1 An Arc-Path Model for OSPF Weight Setting Problem Dr.Jeffery Kennington Anusha Madhavan.

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Presentation transcript:

1 An Arc-Path Model for OSPF Weight Setting Problem Dr.Jeffery Kennington Anusha Madhavan

2 Agenda Introduction Node-Arc Model Arc-Path Model Empirical Analysis and Comparison Conclusion

3 Introduction OSPF – Open Shortest Path First  Interior Gateway Protocol Routing Information in an autonomous system  Link State based Algorithm  The state of the interface or link is used to decide the path on which the information is routed  Multiple links with same state is possible. Demand to a destination can be routed on multiple paths.

4 Routing using OSPF Routers maintain database with link state information, weights computed using link state, IP address etc. This database in each router is updated by transmitting Link State Advertisements throughout the autonomous system A shortest path tree is constructed by each router with itself as the root node and based on weights in the database.

5 Illustration of OSPF Router 2 Router 3 Router 4 Router 5 Router 1 Router 6 a Traffic from a to z =1200 z [1, 600] [1, 300] [2,300] OC-48, [3,600] [Weight, Flow] OC-12, 622 Mbps [2,300] 2488 Mbps

6 Disadvantages Lack of prior knowledge of point to point demands may result in congestion as seen in link OC-12 Updating the weights based on the link state information

7 Node-Arc Weight Setting Problem The weight-setting problem as defined by Pioro and Medhi is as follows:  Given: the network topology, the link capacities, and a set of point-to-point demands  Find: Weights and flows for each link  Constraints: the demands must be satisfied, the capacities cannot be violated, and at each node the total entering flow to a given destination is split equally among all out-going links that lie on the shortest paths to that destination.

8 Illustration of Node-Arc Model Routing 30 units from Node 2 to Node 7 Routing 10 units from Node 4 to i j f ij w ij l ij =0 c ij =50

9 Illustration of Node-Arc Model Routing 50 units from Node 2 to , 1 i j f ij W ij, c ij l ij =0 c ij =50

10 Node-Arc Model Formulation Definition of sets, parameters and variables  denotes the set of nodes (routers)  denotes the set of links (unordered pairs of nodes)  denotes the set of arcs  denotes the demand volume to be routed from origin to destination  denotes the set of pairs such that > 0  is the sum of demand volumes (i.e.) Definition of sets, parameters and variables  denotes the set of nodes (routers)  denotes the set of links (unordered pairs of nodes)  denotes the set of arcs  denotes the demand volume to be routed from origin to destination  denotes the set of pairs such that > 0  is the sum of demand volumes (i.e.)

11 Node-Arc Model Formulation  Set  denotes the capacity of arc  The requirement for commodity at node, denoted by is defined below: otherwise

12 Node-Arc Model Formulation  denotes the weight on arc  denotes the flow on arc with destination  denotes the distance from node to node on the shortest path to node  denotes the common value of the flow assigned to arcs originating at and contained in shortest paths from to  The binary decision variable = 1 if arc belongs to the shortest path to node ; else 0

13 Illustration of Node-Arc Model i j f ij w ij, c ij l ij =0 c ij =50 Routing 30 units from Node 2 to Node 7 Routing 10 units from Node 4 to

14 Formulation of Node-Arc Problem Objective: minimize Constraints:  The first set of constraints ensures that demand at node is satisfied and ensures the conservation of flow at each node  The arc capacity constraints are

15 Formulation of Node-Arc Problem (contd.)  The third set of constraints ensures that flows on shortest paths for each pair are equal.  The fourth set of constraints prevents flow on any arc that is not in a shortest path for demand node.  The next set of constraints ensures that the lengths of shortest paths for an pair are equal.

16 Formulation of Node-Arc Problem (contd.)  The boundary conditions are: w ij

17 Arc-Path Weight Setting Problem The objective is to split the flow equally on limited paths of an demand pair By limiting the candidate paths, all possible flow combinations can be enumerated A unique pattern number is assigned to a possible flow distribution in the paths The selection of a pattern suggests if there is a single or multiple shortest paths for a pair The weights on the arcs can be computed based on the pattern selection subject to capacity constraints

18 Illustration of Arc-Path Model Routing 30 units from Node 2 to Node 7 Routing 10 units from Node 4 to 7

19 Flow Distribution Pattern for 2 (o,d) Pairs - 2->3->5->7 - 2->4->5->7 - 2->4->6->7 - 4>5->7 - 4->6->7 Patterns v 7 and v 10 are selected Candidate Paths

20 Illustration of Arc-Path Model Routing 30 units from Node 2 to Node 7 Candidate Paths – 2->3->5->7; 2->4->5->7;2->4->6->7 Routing 10 units from Node 4 to 7 Candidate Paths – 4->5->7; 4->6-> i j f ij w ij l ij =0 c ij =

21 Arc-Path Model Formulation Definition of sets, parameters and variables  denotes the set of paths for demand pair  P = denotes the denote the set of paths computed using the least hops criterion.  denotes the arcs in path P  denotes the paths that include arc  denotes the pattern numbers for each pair Assumptions  The demand values for all are equal  The number of candidate paths for each demand pair is 3 (i.e.)

22 Arc-Path Model Formulation (contd.) Definition of sets, parameters and variables  Set denote the set of patterns that are associated with a single path for demand pair  Set denote the set of patterns that are associated with two paths for demand pair  Set denote the set of patterns that are associated with three paths for demand pair  Let be the path associated with pattern and let set  Let and be the paths associated with each and let

23 Arc-Path Model Formulation (contd.)  Let and be the paths associated with each and let

24 Arc-Path Model Formulation (contd.)  Let be the set of patterns  The flow in path P, pattern is stored in matrix  Let  Let be the flow of path P  Let be the length of path P  The binary variable is 1 if pattern is selected; and 0, otherwise

25 Formulation of Arc-Path Problem Objective: minimize Constraints:  The first set of constraints ensures that that only one pattern is selected for each pair.  The arc capacity constraints are

26 Formulation of Arc-Path Problem (Contd.)  The third set of constraints calculates the length of each path P  The fourth set of constraints guarantee that the weights on arcs  The following sets of constraints ensure that if a pattern with flow on a single path is chosen then the length of that path is shortest. and are equal

27 Formulation of Arc-Path Problem (Contd.)  The following sets of constraints ensure that if a pattern with flow on two paths is chosen then the lengths of those two paths are shortest  The last sets of constraints ensure that the lengths of multiple paths with flow are equal

28 Formulation of Arc-Path Problem (Contd.) The boundary conditions are given below: P and integer

29 Empirical Analysis Comparison between node-arc and arc-path models  The test cases were generated from 6 different networks  The demand value was fixed at 10 units  The capacity on the arcs were generated randomly in the range [50,100]  Each test case had a maximum of 2 hours to compute weights on the arcs

30 Summary and Conclusions OSPF algorithm involves developing a shortest path tree by each router with itself as the root node Data packets to any other router are directed along this shortest path tree. In this approach the point-to-point demands are disregarded A node-arc based integer programming model to determine the optimal weights for a given problem instance was presented The node-arc model balances flow by splitting the incoming flow at a node equally among the outgoing arcs.

31 Summary and Conclusions The node-arc model is very difficult to solve An improved alternative model using an arc-path approach was presented The arc-path model splits the flow at origin node equally among all the outgoing paths. The arc-path approach allows the user to restrict the number of candidate paths Restricting the solution space allows much larger problems to be solved using the arc-path approach