This paper introduces a utility-based radio resource management technique in multicell wireless packet networks. In terms of allocation of base station (BS) downlink transmit power and assignment of resource to users ...
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This paper introduces a utility-based radio resource management technique in multicell wireless packet networks. In terms of allocation of base station (BS) downlink transmit power and assignment of resource to users in each cell, we formulate a problem of maximizing system utility which is defined as the sum of cell utilities. The problem, however, is not solvable due to its non-convex property. Thus, we propose a heuristic algorithm based on an intuition obtained from analyzing a simple two-cell problem. Though the heuristic approach also incurs signaling overhead for power coordination between neighboring base stations, it is much less than that of the original approach. Simulation results show the performance of our proposed algorithm compared with two competitive schemes: optimal and maximum power allocation schemes. As expected, the optimal allocation scheme shows the best performance but can not be employed in a real network due to intractable complexity. Our heuristic algorithm performs reasonably well with very low complexity. (C) 2006 Elsevier B.V. All rights reserved.
The shared-medium multihop nature of wireless ad hoc networks poses fundamental challenges to the design of effective resource allocation algorithms that are optimal with respect to resource utilization and fair acros...
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The shared-medium multihop nature of wireless ad hoc networks poses fundamental challenges to the design of effective resource allocation algorithms that are optimal with respect to resource utilization and fair across different network flows. None of the existing resource allocation algorithms in wireless ad hoc networks have realistically considered end-to-end flows spanning multiple hops. Moreover, strategies proposed in wireline networks are not applicable in the context of wireless ad hoc networks, due to their unique characteristics of location-dependent contention. In this paper, we propose a new price-based resource allocation framework in wireless ad hoc networks to achieve optimal resource utilization and fairness among competing end-to-end flows. We build our pricing framework on the notion of maximal cliques in wireless ad hoc networks, as compared to individual links in traditional wide-area wireline networks. Based on such a price-based theoretical framework, we present a two-tier iterative algorithm. Distributed across wireless nodes, the algorithm converges to a global network optimum with respect to resource allocations. We further improve the algorithm toward asynchronous network settings and prove its convergence. Extensive simulations under a variety of network environments have been conducted to validate our theoretical claims.
Two rules of a sealed ceiling bid for a contract that a firm offering this contract can set are proposed. The rules are such that they encourage the bidders to submit their prices for the contract within a range desir...
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Two rules of a sealed ceiling bid for a contract that a firm offering this contract can set are proposed. The rules are such that they encourage the bidders to submit their prices for the contract within a range desirable by the firm so that these prices not to exceed the (unknown to the bidders) price of the bid (the ceiling). It is shown that under certain natural assumptions on the behavior of the bidders, evaluating chances of a firm to award the contract at a price within such a desirable range as a result of the bid conducted in line with the rules is reducible to solving mathematical programming problems on polyhedral sets. It is also shown that under additional assumptions of the same kind, under the proposed rules, the maximum probability to win the bid at a price within the range is higher for each bidder than that under the rule of awarding the contract to a bidder nominated the lowest price. Thus, while serving the interests of the firm, the proposed rules make the bid more attractive to the potential bidders. (c) 2006 Elsevier Ltd. All rights reserved.
An efficient steady-state compensation method and a conceptual design for sizing the three-phase three-wire shunt active power filter (APF) under nonsinusoidal source voltages are presented in this paper. Conventional...
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An efficient steady-state compensation method and a conceptual design for sizing the three-phase three-wire shunt active power filter (APF) under nonsinusoidal source voltages are presented in this paper. Conventionally, the compensation currents injected by the APF are determined to eliminate harmonic currents of the nonlinear load as well as to compensate reactive power and maintain the sinusoidal source currents. However, the subject related to the optimal control of the APF to meet the IEEE-519 harmonic current limits and other constraints, such as minimum load power factor requirement after compensation with an optimal kilovolt-ampere rating, are rarely investigated. In this paper, an optimization-based solution algorithm is proposed to determine the three-phase three-wire APF current injections to meet different constraints with an optimal filter size, where the voltage compensation-based control strategy is formulated as a nonlinear programming problem and is solved to find the optimal compensator gains and APF current injections. Results obtained by simulations with Matlab/Simulink show that the proposed approach is very flexible and effective for compensating harmonic currents generated by the nonlinear load with an optimal size of the APF.
