1 Multicast Algorithms for Multi- Channel Wireless Mesh Networks Guokai Zeng, Bo Wang, Yong Ding, Li...

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Multicast Algorithms for Multi-Channel Wireless Mesh Networks

Guokai Zeng, Bo Wang, Yong Ding, Li Xiao, Matt Mutka

Michigan State UniversityICNP 2007

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Outline Introduction System Model Level Channel Assignment

Algorithm Multi-Channel Multicast Algorithm Simulations Conclusion & Comment

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Introduction Efficient multicast protocols in WMNs cannot be

achieved by slightly modifying the multicast protocols for other multi-hop wireless networks. Route recovery or energy efficiency is not the major co

ncern for WMN. We aim to design a multicast protocol that has th

e following characteristics: It improves the system throughput by allowing simult

aneous close-by transmissions with multi-channel. It assigns all the available channels to the interfaces in

stead of just the non-overlapping channels.

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Introduction We propose Level Channel Assignment (LCA)

and Multi-Channel Multicast (MCM) algorithms to optimize throughput.

The algorithms build a multicast structure by minimizing the

number of relay nodes and hop count distances between source and destination and

use dedicated channel assignment strategies to improve the network capacity.

We also illustrate that the use of partially overlapping channels can further improve the throughput.

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A. Basics G = (V, E),

V is the set of gateways and mesh routers E is the physical links.

Each node has the same fixed communication range R.

Each node is able to be equipped with k NICs. In this paper, k=2

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B. Measuring Partial Overlap Previous channel assignment algorithms for

802.11b/g only use three non-overlapping channels.

However, the interference can be further reduced by using the partially overlapping channels too i.e. by using any channel from 1 to 11.

The interference between two links depends on both their physical distance and channel separation [17].

[17] A. Mishra, E. Rozner, S. Banerjee, and W. Arbaugh. Exploiting partially overlapping channels in wireless networks: Turning a peril into an advantage. In ACM/USENIX Internet Measurement Conference, 2005.

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B. Measuring Partial Overlap Ic: the interference range of two links with chann

el separation c. ex. I0 = 2R

We evaluated the interference between two links by comparing the total throughput when both links are active and the sum of each link’s throughput when the other li

nk is turned down.

Interference range decreases with the increase of channel separation.

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Level Channel Assignment Algorithm

Based on BFS, all the nodes are partitioned into different levels according to the hop count distances

between the source and the nodes. Second, we build a multicast tree based

on the node level information. Algorithm 1 gives the detail.

Next, the tree nodes decide their channel assignment with the level information.

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Level Channel Assignment Algorithm

Pro: Simple implementation and throughput improvement.

Con: LCA cannot diminish the interference among the same

levels. When the # of available channels is more than that of

the levels, some channels will not be utilized. The channel assignment does not take the overlap

property of the two adjacent channels into account.

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Multicast Structure Construction

We aim for a multicast protocol for WMNs, which includes two primary procedures: build an effective multicast structure, and tries to allocate channels for minimizing interference.

We can say that broadcast is a special case of multicast. We first consider the situation that all the nodes are t

he multi-receivers. We then detail how to trim those unnecessary branc

hes when the multi-receivers are only a portion of nodes.

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Broadcast Structure The first step is realized by BFS and all the

nodes are divided into different levels. We then delete the edges between any two

nodes of the same level, with which we get the elementary

communication structure “tree mesh”. Why use BFS:

Shorter hop count distance means shorter transmission delay.

If two nodes are not at the same level or the adjacent levels, they are at least two hops away.

The time complexity is O(|V| + |E|).

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Broadcast Structure In the second step, we identify the minimal

number of relay nodes that form the broadcast tree.

A top-down approach is used to identify the relay nodes. Our objective is to identify the minimal number

of relay nodes in level i that can communication with all the nodes in level i+1.

It is a variation of the set-cover problem, which has been proved NP-complete.

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Multicast Structure We propose to construct a “slim”

structure by using algorithm 3. The search process starts from the

bottom to the top. At each step, we intend to minimize

the number of relay nodes at the upper level, which can cover all the multi-receivers

and relay nodes at the lower level.

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B. Channel Assignment Ascending Channel Allocation.

From top to down, the channels are assigned to the interfaces in the ascending order

until the maximum channel number is reached, then start from channel 0 again.

This approach avoids the situation where the same channel is assigned to two nearby links that interfere with each other.

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Heuristic Channel Assignment

We can utilize all the channels instead of just orthogonal channels.

We aim to minimize the sum of the interference area of all the transmissions.

IR(uv) = R * δ|iu-iv| the interference range of sender u of one link with re

spect to sender v of another link. u and v use channel iu and iv for their SIs respectively.

The channel assignment should take a channel that minimizes the sum of square of the IRs between relay node u and u’s neighboring relay nodes.

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Simulations We evaluate MCM, LCA, and single channel

multicast algorithms through the following metrics.

Throughput: the average number of packets each receivers receives.

Delay: the average time it takes for a packet to reach the destination.

We use NS2 (2.29) to simulate a flat area of 900m by 900m with varying number of randomly positioned wireless router nodes.

Transmission range: 250m. Carrier sense range: 550m. Use base rate 1Mbps.

Except for the last subsection, we use the orthogonal channels.

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Simulations A. Impact of Network Size (Figure 7)

# of available channels is 12. MCM builds a more efficient multicast tree and

carefully assigns the channels on the tree. B. Impact of Number of Available Channels

(Figure 8) From channel 2 to 6, both have great throughput

improvement. When the # of channels increases to a certain

extent, it is enough to eliminate almost all the interferences.

The # of channels that LCA uses is equal to the tree height, thus some channels are left unused.

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Simulations C. Impact of Transmission Rate (Figure 9)

The saturated rates for MCM and LCA are 225 and 125 packets/s.

D. Delay Comparison (Figure 10) The transmission rate is set to 200 packets/s. When # of available channels is

6, it just diminishes some interferences. 12, it can greatly diminish interference.

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Simulations E. Partially Overlapping Channel

Assignment Test (Figure 11) We choose two frequency spectrums:

30MHz, which can offer 2 orthogonal channels and 6 partially overlapping channels, and

60MHz, which can offer 3 orthogonal channels and 12 partially overlapping channels.

Using partially overlapping channels can achieve better throughput than using just orthogonal channels.

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Conclusion in order to achieve efficient multicast in WMNs,

two multicast algorithms, LCA and MCM, are proposed.

An effective multicast structure is constructed to minimize the number of relay nodes and the communication delay.

The dedicated channel assignment helps to further minimize the interference as well.

The performance evaluation shows that our algorithms outperform the single-channel multicast in terms of throughput and delay.

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Comments

Since MCM is better than LCA, they should focus on MCM and provide more results on using partially overlapping channels.

The paper only compared their own algorithms in the performance evaluation. No comparison with other peer

mechanisms.

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