Building an adaptive multimedia system using the utility model

Chen, Lei; Khan, Shahadat; Li, Kin F.; Manning, Eric G.

doi:10.1007/bfb0097911

Cited by 15 publications

(7 citation statements)

References 2 publications

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“…Similarly, the increment Δ , * → to the Lagrange multiplier of the radio constraint can be computed as: (29) [25], the user * and candidate BS * causing the least increase of the corresponding multiplier is chosen for exchange (lines [19][20][21][22][23][24][25] as this choice minimizes the gap between the optimal solution characterized by (26) and the new assignment solution obtained at this point. However, if the multiplier increase is just computed as the equality as done in [25], important convergence problems arise since users tend to have the same weighted utility towards multiple BSs.…”

Section: B Description Of the Algorithmmentioning

confidence: 99%

“…The formulated optimization problem is based on utility and resource cost concepts, which have been widely used to develop resource allocation algorithms [19]. The second contribution is the mapping, after some practical considerations, of the BS assignment problem to a Multiple-Choice Multidimensional Knapsack Problem (MMKP), a well-known NP-hard combinatorial optimization problem arisen in many practical and real life problems [20], [21]. Motivated by the need to obtain suboptimal solutions with polynomial time complexity, the third contribution is the derivation of a heuristic backhaulaware BS assignment algorithm along with its performance comparison respect to classical schemes entirely based on radio conditions.…”

Section: B Our Contributionsmentioning

confidence: 99%

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Design and Evaluation of a Backhaul-Aware Base Station Assignment Algorithm for OFDMA-Based Cellular Networks

Galeana-Zapién

Ferrús

2010

IEEE Trans. Wireless Commun.

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Existing base station (BS) assignment methods in cellular networks are mainly driven by radio criteria since it is assumed that the only limiting resource factor is on the air interface. However, as enhanced air interfaces have been deployed, and mobile data and multimedia traffic increases, a growing concern is that the backhaul of the cellular network can become the bottleneck in certain deployment scenarios. In this paper, we extend the BS assignment problem to cope with possible backhaul congestion situations. A backhaul-aware BS assignment problem is modeled as an optimization problem using a utility-based framework, imposing constraints on both radio and backhaul resources, and mapped into a Multiple-Choice Multidimensional Knapsack Problem (MMKP). A novel heuristic BS assignment algorithm with polynomial time is formulated, evaluated and compared to classical schemes based exclusively on radio conditions. Simulation results demonstrate that the proposed algorithm can provide the same system capacity with less backhaul resources so that, under backhaul bottleneck situations, a better overall network performance is effectively achieved.Index Terms-BS assignment algorithms, mobile backhaul, OFDMA, radio resource management.

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Section: B Description Of the Algorithmmentioning

confidence: 99%

Section: B Our Contributionsmentioning

confidence: 99%

Design and Evaluation of a Backhaul-Aware Base Station Assignment Algorithm for OFDMA-Based Cellular Networks

Galeana-Zapién

Ferrús

2010

IEEE Trans. Wireless Commun.

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“…In our problem several items of the same type can be chosen, depending on the combination and subcombination patterns. MMKP is NP-hard, so it would not be efficient to apply an exact method to solve it, especially for a real-time decision making application (Chen et al, 1999). Recent heuristic approaches use various techniques, such as Local Search (Hifi et al, 2004;Hifi et al, 2006), Tabu Search and Ant Colony Optimization (Lau and Lim, 2004), or reductions of the search space (Akbar et al, 2006), etc.…”

Section: Links With Other Optimization Problemsmentioning

confidence: 99%

TOURISM-KM - A Variant of MMKP Applied to the Tourism Domain

2012

Proceedings of the 1st International Conference on Operations Research and Enterprise Systems

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Abstract:We are interested in an original real-world problem coming from tourism field. We describe a modelling of the problem and propose a first approach that mixes knowledge management and operational research methods. Our algorithms have been implemented in order to produce tourism solutions that are not unique for a given request but that take into account the preferences of the tourist user and provide a personalized solution. We report computational results obtained on real-world instances.

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“…MMKP is an N P-hard optimization problem (as a generalization of the single Knapsack Problem KP) which models many practical and real life problems. We cite the problem of quality adaptation and admission control for interactive multimedia systems (Chen et al, 1999), or service level agreement management in telecommunication networks problems (Watson, 2001). In the MMKP, we are given a set N of items divided into n classes J i , where each class J i , i = 1, .…”

Section: Introductionmentioning

confidence: 99%

A best first search exact algorithm for the Multiple-choice Multidimensional Knapsack Problem

Sbihi

2006

J Comb Optim

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In this paper, we propose an optimal algorithm for the Multiple-choice Multidimensional Knapsack Problem MMKP. The main principle of the approach is twofold: (i) to generate an initial feasible solution as a starting lower bound, and (ii) at different levels of the search tree to determine an intermediate upper bound obtained by solving an auxiliary problem called MMKP aux and perform the strategy of fixing items during the exploration. The approach which we develop is of best-first search strategy. The method was able to optimally solve the MMKP. The performance of the exact algorithm is evaluated on a set of small and medium instances, some of them are extracted from the literature and others are randomly generated. This algorithm is parallelizable and it is one of its important feature.

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Building an adaptive multimedia system using the utility model

Cited by 15 publications

References 2 publications

Design and Evaluation of a Backhaul-Aware Base Station Assignment Algorithm for OFDMA-Based Cellular Networks

Design and Evaluation of a Backhaul-Aware Base Station Assignment Algorithm for OFDMA-Based Cellular Networks

TOURISM-KM - A Variant of MMKP Applied to the Tourism Domain

A best first search exact algorithm for the Multiple-choice Multidimensional Knapsack Problem

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