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

Contents Introduction Problem Formulation Channel Assignment Algorithm Simulations Results Conclusions

Contents Introduction Problem Formulation Channel Assignment Algorithm Simulations Results Conclusions

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

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 802.11 interface를 싼 값에 장비할 수 있다는 점. 주어진 채널을 효과적으로 사용할 수 있다는 점 하나의 radio를 사용할 때의 단점들을 극복할 수 있다는 점.

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.

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.

Contents Introduction Problem Formulation Channel Assignment Algorithm Simulations Results Conclusions

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

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

Channel assignment algorithm 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 - 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 <5> <1> b a c <4> <6> <2> d <7> <3>

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 <5> <1> b a c <4> <6> <2> d <7> <3>

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

Contents Introduction Problem Formulation Channel Assignment Algorithm Simulations Results Conclusions

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 802.11b와 802.11a를 본따 3개의 channel과 12개의 channel에서 실험하였으나 발표에서는 12개만을 인용하겠다.

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

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

Simulation Results – part 2: Single hop performance

Simulation Results – part 2: Multihop performance

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

Q&A