A fast and simple randomized parallel algorithm for maximal matching
Information Processing Letters
An approximation algorithm for the generalized assignment problem
Mathematical Programming: Series A and B
A PTAS for the multiple knapsack problem
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Distributed computing: a locality-sensitive approach
Distributed computing: a locality-sensitive approach
A unified approach to approximating resource allocation and scheduling
Journal of the ACM (JACM)
Proceedings of the 10th annual international conference on Mobile computing and networking
An efficient approximation for the generalized assignment problem
Information Processing Letters
Improved distributed approximate matching
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures
Coping with interference: from maximum coverage to planning cellular networks
WAOA'06 Proceedings of the 4th international conference on Approximation and Online Algorithms
IEEE Journal on Selected Areas in Communications
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We consider the following model of cellular networks. Each base station has a given finite capacity, and each client has some demand and profit. A client can be covered by a specific subset of the base stations, and its profit is obtained only if its demand is provided in full. The goal is to assign clients to base stations, so that the overall profit is maximized subject to base station capacity constraints. In this work we present a distributed algorithm for the problem, that runs in polylogarithmic time, and guarantees an approximation ratio close to the best known ratio achievable by a centralized algorithm.