We present a new formulation of the truss topology problem that results in unique design and unique displacements of the optimal truss. This is reached by adding an upper level to the original optimization problem and...
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We present a new formulation of the truss topology problem that results in unique design and unique displacements of the optimal truss. This is reached by adding an upper level to the original optimization problem and formulating the new problem as an MPCC (Mathematical Program with Complementarity Constraints). We derive optimality conditions for this problem and present several techniques for its numerical solution. Finally, we compare two of these technique's on a series of numerical examples.
An algorithm was developed to select an optimum model among several neural network (NN) models using the Manhattan and Euclidean metric measures. The algorithm was implemented to find an optimum NN prediction model ba...
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An algorithm was developed to select an optimum model among several neural network (NN) models using the Manhattan and Euclidean metric measures. The algorithm was implemented to find an optimum NN prediction model based on simultaneous comparison of five performance parameters. Weighted coefficients were given to each performance parameter based on their significance for specific condition. The associated weighted coefficients were optimised using two optimisation techniques: (i) genetic algorithm;and (n) linear programming. The algorithm performed satisfactorily in determining acceptable models and selecting an optimum NN model. The radial basis function NN model based on green vegetation index texture yielded an average prediction accuracy of 92(.)1% for predicting leaf nitrogen content under field conditions. (c) 2006 IAgrE. All rights reserved. Published by Elsevier Ltd.
A new steady-state approach for determining the optimal shunt active power filter (APF) reference compensation current injections to control harmonic currents generated by the nonlinear load and for reactive power com...
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A new steady-state approach for determining the optimal shunt active power filter (APF) reference compensation current injections to control harmonic currents generated by the nonlinear load and for reactive power compensation under ideal or nonideal supply voltages are presented in the paper. Conventionally, the compensation currents injected by the shunt APF are determined to eliminate harmonic currents of the load. However, when considering different APF performance indices such as minimizing source current distortion and maximizing compensated load power factor, the issues related to sizing the APF to meet IEEE-519 harmonic current limits and other constraints such as current imbalance limits and minimum load power factor requirement are rarely investigated. In the paper, a new theory of APF control in the a-b-c lreference frame is proposed to determine the APF current injections to meet different constraints with an optimal APF size, where the filter control strategy is formulated as a nonlinear programming problem and is solved to find the optimal current injections. Results obtained by simulations with Matlab/Simulink show that the proposed approach is more flexible and effective than the conventional approaches on compensating reactive power and harmonic currents of the load.
A class of optimal control problems for semilinear elliptic equations with mixed control-state constraints is considered. The existence of bounded and measurable Lagrange multipliers is proven. As a particular applica...
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A class of optimal control problems for semilinear elliptic equations with mixed control-state constraints is considered. The existence of bounded and measurable Lagrange multipliers is proven. As a particular application, the Lavrentiev-type regularization of pointwise state constraints is discussed. Here, the existence of associated regular multipliers is shown, too.
This article presents a new approach to minimize the losses in electrical power systems. This approach considers the application of the primal-dual logarithmic barrier method to voltage magnitude and tap-changing tran...
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This article presents a new approach to minimize the losses in electrical power systems. This approach considers the application of the primal-dual logarithmic barrier method to voltage magnitude and tap-changing transformer variables, and the other inequality constraints are treated by augmented Lagrangian method. The Lagrangian function aggregates all the constraints. The first-order necessary conditions are reached by Newton's method, and by updating the dual variables and penalty factors. Test results are presented to show the good performance of this approach.
This paper extends an exponential reliability growth model to determine the optimal number of test cases to be executed for various use case scenarios during the system testing of software. An example demonstrates a p...
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This paper extends an exponential reliability growth model to determine the optimal number of test cases to be executed for various use case scenarios during the system testing of software. An example demonstrates a practical application of the optimization model for system test planning.
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