We consider the problem of fair rate control for wireless ad-hoc networks with time varying channel capacities. The interaction between links in wireless ad-hoc networks introduces additional constraints on the flow r...
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We consider the problem of fair rate control for wireless ad-hoc networks with time varying channel capacities. The interaction between links in wireless ad-hoc networks introduces additional constraints on the flow rate. A primal-dual algorithm that guarantees fair rate control is proved to be trajectory stable. Various fairness indexes are obtained by choosing the specified form of the utility functions, and the numerical results validate the effectiveness of the proposed algorithm.
The margin maximization problem in digital subscriber line（DSL） systems is *** particle swarm optimization（PSO） theory is applied to the nonconvex margin optimization problem with the target power and rate *** is ...
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The margin maximization problem in digital subscriber line（DSL） systems is *** particle swarm optimization（PSO） theory is applied to the nonconvex margin optimization problem with the target power and rate *** is a new evolution algorithm based on the social behavior of swarms, which can solve discontinuous, nonconvex and nonlinear problems *** proposed algorithm can converge to the global optimal solution, and numerical example demonstrates that the proposed algorithm can guarantee the fast convergence within a few iterations.
In clustering algorithm of wireless sensor networks, to solve the problem of excessive energy consumption in the cluster heads, an residual energy and node degree synthesized clustering algorithm named ENCA (energy an...
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The margin maximization problem in digital subscriber line(DSL) systems is *** particle swarm optimization(PSO) theory is applied to the nonconvex margin optimization problem with the target power and rate *** is a ne...
详细信息
The margin maximization problem in digital subscriber line(DSL) systems is *** particle swarm optimization(PSO) theory is applied to the nonconvex margin optimization problem with the target power and rate *** is a new evolution algorithm based on the social behavior of swarms, which can solve discontinuous, nonconvex and nonlinear problems *** proposed algorithm can converge to the global optimal solution, and numerical example demonstrates that the proposed algorithm can guarantee the fast convergence within a few iterations.
We consider the distributed random access algorithms for wireless ad hoc networks in which each node needs to tune its persistent probability so as to optimize its own the total throughput. First, we present an asynch...
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We consider the distributed random access algorithms for wireless ad hoc networks in which each node needs to tune its persistent probability so as to optimize its own the total throughput. First, we present an asynchronous algorithm for updating persistent probabilities and prices to avoid collision using local coordination. By casting this algorithm as a best response in a cooperative game, we characterize its convergence analytically. We further model that each node attempts to maximize a selfish local payoff function. We characterize the Nash equilibrium (NE) of the non-cooperative game and prove the convergence of a best response algorithm to the unique NE. Then we study the energy efficient throughput maximization problem when the wireless nodes are constrained by their battery power. Despite the inherent difficulty of non-separability of the constraint set, we propose a distributed primal-based algorithm. Its convergence is studied numerically
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