Fangting Sun Mark Shayman University of Maryland, College Park {ftsun, shayman}@glue.umd

1. Minimum Interference Algorithm for Integrated Topology Control and Routing in Wireless Optical Backbone Networks Fangting Sun Mark Shayman University of Maryland, College Park {ftsun, shayman}@glue.umd.edu

2. Introduction • Advantages of free space optics • Topology control • The number of the transceivers is an important constraint in point-to-point wireless network • In low mobility optical wireless backbone network, it is reasonable to setup bandwidth guaranteed paths

3. System Assumptions • Each node is either stationary or has low mobility • Each node is equipped with a limited number point-to-point wireless interfaces • A unidirectional wireless communication can be setup between a node and its potential neighbor • No interference between transmissions • Either • All network information is known to all nodes and routing path of an arriving request is computed at its source, or • Routes are computed at a centralized route server

4. System Model • Node Transformation: modeling interfaces • Simple Example: modeling potential links

5. Request 12 with demand r is routed on the network Another request 14 with demand q or Modeling Actual Links Forming new link consumes interfaces; routing through existing link consumes BW.

6. Minimum Interference Routing • References • K. Kar, M. Kodialam and T. Lakshman, JSAC, 2000. • I. Iliadis and D. Bauer, Networking 2002, LNCS 2345. • Network with fixed topology • Requests for BW guaranteed paths arrive randomly with no information about future requests • Request is routed so as to minimize interference it may cause for routing of future requests • Links are weighted according to their potential importance for future requests • Minimum weight path is chosen to route current request • Our main contribution: Extend to integrated topology control and routing by introducing notion of interface interference

7. K-WSP under bottleneck and interface elimination • Select a WSP between pair (s, d) • Lpsd1 is the set of links constituting this WSP btlsd1 is the corresponding bandwidth • Lbsd1is the subset of links whose residual bandwidth is btlsd1 • Ibsd1 is the subset of interface links in Lpsd1 • Select second WSP for (s, d) after Lbsd1 and Ibsd1 are removed • Repeat this procedure until either K WSPs are found or no more WSP is available

8. Critical link and critical interface • Once used, the chance that some future requests can be satisfied decreases dramatically • Compute the critical weight for each link and interface using K-WSP under bottleneck and interface elimination procedure • ith WSP is more important than the (i+1)th WSP • A link with less residual bandwidth is more critical, r(l) is the residual bandwidth of link l • A free interface on a node with fewer free interfaces is more critical, o(l) is the number of free interfaces of l’s owner node • Basic weight for general links and the interface links is different, wB is the basic weight for general links and wI is for interface links • Different ingress-egress pair has different importance, asd is used to reflect the relative importance

9. Critical link and critical interface,cont. • Weight function • General links • Interface links (1) (2) Novel feature: putting weights on interfaces to model the interference that setting up a link causes for future links that may be needed.

10. Integrated Algorithm • Input: • Transformed network graph G(N,E); • Set B indicating the residual bandwidth for each link; • Set I indicating the interface usage situation; • Set P of ingress-egress pairs; • A setup request (sk, dk, bk) • Output • Pathbetweensk and dk with bkunits or none. • Procedure • Assign weight w(l) for each link according to equation (1) and (2) using previous procedure • Eliminate the links whose residual bandwidth is smaller than bk • Use Dijkstra’s algorithm to compute min-weighted path R • If R exists, reserve bandwidth and update sets E, B and I

11. Simulation Setup • Node number: 100 • Moving range: 1000 x 1000 • Interface constraint: 4 transmitters and 4 receivers per node • Transmission range: 150 (network 1) and 175 (network 2) • Ingress-egress pair number per set: 50 • Bandwidth demand per request: uniform(1, 3) • Initial bandwidth: 1000 (static case) and 20 (dynamic case) • Dynamic case • Requests arrival process between each ingress-egress pair: Poisson • Requests holding time: exponentially distributed

12. Performance Studies Static Case: Once a request is routed, it never leaves the network For each network, 10 rounds of simulations are performed. Each round uses different ingress-egress pairs set, and to each pairs set 10 different request sequences (5000 requests per sequence for net 1 and 10000 requests per sequence for net 2) are computed to get average.

13. Performance Studies, cont. Dynamic Case: A routed request will leave the network after some holding time For each network, 10 rounds of simulations are performed. Each round uses different ingress-egress pairs set, and to each pairs set 10 different request sequences (10000 requests per sequence) are computed to get average.

14. Conclusion • An algorithm for integrated topology control and routing in wireless optical backbone networks is developed • The performance of proposed algorithm is superior to existing alternatives