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O. Yilmaz et al.<strong>Author</strong> Pro<strong>of</strong>503504505506507508509510511512513514515516517518519520521522523524525526527528529Fig. 9 Sensitivity <strong>of</strong> initial solution quality with respect to QoS constraintssolution found by <strong>the</strong> fast spillover CAC algorithm is insensitive to <strong>the</strong> solution quality <strong>of</strong><strong>the</strong> initial solution.5 Conclusion and Future WorkIn this paper we have developed and analyzed spillover-partitioning CAC for serving multipleservice classes in mobile wireless networks for revenue optimization with QoS guarantees.We comp<strong>are</strong>d <strong>the</strong> performance <strong>of</strong> spillover-partitioning CAC with existing CAC algorithmsin terms <strong>of</strong> <strong>the</strong> solution efficiency (time spent) and solution quality (revenue generated). Wepresented two versions <strong>of</strong> spillover-partitioning CAC: pure spillover-partitioning CAC thatdetermines <strong>the</strong> exact optimal solution and fast spillover-partitioning CAC that determinesa near optimal solution by using a greedy search method. Although partitioning CAC wassignifi<strong>can</strong>tly faster than all o<strong>the</strong>r algorithms, it performed poorly in terms <strong>of</strong> revenue optimization.The threshold-based and <strong>the</strong> hybrid CACs performed reasonably well in terms <strong>of</strong> solutionquality. However, <strong>the</strong>se algorithms performed poorly in solution efficiency. We showed thatboth versions <strong>of</strong> spillover-partitioning CAC <strong>are</strong> able to generate higher rewards than existingCAC algorithms while providing QoS guarantees. The 1–2% difference in solution qualityis considered signifi<strong>can</strong>t because <strong>the</strong> objective function is revenue per unit time. Moreoverboth versions <strong>are</strong> able to generate solutions with much higher search efficiency. In particular,fast spillover-partitioning CAC <strong>of</strong>fers very high solution efficiency while generating nearoptimal solutions comparable to optimal solutions found by pure spillover-partitioning orthreshold-based CAC algorithms.We also performed a sensitivity analysis <strong>of</strong> <strong>the</strong> solution quality <strong>of</strong> <strong>the</strong> initial solution foundby fast spillover CAC (relative to <strong>the</strong> upper bound) with respect to <strong>the</strong> total traffic demandand QoS constraints. We observed that <strong>the</strong> solution quality <strong>of</strong> <strong>the</strong> initial solution is relativelyinsensitive to <strong>the</strong> traffic demand. However, <strong>the</strong> initial solution quality is strongly affected byQoS constraints, exhibiting a lower solution quality when QoS constraints <strong>are</strong> less stringent.Never<strong>the</strong>less, we observed that <strong>the</strong> final solution quality is relatively insensitive to <strong>the</strong> initialsolution quality found by fast spillover CAC over a wide range <strong>of</strong> traffic demands and QoSuncorrected pro<strong>of</strong>123Journal: 11277 MS: WIRE823 CMS: 11277_2009_9673_Article TYPESET DISK LE CP Disp.:2009/2/19 Pages: 21 Layout: Small

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