Max-Min Fair Resource Allocation in HetNets: Distributed Algorithms and Hybrid Architecture
Max-Min Fair Resource Allocation in HetNets: Distributed Algorithms and Hybrid Architecture
复制标题
HetNet 中的最大-最小公平资源分配：分布式算法和混合架构
DOI：
10.1109/icdcs.2017.205
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
M. Chiang
中科院分区：
文献类型：
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作者：
Ehsan Aryafar;A. Keshavarz;Carlee Joe;M. Chiang
研究了RAN级集成HetNet的资源分配问题。这种新兴的HetNets范例允许针对每个客户端跨无线电接入技术进行动态业务拆分，然后用于聚合网络内的业务以提高整体资源利用率。我们专注于最大-最小公平服务速率分配的客户端，并研究最优解的性质。在此基础上，我们设计了一个低复杂度的分布式算法，试图实现最大最小公平性。我们还设计了一个混合网络架构，利用机会主义集中式网络监管，以增强分布式解决方案。我们分析了我们提出的算法的性能，并证明了它们的收敛性。我们也得到的条件下，结果是最佳的。当条件不满足时，我们提供恒定的最优性差距的上界和下界。最后，我们研究了我们的分布式解决方案的收敛时间，并表明，利用适当的政策，在其设计显着减少收敛时间。
We study the resource allocation problem in RAN-level integrated HetNets. This emerging HetNets paradigm allows for dynamic traffic splitting across radio access technologies for each client, and then for aggregating the traffic inside the network to improve the overall resource utilization. We focus on the max-min fair service rate allocation across the clients, and study the properties of the optimal solution. Based on the analysis, we design a low complexity distributed algorithm that tries to achieve max-min fairness. We also design a hybrid network architecture that leverages opportunistic centralized network supervision to augment the distributed solution. We analyze the performance of our proposed algorithms and prove their convergence. We also derive conditions under which the outcome is optimal. When the conditions are not satisfied, we provide constant upper and lower bounds on the optimality gap. Finally, we study the convergence time of our distributed solution and show that leveraging appropriate policies in its design significantly reduces the convergence time.