A Self-Managed Distributed Channel Selection Algorithm for WLANs

Leith, Douglas J.; Clifford, Peter

doi:10.1109/wiopt.2006.1666484

Cited by 86 publications

(73 citation statements)

References 21 publications

(25 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here we propose a decentralised Learning MAC (L-MAC), which can be regarded as an evolution of L-BEB [2] incorporating ideas from the self-managed decentralised channel selection algorithm in [3]. The primary difference between L-MAC and L-BEB is that in L-BEB collisions cause memory to be lost of the current schedule.…”

Section: The L-mac Protocolmentioning

confidence: 99%

Decentralised learning MACs for collision-free access in WLANs

et al. 2012

View full text Add to dashboard Cite

Abstract-By combining the features of CSMA and TDMA, fully decentralised WLAN MAC schemes have recently been proposed that converge to collision-free schedules. In this paper we describe a MAC with optimal long-run throughput that is almost decentralised. We then design two schemes that are practically realisable, decentralised approximations of this optimal scheme and operate with different amounts of sensing information. We achieve this by (1) introducing learning algorithms that can substantially speed up convergence to collision free operation; (2) developing a decentralised schedule length adaptation scheme that provides long-run fair (uniform) access to the medium while maintaining collision-free access for arbitrary numbers of stations.

show abstract

Section: The L-mac Protocolmentioning

confidence: 99%

Decentralised learning MACs for collision-free access in WLANs

et al. 2012

View full text Add to dashboard Cite

show abstract

“…The channel assignment problem was initially addressed in the work of Kaufmann, Baccelli, Chaintreau, Papagiannaki, and Diot (2005) and more recently by Leith and Clifford (2006) and Mishra, Shrivastava, Agarwal, Banerjee and Ganguly (2006). These references consider the problem of interference in an 802.11 based infrastructure networks when collocated networks are owned by different entities and there is no wireless connectivity present between them.…”

Section: Related Workmentioning

confidence: 99%

A topology control-based self-organisation in wireless mesh networks

Prodan

Mirchandani

Debenham

2008

IJCNDS

View full text Add to dashboard Cite

Abstract:An algorithm for self-organisation that assigns the channels intelligently in Multi-Radio Wireless Mesh Networks (MR-WMN) is important for the proper operation of MR-WMN. The aim of the self-organisation algorithm is to reduce the overall interference and increase the aggregate capacity of the network. In this paper, we have first proposed a generic selforganisation algorithm that addresses these two challenges. The basic approach is that of a distributed, light-weight, co-operative multiagent system that guarantees scalability. Second, we have evaluated the performance of the proposed self-organisation algorithm for two sets of initialisation schemes. The initialisation process results in a topology control of MR-WMN by way of spatial distribution of connectivity between the mesh nodes. The results have been obtained for realistic scenarios of MR-WMN node densities and topologies. We have shown further the need to develop non-transmit power control based algorithms to achieve a further increase in system capacity.

show abstract

“…We find that this estimator appears to be somewhat less accurate than the idle/busy estimator, probably due to physical layer capture effects, but that it is nevertheless effective and practical. In future work we intend to use these estimators to support decision making in algorithms for channel allocation [1], rate adaptation [2], [4], carrier-sense adaption, etc.…”

Section: Convergence Rate Of Estimatesmentioning

confidence: 99%

Experimental assessment of 802.11 MAC layer channel estimators

et al. 2007

Self Cite

View full text Add to dashboard Cite

Abstract-We evaluate two approaches for estimating the proportions of frame losses at an 802.11 station due to collisions and interference. These methods use only local 802.11 measurements available in basic access mode. We implement the estimators on an experimental testbed using off-the-shelf hardware to investigate implementation requirements and to evaluate performance in real wireless environments. We find that the estimators are accurate and of potential practical utility. I. INTRODUCTIONThe CSMA/CA medium access mechanism of 802.11 makes estimation of channel quality challenging as frame loss due to collisions is a feature of normal operation. Importantly, the level of collision-induced loss is load dependent. The problem is how to disentangle collisions and losses due to channel impairment. Most work on channel quality estimation has focused on PHY layer approaches based on SNR and RSSI, but it is known that the correlation between these and channel behaviour may be weak. Motivated by this, in [3] the authors propose a cross-layer approach. A related technique is suggested in [5] for estimating the number of active stations. While [3], [5] test their proposals by simulation, they do not carry out an experimental validation. In view of the complex nature of the radio interference environment, and the limited accuracy of available channel models, we argue that it is vital to evaluate the performance of these schemes on real hardware.The contributions of this paper are twofold. First, we demonstrate the practicality of the estimator proposed in [3] by implementing it in a hardware testbed via driver and firmware modifications. We evaluate the performance of the estimator in real radio environments. To our knowledge, these are the first reported experimental measurements for this class of estimators and they confirm the promising nature of the approach. Second, we present an alternative technique for estimating the frame error rate due to radio interference that complements the first estimator. This makes use of information on frame status which is available in off-the-shelf network cards, but which is not yet widely utilised.

show abstract

A Self-Managed Distributed Channel Selection Algorithm for WLANs

Cited by 86 publications

References 21 publications

Decentralised learning MACs for collision-free access in WLANs

Decentralised learning MACs for collision-free access in WLANs

A topology control-based self-organisation in wireless mesh networks

Experimental assessment of 802.11 MAC layer channel estimators

Contact Info

Product

Resources

About