topology aggregation and multi-constraint qos routing presented by almas ansari
TRANSCRIPT
![Page 1: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/1.jpg)
Topology aggregation and Multi-constraint QoS
routing
Presented by Almas Ansari
![Page 2: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/2.jpg)
Flow of the presentation
• The Scalability Problem
• Need for Topology Aggregation
• Topology Aggregation Schemes
• Assigning Values to Logical Links
• Multi-Constrained QoS Routing
• Conclusions
![Page 3: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/3.jpg)
The Scalability Problem
• Routing consists of 2 basic tasks:
- collecting network state information
- finding a feasible path for a connection
based on this information
• Topology is usually obtained from a link state protocol like OSPF.
![Page 4: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/4.jpg)
• As the network grows larger, it is impossible to broadcast topology to every node because it takes too much space, time and bandwidth.
• Ways to deal with this problem:- reducing the no. of topology updates (Goal : deliver as infrequently as possible without affecting routing performance.)
- topology aggregation (Goal: reduce the size of the messages without affecting routing)
- combining both
![Page 5: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/5.jpg)
Need for Topology Aggregation
• TA: very important technique to achieve scalability.
• Reduces routing information and thereby routing table sizes by very large magnitude.
• Achieved by dividing networks into smaller, manageable routing domains.
![Page 6: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/6.jpg)
• Internal details of a domain topology is aggregated before broadcasting.
• Inside the domain : complete view
• Outside the domain: aggregated view
![Page 7: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/7.jpg)
• Aggregated view is used by outside nodes to make routing decisions.
• Hence aggregated topologies must be as accurate as possible.
• An efficient TA scheme must provide an adequate balance between compaction and accuracy.
![Page 8: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/8.jpg)
Topology Aggregation Schemes
• Full Mesh• Single Node • Star• Spanning Tree• ?
All schemes suffer from varying degrees of distortion.
![Page 9: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/9.jpg)
Full Mesh• All border nodes connected by logical links.
• A logical link has QoS parameters like a physical link.
• How to come up with these parameters?
• This is still a huge matrix of b(b-1)/2 links.
• Does not scale well.
![Page 10: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/10.jpg)
Single Node
• One node will represent each routing domain.
• It has QoS parameters.
• Parameters may be the best, worst or average of all links.
• Sometimes the values of the diameter of the graph is used.
![Page 11: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/11.jpg)
Star
• Here border nodes are connected via logical links to a virtual nucleus.
• Bypasses may be allowed.
![Page 12: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/12.jpg)
Spanning Tree
• A spanning tree of all border nodes is created.
• To make the representation more accurate, start by including crucial links.
![Page 13: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/13.jpg)
QoS Parameters – How to assign them to logical links?
• 2 types of QoS parameters:- link constraint (e.g. bandwidth)
- path constraint (e.g. delay)
• Additive or Restrictive
• Other e.g. : delay jitter, cost etc.
![Page 14: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/14.jpg)
• A fundamental step in TA is assigning the QoS parameters to logical link.
• Choosing these values correctly is crucial because improper values may lead to rejection of supported calls (under-estimation) or crankback i.e. failure to support an accepted call (over-estimation).
• Assigning values to logical links is easier to do when one metric is under consideration
• Take best, worst or average values.
![Page 15: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/15.jpg)
• It is very difficult to do aggregation with bounded distortion when 2 or more parameters are under consideration.
• If a link has 2 parameters b and d, we can find separate optimal paths for each b and d. If we can find a path that maximizes b as well as minimizes d, then a jointly optimal path is found.
• A jointly optimal path i.e. that provides better values for all metrics may not exist.
• In such cases, other ways to assign values are used.
![Page 16: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/16.jpg)
Conventional approaches to assign values for multi metrics:
Single Path Parameters Approach- Decide on the most important parameter
- How to decide upon the most important parameter?- Find the best path according to this parameter
- Assign values of this path to the logical link
![Page 17: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/17.jpg)
Multiple Path Parameters Best Case Approach- find best path between 2 border for each metric- assign the logical link the best values- aggressive method: since high possibility of crankback
Multiple Path Parameters Worst Case Approach- find worst path between 2 border for each metric- assign the logical link the worst values- under estimation method: since high possibility
of supported calls not being admitted
![Page 18: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/18.jpg)
QoS Routing• The notion of QoS has been proposed to capture
the qualitatively or quantitatively defined performance contract between the service provider and the user application.
• QoS routing selects network routes with sufficient resources for the requested QoS parameters.
• Goal: satisfying the QoS requirement for every admitted connection.
![Page 19: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/19.jpg)
• A QoS routing algorithm may fail to find a feasible path for a connection because:
- such a path does not exist
- the searching space of a heuristic approach
does not cover any existing a feasible path
• When this happens the system can either reject the connection or negotiate with the application for a looser QoS constraint.
![Page 20: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/20.jpg)
Multi-Constraint QoS Routing
• Multi-Constrained QoS routing deals with finding routes that satisfy multiple independent QoS constraints.
• Is NP-Hard
• The basic QoS routing problems can be:
• Link optimization routing
e.g. b optimization routing
finding widest route from src to dst.
![Page 21: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/21.jpg)
• Link constrained routing
e.g. b constrained routing
finding a path from src to dst such that b is not less than a certain value on all links.
Link optimization problem can be reduced to link constrained problem and then solved by a slightly modified DA or BFA.
![Page 22: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/22.jpg)
• Path optimization routinge.g. d optimization routingleast delay path
• Path constrained routinge.g. d constrained routingd of path below a certain value
• These problems can be solved by directly by DA or BFA.
![Page 23: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/23.jpg)
• Now consider a link has 2 parameters b and d.
• Of this we can have several combinations of routing problems.
• E.g. link-constrained path-optimizationi.e. To find the least delay path that has a bandwidth constraint
• Can be solved by a shortest path algorithm which works on a graph whose links that violate the bandwidth requirement have been pruned.
![Page 24: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/24.jpg)
• Other four problem classes are:
- link-constrained link-optimization
- multi-link constrained
- link-constrained path-constrained
- path-constrained link-optimization
• These are solvable in polynomial time by a modified shortest path algorithm.
![Page 25: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/25.jpg)
• Other difficult to solve problem classes are: - path-constrained path-optimization e.g. delay-constrained least-cost routing finding the least cost path with bounded delay.
- multi-path constrained e.g. delay-delay jitter constrained finding a path with bounded delay as well as bounded jitter.
![Page 26: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/26.jpg)
• If all metrics except one take bounded integer values then the problems are solvable in polynomial time by running the EBFA.
• EBFA finds all optimal paths at each node.
• Very high space and time complexity.
![Page 27: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/27.jpg)
• Limited granularity and Limited path heuristics can be used.
• Limited granularity heuristic uses bounded finite range to approximate QoS metrics. Problem can now be solved in polynomial time.
• Limited path heuristic limits the no. of optimal paths stored at each node, thereby reducing space complexity.
![Page 28: Topology aggregation and Multi-constraint QoS routing Presented by Almas Ansari](https://reader030.vdocuments.us/reader030/viewer/2022032606/56649e955503460f94b9965e/html5/thumbnails/28.jpg)
Conclusions
• TA is very important to achieve scalability.
• All TA schemes suffer from some distortion.
• Multi-Constrained QoS routing is difficult.