2006/9/14 Kim Young Hoon

1. A Topology Control Approach for Utilizing Multiple Channels in Multi-Radio Wireless Mesh Networks (broadnet2005)Mahesh K. Marina, Samir R. Das 2006/9/14 Kim Young Hoon

2. Contents • Introduction • Problem Formulation • Channel Assignment Algorithm • Simulations Results • Conclusions

3. Contents • Introduction • Problem Formulation • Channel Assignment Algorithm • Simulations Results • Conclusions

4. Introduction • Wireless mesh networks • Wired router nodes/wireless nodes • No need of infrastructure • Wider coverage • Mesh networks with multi-hop extension of 802.11 standard • Different from 802.11 LANs: risk of disconnection • All nodes use same channel in mesh for connectivity • Inefficient Utilization of Available Channels • Need to use Multiples Channels

5. Introduction • Single radio for multiple channels? Possible. But need of ... • Dynamically switch between channels • Tight time synchronization among nodes • Slow switching  reducing synchronization requirements and overhead,  increasing end-to-end delay • Require MAC or hardware modification • Therefore, Multiple radios per node • Effective use of given channels • Overcoming the deficiencies of single radio

6. Introduction • What happens in multi-radio mesh network? • Disconnection between nodes can happen • Node’s transmission is interfered by other nodes’ • So, a key issue in multi-radio mesh network architecture is Channel Assignment Problem.

7. Introduction • Channel Assignment Problem • has to balance between connectivity and interference • is viewed as topology control problem (adjustable links between nodes in wireless) In this paper, authors proposed base channel assignment to obtain an initial, well-connected topology.

8. Contents • Introduction • Problem Formulation • Channel Assignment Algorithm • Simulations Results • Conclusions

9. Problem Formulation • Channel Assignment Problem belongs to the class of NP-complete Proof flow) Channel Assignment Problem Topology Control Problem Topology Control’s Target  Reducing Interference Channel Assignment Problem  Optimization Problem Optimization Problem  Decision Problem Showing that decision problem is in NP-complete (using minimum edge coloring) For more detail, see 2nd part of the paper

10. Channel assignment algorithm • CLICA (Connected Low Interference Channel Assignment) • Polynomial time heuristic • Order nodes by their degree of flexibility • degree of flexibility: amount of freedom when choosing channel • Greedily assign channel between nodes

11. Coloring uncolored links with a common color to already assigned radios Coloring nodes which have no available radios Greedily coloring uncolored links Channel assignment algorithm

12. Channel assignment algorithm - case 1 Initial order: a-d-c-b • Starting from a, assign channel a-b, b’s priority bumps up • Assign channel b-c, and c-d in similar manner • Node a and d have a common channel, so assign that to a-d <1> <5> b a c <2> <6> <4> d <7> <3>

13. Channel assignment algorithm - case 2 Node a and d has two radios • Starting from a, assign channel a-b, b’s priority bumps up • Assign channel b-c, and c-d in similar manner • Node a and d have additional radios, so assign different channel to a-d <1> <5> b a c <2> <6> <4> d <7> <3>

14. Channel assignment algorithm • Each coloring decision is made in a greedy fashion • Locally optimal choice • Theorem 2: CLICA algorithm yields a connectivity preserving color assignment

15. Contents • Introduction • Problem Formulation • Channel Assignment Algorithm • Simulations Results • Conclusions

16. Simulation Results – part 1 • Graph-based simulations • Interference and capacity properties of topologies generated by different channel assignment algorithms • Compared with CCA (Common Channel Assignment – assign same set of channelr to all nodes) • Measure: • Maximum link conflict weight – network wide interference • Maximum number of concurrent transmissions – total one-hop capacity

17. Simulation Results – part 1 • CCA • CCA interference performance is unaffected by the number of channels • CCA capacity performance shows a linear growth • CLICA • As the number of radios increases, interference goes up and capacity shows marginal perfromance • Minimum interference doesn’t match maximum capacity DUE TO HEURISTIC NATURE

18. Simulation Results – part 2 • Ns-2 simulations • Evaluating the performance of CLICA • Aggregate throughput and average delay • 50 nodes with 250m TX range in 1000m x 1000m • 550m interference range • 802.11 physical layer model in ns-2 • Fixed data rate of 2Mbps

19. Simulation Results – part 2: Single hop performance

20. Simulation Results – part 2: Multihop performance

21. Conclusions • The authors • have formulated base channel assignment as a topology control optimization problem • solved the channel assignment (radio-channel mapping) problem in greedy way (called CLICA) • shows the interference-reducing results by simulations

22. Q&A