Gautam Kulkarni & Vijay Raghunathan UCLA Networked and Embedded Systems Lab (NESL) Adaptive, Traffic-based Channel Allocation.

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Presentation transcript:

Gautam Kulkarni & Vijay Raghunathan UCLA Networked and Embedded Systems Lab (NESL) Adaptive, Traffic-based Channel Allocation for Wireless Ad-hoc Networks

2 Outline Introduction Radio architecture: overview of OFDM Distributed Channel Allocation Algorithm Validation and Simulation Results

3 Wireless Backbone Wireless IP router OFDM Radio Rapidly deployable ad hoc backbone Need high capacity links between the wireless routers Limited available spectrum – need spatial reuse Wireless IP backbone Gigabit Wireless Router project with RSC – part of NGI program

4 Analogy Links  “Pipes” carrying information Thickness  Bandwidth available Due to limited spectrum, increase in the thickness of one pipe comes at the cost of a decrease in the thickness of some other. Modulation schemes like OFDM allow us to modify the thickness of a pipe.

5 Radio Architecture: OFDM N-IFFT Front-end Frequency ff N tones Time N samples N.fN.f 1 OFDM: Orthogonal Frequency Division Multiplexing N tightly spaced subcarriers Each tone is modulated individually Digital multiplexing using an IFFT

6 OFDM (contd.) Modulate Demodulate Sub channels The wireless channel is heavily frequency selective. OFDM is composed of multiple narrow contiguous subcarriers. Each subcarrier experiences only a part of the channel (subchannel). OFDM effectively deals with multi- path effects. Becoming increasingly popular: Cisco, Rockwell Science Center, Iospan Wireless (formerly Gigabit Wireless), Malibu Networks etc.

7 Problem Statement Two orthogonal issues What channels to assign? How to assign? Constraints: Limited spectrum Spatial reuse of spectrum permitted Subchannels have to be contiguous We present a distributed algorithm to perform channel allocation under these constraints.

8 Example Spatial reuse is NOT permitted in any three link chain. Each link has a pre-specified bandwidth requirement

9 First level of clustering Lowest ID clustering algorithm [Lin & Gerla] Ordinary nodeClusterhead

10 Second level of clustering Master

11 Polling Each Master polls its clusterheads, granting them permission to allocate frequencies

12 Polling (contd.) Each clusterhead assigns frequencies to its links LinkRequirementAssigned

13 Algorithm Combines the features of clustering and polling 1.Organize into clusters based on lowest ID 2.Organize the clusters into super-clusters (Each super-cluster can allocate frequencies in parallel) 3.Master assigns channels to its ordinary neighbors 4.Master polls each clusterhead, asking it to allocate channels within its cluster, given the allocation restrictions. 5.The clusterhead allocates contiguous sub-channels to its links and when done, returns an acknowledgement to the master along with the allotted sub- channels.

14 Simulations Simulated using PARSEC Measures of performance Scalability in terms of protocol messages Comparison with optimal assignment (graph-theoretic approach) Simulation parameters Number of nodes Connectivity of network

15 Scalability

16 Comparison

17 Conclusions Presented a distributed algorithm for contiguous channel allocation in wireless ad hoc networks Validated through PARSEC simulations Future work Incorporate traffic-based adaptation into the scheme Possible application As a wireless ad hoc backbone in the MINUTEMAN project!