Kademlia 论文中的 bucket height 是什么意思？
What is the meaning of bucket height in the Kademlia paper?
它说：
We start with some definitions. For a k-bucket covering the distance range 2i,2i+1 , define the index of the bucket to be i. Define the depth, h, of a node to be 160 − i, where i is the smallest index of a non-empty bucket. Define node y’s bucket height in node x to be the index of the bucket into which x would insert y minus the index of x’s least significant empty bucket. Because node IDs are randomly chosen, it follows that highly non-uniform distributions are unlikely. Thus with overwhelming probability the height of a any given node will be within a constant of log n for a system with n nodes. Moreover, the bucket height of the closest node to an ID in the kth-closest node will likely be within a constant of log k.
我能理解bucket height的定义，但是我不知道为什么我们需要那个定义，而且我不明白该段的最后一句话。
更新：
我还认为这篇论文有一个错字：桶高应该是包含 y 的桶的索引减去 x 的最低有效 "NON-" 空桶的索引。我错了吗？
but I don't know why we need that definition
kademlia 在路由 table 大小和查找步骤方面的 O(log n) 效率的论点是基于将 n 个节点的整个键空间映射到 k-buckets，其中更远的 buckets 以指数方式覆盖键空间的较大部分。有效地将整个网络压缩成一个有偏见的样本列表。
然后进一步向下的论点基于这个基于桶的投影。
Moreover, the bucket height of the closest node to an ID in the kth-closest node will likely be within a constant of log k.
我认为这是一种令人费解的说法，即您的 k 个最近的邻居最终都将位于或接近同一个桶，即最深的桶（最小索引非空桶）。
请注意，这是用 表示的，在树布局中，最小的桶类似于但不一定与覆盖自己 ID 的桶相同。
它说：
We start with some definitions. For a k-bucket covering the distance range 2i,2i+1 , define the index of the bucket to be i. Define the depth, h, of a node to be 160 − i, where i is the smallest index of a non-empty bucket. Define node y’s bucket height in node x to be the index of the bucket into which x would insert y minus the index of x’s least significant empty bucket. Because node IDs are randomly chosen, it follows that highly non-uniform distributions are unlikely. Thus with overwhelming probability the height of a any given node will be within a constant of log n for a system with n nodes. Moreover, the bucket height of the closest node to an ID in the kth-closest node will likely be within a constant of log k.
我能理解bucket height的定义，但是我不知道为什么我们需要那个定义，而且我不明白该段的最后一句话。
更新： 我还认为这篇论文有一个错字：桶高应该是包含 y 的桶的索引减去 x 的最低有效 "NON-" 空桶的索引。我错了吗？
but I don't know why we need that definition
kademlia 在路由 table 大小和查找步骤方面的 O(log n) 效率的论点是基于将 n 个节点的整个键空间映射到 k-buckets，其中更远的 buckets 以指数方式覆盖键空间的较大部分。有效地将整个网络压缩成一个有偏见的样本列表。
然后进一步向下的论点基于这个基于桶的投影。
Moreover, the bucket height of the closest node to an ID in the kth-closest node will likely be within a constant of log k.
我认为这是一种令人费解的说法，即您的 k 个最近的邻居最终都将位于或接近同一个桶，即最深的桶（最小索引非空桶）。
请注意，这是用