IEEE 802.11 MR-MC WMN的QoS路由与多信道协同策略

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本文主要探讨了IEEE 802.11多无线电多信道（MR-MC）无线网状网络（Wireless Mesh Networks, WMNs）中的有效联合信道分配和质量-of-Service (QoS) 路由协议设计。随着视频、VoIP等实时多媒体服务的兴起，对带宽、延迟和抖动等QoS因素的关注度日益提升。对于作为宽带无线接入的有效手段，WMNs提供QoS保障的需求变得至关重要。当前的研究工作大多针对专为Ad-hoc或传感器网络设计的QoS架构进行改进，侧重于单无线电和单一信道的情况。然而，这些研究通常从各自独立的层面上分别处理QoS路由或介质访问控制（Medium Access Control, MAC）问题。本文提出了一种创新的方法，旨在克服这些局限性，实现多无线电和多信道环境下的QoS路由协议，以促进WMNs的整体性能优化。该论文的核心贡献在于提出了一种跨层（Cross-layer）的设计策略，它将网络层、MAC层以及物理层（PHY层）的信息融合在一起，以动态调整信道分配和路由决策。通过这种方式，协议能够更好地平衡网络流量、减少竞争，同时满足不同业务流的QoS需求。具体来说，可能包括： 1. **联合信道分配**：协议采用自适应策略，根据网络负载、信号强度和信道干扰情况，动态选择合适的无线电和信道组合，以最大化网络容量并最小化干扰。 2. **QoS路由算法**：考虑到实时服务的特性，设计了一种基于优先级的QoS路由算法，结合带宽预留、延迟约束和丢包容忍度等因素，确保关键业务流得到优先处理。 3. **跨层优化**：协议利用多源信息（如链路质量、节点状态）进行决策，避免了传统层间通信的瓶颈，提高了整体系统效率。 4. **协议实现与性能评估**：论文提供了详细的算法描述和仿真验证，展示其在实际网络环境中的性能优势，包括吞吐量、延迟和丢包率等关键指标的改善。总结，这篇研究论文针对IEEE 802.11 MR-MC WMNs的挑战，提出了一个创新的解决方案，旨在提升网络的QoS性能，适应未来实时服务的需求。通过跨层设计，该协议有望成为无线网状网络发展中的一个重要里程碑，推动了宽带无线接入技术的进一步优化。

Kodialam and Lakshman, 2000; Suri et al., 2003; Ricciato and

Monaco, 2005). In these literatures, the common solution is to

ﬁnd a feasible path on the constructed topology by removing all

links that do not meet the bandwidth requirement. Although this

method could work well in wired model, it is not applicable in

wireless multi-hop networks due to interference.

In the past few years, a lot of research efforts have been made

on QoS guarantee issues in wireless multi-hop networks. Some of

them (e.g., Lin and Liu, 1999; Hanzo-II and Tafazolli, 2007; Chiu

et al., 2009; Khoukhi and Cherkaoui, 2010; Hanzo-II and Tafazolli,

2011; Kajioka et al., 2011) have been especially dedicated for

mobile ad hoc networks (MANET). In Lin and Liu (1999), the paper

proposed a bandwidth-based routing protocol for QoS support in

multi-hop mobile network, by which the source was informed of

the bandwidth and QoS available to any destination. In Hanzo-II

and Tafazolli (2007), the authors offered a survey QoS routing

solutions for MANETs published in the period 1997–2006. This

article provided the academic with insight into the differences

and allowed them to highlight trends in protocol design and

identify areas for future research. In Chiu et al. (2009), the authors

introduced an efﬁcient distributed joint channel assignment and

routing protocol in multi-channel multi-radio ad hoc networks,

which allowed a data interface to dynamically change its working

mode on a call-by-call basis. In Khoukhi and Cherkaoui (2010),

Khoukhi et al. proposed a new intelligent cross-layer QoS scheme

for MANETs. The solution adopted fuzzy logic for improving trafﬁc

regulation and the control of congestion to support both real-time

multimedia (audio/video) services and non-real-time trafﬁc ser-

vices. Lajos Hanzo et al. designed a QoS-aware routing protocol

and admission control mechanism in shadow-fading environ-

ments for Multi-rate MANETs in Hanzo-II and Tafazolli (2011),

which could enhance system performance in situation of mobi-

lity, shadowing, and varying SINR. In Kajioka et al. (2011), the

authors proposed a new QoS-aware routing protocol to support

real-time multimedia communication by efﬁciently exploiting the

limited wireless network capacity in MANETs.

