QoS Routing using Clustering with Interference Considerations

1. Source • Clustering 2. Intercluster next hop Links 3. Intracluster Routing Gateway Node Dest Nodeid 2 Current Cluster More Frequent Less Frequent 4 6 1. Clustering 1 Bidirectional Links Color Clusterid 5 4. Reservation and Forward 3 Motivation Admission Control Clustering Intercluster Routing Intracluster Routing Simulation Future Work Admitted high Trial QoS Routing using Clustering with Interference Considerations Eric Chi, Antonis Dimakis, Zhangfeng Jia, Teresa Tung, Jean Walrand <echi, dimakis, jia, teresat, wlr>@eecs.berkeley.edu University of California at Berkeley Topology 2 • We study QoS Routing using clustering with interference considerations. • We focus on the cost of decoupling the computation to clusters. Routing Strategies Topology 1 • OSPF: Weight on link j is 1/C+max{Ui} where • C is the speed of link j • Ui is the utilization of link i • Link j belongs to a set of cliques for which each has constraint Ui of which max{Ui} is the largest • Integer Linear Program: Uses clique constraints Decomposition Network Graph all links in the same clique Load/Topology Admission 1 • Minimize the number of interfering links outside of a cluster subject to a constraint on cluster size. • Damped Clustering • Prospective Clustering: Updated Frequently • Actual Clustering: Updated from Prospective Clustering when better used for Routing • Initially, each node is its own prospective and actual cluster Routing Strategy Full Clique Constraint U12+U21+U13+U31+…+U56+U65 1 Even Decomposition U12+U13+U31+U32+U34+U35+U53+U54+U56 1/3 U21+U23+U24+U42+U43+U45+U46 1/3 U64+U65 1/3 Prospective Clustering Algorithm executed per node Randomly assign clusterid from set of clusterids of neighboring nodes Toss a coin heads with probability P heads Wait a random time tails Proportional Decomposition U12+U13+U31+U32+U34+U35+U53+U54+U56 1/2 U21+U23+U24+U42+U43+U45+U46 7/18 U64+U65 1/9 Medium: Average 5 flows active per time High: Average 10 flows active per time Node becomes a new cluster Network Utilization • Limit the propagation of cross cluster information using Fisheye strategy • Nearby clusters exchange link state information more frequently. Local information is more accurate. • Each cluster has its own view of the intercluster topology. • OSPF at intercluster level per cluster hop • Each cluster calculates the intercluster route using OSPF and its current view of the intercluster network topology • Intracluster routing to reach the next cluster • Forward the request to the next cluster. 2 • By checking clique constraints • Measurement • Run trial flow with same characteristics for T seconds • Trial packets served with low priority • Accept flow if all links able to serve trial packets • Analysis for the cost of decoupling the routing to per cluster computations • Intercluster Routing • OSPF • What information to forward to the next cluster • Timing and mobility effects in simulation • Introduces inconsistency which makes global calculation infeasible • Rerouting • Measurement • To refine/estimate clique constraints • For admission control • Dimakis, He, Musacchio, So, Tung, Walrand. “Adaptive Quality of Service for a Mobile Ad-Hoc Network” MWCN October 2003. • Pei, Gerla, Chen. “Fisheye State Routing in Mobile Ad-Hoc Networks” ICDCS Workshop on Wireless Networks and Mobile Computing 2000.