Distributive online channel assignment for hexagonal cellular networks with constraints

Fitzpatrick, Shannon L.; Janssen, Jeannette; Nowakowski, Richard J.

doi:10.1016/j.dam.2003.06.005

Cited by 8 publications

(7 citation statements)

References 12 publications

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“…This special case has been studied in the case of frequency assignment problems (see e.g. [9,12,16,20,23,24]). A communication request r is speciÿed by the point p r of the two-dimensional space where the request arises and the bandwidth b r required by the request.…”

Section: From Channel Assignment To Load Balancingmentioning

confidence: 99%

“…Moreover, only the "unweighted" restriction of the problem is considered, i.e., the case in which each user can request only a globally ÿxed resource (bandwidth or frequency). The on-line frequency assignment problem 2 has been the subject of several works (see for instance [9,12,16,20]). This problem consists of assigning frequencies to users so that interference constraints are satisÿed (e.g., two users within adjacent cells cannot use the same frequency).…”

Section: Introductionmentioning

confidence: 99%

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On-line algorithms for the channel assignment problem in cellular networks

Crescenzi

Gambosi

Penna

2004

Discrete Applied Mathematics

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We consider the on-line channel assignment problem in the case of cellular networks and we formalize this problem as an on-line load balancing problem for temporary tasks with restricted assignment. For the latter problem, we provide a general solution (denoted as the cluster algorithm) and we characterize its competitive ratio in terms of the combinatorial properties of the graph representing the network. We then compare the cluster algorithm with the greedy one when applied to the channel assignment problem: it turns out that the competitive ratio of the cluster algorithm is strictly better than the competitive ratio of the greedy algorithm. The cluster method is general enough to be applied to other on-line load balancing problems and, for some topologies, it can be proved to be optimal. (C) 2003 Elsevier B.V. All rights reserved

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Section: From Channel Assignment To Load Balancingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On-line algorithms for the channel assignment problem in cellular networks

Crescenzi

Gambosi

Penna

2004

Discrete Applied Mathematics

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“…Online channel assignment has been studied for cellular networks [5], [6] and in monitoring wireless networks [7] where the goal is to maximize the amount of traffic captured by sniffers in the network.…”

Section: Related Workmentioning

confidence: 99%

Distributed dynamic channel assignment in wireless networks

Kari

Shashidhar

Kentros

2014

2014 International Conference on Computing, Networking and Communications (ICNC)

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This paper studies the online channel assignment problem arising in dynamic wireless networks. The goal is to assign channels to communication links such that interference (or the number of conflicts) in the network is minimized. We model the problem as an online edge coloring problem. This problem is NP-hard by a reduction from EDGE COLORING. We present an online distributed greedy algorithm that gives a solution with at most 2(1 1 k )|E| more conflicts than the optimal solution, which implies a (2 1 k )-approximation. We then show that this ratio is tight by proving a lower bound that matches the above ratio.

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“…Let us consider a call sequence σ 1 = (8, 1, 6, 10, 8,4,8,19,6,8,13,11). To apply the algorithm HYBRID , we first partition the frequencies into the following sets: …”

Section: Frequency Assignment Schemementioning

confidence: 99%

Absolute and Asymptotic Bounds for Online Frequency Allocation in Cellular Networks

Chan

Chin

et al. 2009

Algorithmica

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Given a cellular (mobile telephone) network, whose geographical coverage area is divided into hexagonal cells, phone calls are serviced by assigning frequencies to them so that no two calls emanating from the same or neighboring cells are assigned the same frequency. Assuming an online arrival of calls, the goal is to minimize the span of frequencies used to serve all of the calls.By first considering χ-colorable networks, which is a generalization of the (3-colorable) cellular networks, we present a (χ + 1)/2-competitive online algorithm. This algorithm, when applied to cellular networks, is effectively a positive solution to the open problem posed in (Caragiannis et al. in Theory Comput. Syst. 35(5):521-543, 2002) Does a 2-competitive online algorithm exist for frequency allocation in cellular networks? We further prove a matching lower bound, which shows that our 2-competitive algorithm is optimal. Algorithmica (2010) 58: 498-515 499 We discover that an interesting phenomenon occurs for the online frequency allocation problem when the number of calls considered becomes large: previouslyderived optimal bounds on competitive ratios no longer hold true. For cellular networks, we show a new asymptotic lower and upper bounds of 1.5 and 1.9126, respectively, which breaks through the optimal bound of 2 shown above.

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Distributive online channel assignment for hexagonal cellular networks with constraints

Cited by 8 publications

References 12 publications

On-line algorithms for the channel assignment problem in cellular networks

On-line algorithms for the channel assignment problem in cellular networks

Distributed dynamic channel assignment in wireless networks

Absolute and Asymptotic Bounds for Online Frequency Allocation in Cellular Networks

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