Load balancing and adaptive scheduling for data intensive prioritised traffic in multi-radio multi-channel wireless mesh networks

Kumar, Neeraj; Chilamkurti, Naveen; Park, Jong Hyouk; Park, Doo Soon

doi:10.1504/ijahuc.2013.051377

Cited by 4 publications

(1 citation statement)

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“…However, most of the previous joint problems for WMNs were associated with only two of the three concerns, and hence this paper further investigates the joint problem of routing, scheduling, and channel allocation (RSC for short) to address the network scenario more realistically. Another important issue on WMNs is the influence of signal interference on network performance, which can be lessened by using multiple radios and multiple orthogonal channels; for example, see [ 8 , 9 ]. A recent work in [ 10 ] has proposed a software technique with very little overhead that can dynamically adapt the widths of multiple channels at different times so as to attain more concurrent transmissions and reduce signal interference under limited resource of wireless spectrum.…”

Section: Introductionmentioning

confidence: 99%

A Novel Joint Problem of Routing, Scheduling, and Variable-Width Channel Allocation in WMNs

Lin

Liu

Chou³

et al. 2014

The Scientific World Journal

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This paper investigates a novel joint problem of routing, scheduling, and channel allocation for single-radio multichannel wireless mesh networks in which multiple channel widths can be adjusted dynamically through a new software technology so that more concurrent transmissions and suppressed overlapping channel interference can be achieved. Although the previous works have studied this joint problem, their linear programming models for the problem were not incorporated with some delicate constraints. As a result, this paper first constructs a linear programming model with more practical concerns and then proposes a simulated annealing approach with a novel encoding mechanism, in which the configurations of multiple time slots are devised to characterize the dynamic transmission process. Experimental results show that our approach can find the same or similar solutions as the optimal solutions for smaller-scale problems and can efficiently find good-quality solutions for a variety of larger-scale problems.

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Section: Introductionmentioning

confidence: 99%