平衡覆盖网络（BON）：通过自组织随机网络实现分散式负载均衡
Balanced Overlay Networks (BON): Decentralized Load Balancing via Self-Organized Random Networks
摘要：
我们提出了一种新的框架，称为平衡覆盖网络（BON），它提供了可扩展的，分散的负载均衡的分布式计算使用大规模池的异构计算机。基本上，BON将每个节点的可用计算资源信息编码在连接网络中节点的链路结构中。这种分布式编码是自组织的，每个节点通过随机游走采样管理其入度和本地连接。将传入作业分配给具有最多空闲资源的节点也通过经由短随机游走对节点进行采样来完成。大量的模拟表明，由此产生的高度动态和自组织的图结构可以有效地平衡整个大规模网络的计算负载。这些模拟涵盖了广泛的情况，包括可用计算资源的显著异质性和传入负载的高突发性。我们提供了分析结果，证明了BON的可扩展性，真正的大规模网络：特别是我们表明，在某些理想条件下，网络结构收敛到Erdos-Renyi（ER）随机图;我们的模拟结果，但是，表明该算法做得更好，结构似乎接近理想情况下的d-正则随机图。我们还将高负载的BON和著名的球仓随机负载均衡框架联系起来。
英文摘要：
We present a novel framework, called balanced overlay networks (BON), that provides scalable, decentralized load balancing for distributed computing using large-scale pools of heterogeneous computers. Fundamentally, BON encodes the information about each node's available computational resources in the structure of the links connecting the nodes in the network. This distributed encoding is self-organized, with each node managing its in-degree and local connectivity via random-walk sampling. Assignment of incoming jobs to nodes with the most free resources is also accomplished by sampling the nodes via short random walks. Extensive simulations show that the resulting highly dynamic and self-organized graph structure can efficiently balance computational load throughout large-scale networks. These simulations cover a wide spectrum of cases, including significant heterogeneity in available computing resources and high burstiness in incoming load. We provide analytical results that prove BON's scalability for truly large-scale networks: in particular we show that under certain ideal conditions, the network structure converges to Erdos-Renyi (ER) random graphs; our simulation results, however, show that the algorithm does much better, and the structures seem to approach the ideal case of d-regular random graphs. We also make a connection between highly-loaded BONs and the well-known ball-bin randomized load balancing framework.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
