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Theoretical-Analysis-Based Distributed Load Balancing Over Dynamic Overlay Clustering

机译:动态重叠集群中基于理论分析的分布式负载均衡

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In multicell networks, unbalanced cell loading can lead to decreased system stability and reduced fairness among serviced users. In this paper, we propose theoretical-analysis-based distributed load balancing (DLB) over dynamic overlay clustering implemented over a multicell network. The proposed system is divided into two parts: DLB and overlay clustering. First, for DLB, we define the long-term expected load after deriving the long-term expected rate in terms of proportional fairness. We then introduce two algorithms: DLB for load dispersion and DLB for edge-rate enhancement (ERE). These algorithms operate in a distributed manner based on mathematical analyses and load balancing characteristics. Second, through overlay clustering, load balancing within each cluster is consecutively performed on neighboring clusters, which enables the algorithm to optimally approximate in a distributed manner. The simulation results show that approximately 90% of the near-optimal performance in terms of load variation and ERE can be achieved with low complexity by using the proposed schemes. In addition, we discuss aspects and tradeoffs of the load balancing system.
机译:在多小区网络中,不均衡的小区负载会导致系统稳定性下降和服务用户之间的公平性下降。在本文中,我们提出了在多小区网络上实现的基于动态覆盖群集的基于理论分析的分布式负载平衡(DLB)。提出的系统分为两部分:DLB和覆盖聚类。首先,对于DLB,我们在按比例公平性推导长期预期利率之后定义长期预期负荷。然后,我们介绍两种算法:用于负载分散的DLB和用于边缘速率增强(ERE)的DLB。这些算法基于数学分析和负载平衡特性以分布式方式运行。其次,通过覆盖群集,可以在相邻群集上连续执行每个群集内的负载平衡,这使算法能够以分布式方式进行最佳近似。仿真结果表明,通过使用所提出的方案,可以以较低的复杂度实现大约90%的最佳性能(负载变化和ERE)。此外,我们讨论了负载平衡系统的各个方面和权衡取舍。

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