In addition, there are also some research papers (Cobo et al.,

2010; Kandris et al., 2011; Lin et al., 2011) aiming to solving QoS

issues in the ﬁeld of wireless sensor networks (WSNs). In Cobo

et al. (2010), Cobo et al. built a hierarchical structure on the

network before choosing suitable routes to meet various QoS

requirements, thus maximizing network utilization. In Kandris

et al. (2011), the article proposed a novel scheme for video

communication, which incorporated an energy aware hierarchical

routing protocol with an intelligent video packet scheduling

algorithm to achieve energy saving and high QoS attainment. In

Lin et al. (2011), the literature systemically analyzed the similar-

ity between social network and wireless multimedia sensor net-

work (WMSN), and designed a QoS trust estimation model based

on social network analysis. Furthermore, it proposed an energy

efﬁcient QoS assurance routing based on cluster hierarchy to

achieve energy efﬁciency and meet the QoS requirement.

However, the above QoS guarantee mechanisms dedicated for

MANETs and WSNs are not very effective and efﬁcient in WMNs.

The designing baseline of QoS routing in MANETs is to deal with

the mobility of nodes and availability of routing satisfying some

weight measures, while the main point of designing QoS control

mechanism for WSNs is to consider both the energy efﬁciency

constrain of node characteristic and QoS guarantee for real-time

trafﬁc. As a contrast, the mesh backbone has static topology,

meanwhile mesh nodes without power limit are often plug in.

Therefore the focus of QoS routing designing in WMNs is on how

to offer high-speed broadband services to maximize throughput

capacity of networks with QoS assurance.

In recent years, there are also some exploration literatures for

QoS routing in WMNs. In Ergin et al. (2008), the article presented

an integrated admission control and routing mechanism for

multi-rate WMNs. The authors also introduced a packet

probing-based bandwidth estimation method, suitable for legacy

device implementations, and veriﬁed it experimentally. In Liu and

Liao (2009), Liu et al. proposed an on-demand bandwidth-con-

strained routing protocol for multi-radio multi-rate multi-

channel WMNs with the IEEE 802.11 DCF MAC protocol. Basing

on a distributed threshold-triggered bandwidth estimation

scheme, they proposed a novel routing metric which struck a

balance between the routing cost and the path bandwidth. In

Rezgui et al. (2010), the paper introduced a distributed admission

control scheme for WMNs, and proposed an analytical model to

compute the appropriate acceptance ratio. This scheme guaran-

teed that the packet loss probability did not exceed a threshold

value. In Bakhshi and Khorsandi (2011), the paper studied the

problem of QoS provisioning in term of end-to-end bandwidth

allocation in WMNs. Then the authors proposed a k-shortest path

based algorithmic framework to solve this problem by on-line

dynamic routing. In Hou et al. (2012), Hou et al. studied the

problem of identifying the maximum available bandwidth path in

WMNs, and proved that the proposed hop-by-hop routing proto-

col could satisfy the consistency and loop-freeness requirements.

However, some of the above references need to modify MAC to

adapt these protocols and are not easy to implement, while others

do not consider integration of multiple channels to accommodate

the high volume trafﬁc of real-time multimedia applications.

Contrary to those mentioned mechanisms, our protocol intro-

duces cross-layer idea and multi-radio multi-channel technique

over 802.11 MAC, thus overcomes the disadvantages and has

good adaptability.

3. System model

We consider the multi-radio multi-channel WMNs with the

IEEE 802.11 DCF MAC protocol. In our model, there are N nodes

which are all stationary and act as trafﬁc aggregation access

points, providing network connectivity to mobile end-users

within their coverage ranges. Packets are forwarded via multi-

hop relaying manner. Each node i is equipped with R

hetero-

geneous radios, and the number of radios on each node may be

different. By heterogeneous radios, we mean that the wireless

capability, power level, and working spectrum, etc., on these

radios may be different. Each radio serves as a transmitter or a

receiver on a channel at any given time, i.e., half duplex mode. We

assume that there are a total of L orthogonal channels in the

system, numbered CH

, CH

,y,CH

, exhibiting no inter-channel

interference. For the sake of efﬁciency, all radios of each node are

tuned to non-overlapping channels. We consider a random trafﬁc

model and adopt dynamic channel assignment strategy, which

assigns the radio with the best channel greedily in neighboring

areas. Two nodes are said to be neighbors on channel k if they

both have a radio operating on the common channel k and

simultaneously fall within the transmission range of each other.

The multi-rate capability in the physical layer is also taken into

account in our model, i.e., nodes in the network may commu-

nicate at different data rates, depending on the distance between

them, the radio signal quality, and the set of modulation and

coding schemes available in the system. Note that here we can

use radio and interface alternatively without confusion through-

out this article. Without loss of generality, we number radios and

channels from 0 to R

1. When network initializes, we need to

assign identiﬁcations for radios and channels. For simplicity, the

assignment method is the same among all nodes: channel 0

is assigned to match radio 0, channel 1 is assigned to match

radio 1 and so on. In our proposal, one channel numbered 0, called

Y. Peng et al. / Journal of Network and Computer Applications 36 (2013) 843–857 845

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