这些称为红黑树的四个先决条件。
These are called the four prerequisites of a red-black tree. Figure 4 shows an example of a red-black tree.
红黑树在时间和空间之间达成了妥协。
红黑树是一个自平衡的二叉查找树。
红黑树的算法试验作业。
在红黑树的内部节点的最大和最小的号码吗？
Largest and smallest number of internal nodes in red-black tree?
红黑树的叶子不包含信息，但是内部节点代表一个或多个可运行的任务。
Leaves in a red-black tree contain no information, but internal nodes represent one or more tasks that are runnable.
它将调度实体(进程)放入红黑树中，并对nr_running变量加1。
It puts the scheduling entity (process) into the red-black tree and increments the nr_running variable.
为了公平，调度器然后选取红黑树最左端的节点调度为下一个以便保持公平性。
The scheduler then, to be fair, picks the left-most node of the red-black tree to schedule next to maintain fairness.
实现时采用红黑树管理所分配的堆内存，理论推导和实验表明其具有较高的效率。
To cope with the problem of heap memory leak, this paper presents a dynamic memory leak check technology based on red-black tree.
第三，着重研究了基于红黑树的实时内存数据库数据组织结构及其查询优化方案。
The third, the Real-Time Memory Database based on the red-black tree and the querying optimization program are mainly researched.
此函数只是从红黑树中获取最左端的任务并返回相关 sched_entity。
This function simply picks the left-most task from the red-black tree and returns the associated sched_entity.
红黑树的每个节点都由rb _ node表示，它只包含子引用和父对象的颜色。
Each node in the red-black tree is represented by an rb_node, which contains nothing more than the child references and the color of the parent.
Watson分配策略在两个单独的 “红黑树” 中以节点的形式维护堆中的空闲空间
The Watson allocation policy maintains free space in the heap as nodes in two separate "red-black trees"
首先，我们介绍红黑树(red - black tree)技术以显示本文中消息队列框架的内部操作。
First, we'll introduce red-black tree technology to show the internal operations of the message queue framework in this article.
当前运行任务(现在被抢占的任务)通过对put _ prev_task调用(通过调度类)返回到红黑树。
The currently running task (now preempted) is returned to the red-black tree through a call to put_prev_task (via the scheduling class).
但是与之前的Linux调度器不同，它没有将任务维护在运行队列中，CFS维护了一个以时间为顺序的红黑树(参见图1)。
But rather than maintain the tasks in a run queue, as has been done in prior Linux schedulers, the CFS maintains a time-ordered red-black tree (see Figure 1).
对于大多数操作，红黑树的执行时间为O(logn)，而以前的调度程序通过具有固定优先级的优先级数组使用 O(1)。
The red-black tree is O(log n) in time for most operations, while the previous scheduler employed O(1), using a priority array with a fixed number of priorities.
最重要的是， sched_entity包含vruntime（64位字段），它表示任务运行的时间量，并作为红黑树的索引。
Most importantly, the sched_entity contains the vruntime (64-bit field), which indicates the amount of time the task has run and serves as the index for the red-black tree.
dequeue _ task：当某个任务退出可运行状态时调用该函数，它将从红黑树中去掉对应的调度实体，并从nr_running变量中减1。
Dequeue_task: When a task is no longer runnable, this function is called to keep the corresponding scheduling entity out of the red-black tree. It decrements the nr_running variable.
第一个可能的未来改变是对未应答的包列表进行修改，因此包列表的组织形式不再是当前的线性列表而是通过索引组织成红-黑树。
The first potential future change would modify the unacknowledged packet list so that it is organized with an index as a red-black tree instead of the current linear list.
“红-黑”树广泛应用于各种应用程序，其中包括关联数组的构造。
You can find red-black trees used in a variety of applications, including the construction of associative arrays.
这个数据结构是一个“红-黑”树，对于注重性能的应用程序很理想(且恰好作为内核中的一个库普遍可用)。
The data structure used is a red-black tree, which is ideal for performance-focused applications (and happens to be available generically as a library within the kernel).
您可以在./lib/rbtree.c 中找到 “红-黑”树的这个实现。
You can find the implementation of red-black trees in the kernel at ./lib/rbtree.c.
这就是为什么红-黑规则能保证树是平衡的。
假设执行旋转和适当颜色改变造成了在树的上方出现其他红-黑规则违规的情况。
Suppose that performing a rotation and appropriate color changes caused other violations of the red-black rules to appear further up the tree.
这保证了一次或两次旋转可以使整棵树再次成为正确的红-黑树。
It ensures that one or two rotations will restore red-black correctness in the entire tree.
可以说，2-3-4树中的3 -节点等价于红-黑树中有一个红色子节点的父节点，4 -节点等价于有两个红色子节点的父节点。
You can say that a 3-node in a 2-3-4 tree is equivalent to a parent with a red child in a red-black tree, and a 4-node is equivalent to a parent with two red children.
可以说，2-3-4树中的3 -节点等价于红-黑树中有一个红色子节点的父节点，4 -节点等价于有两个红色子节点的父节点。
You can say that a 3-node in a 2-3-4 tree is equivalent to a parent with a red child in a red-black tree, and a 4-node is equivalent to a parent with two red children.
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