing Wireless Mesh Networks: a Winning Combination of Routing and Forwarding Mechanisms, submitted to the First IFIP Conference on Network and Service Security, Paris, France, June 24-26, 2009 Masip-Bruin, X., M. Yannuzzi, J. Domingo-Pascual, A. Fonte, M. Curado, E. Monteiro, F. Kuipers, P. Van Mieghem, S. Avallone, G. Ventre, P. Aranda-Gutierrez, M. Hollick, R. Steinmetz, L. Iannone and K. Salamatian, 2006, "Research Challenges in QoS Routing", Computer Communications, Vol. 29, pp

26 i