Relaxed Balanced Red - Black Trees

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Abstract. Relaxed balancing means that, in a dictionary stored as a balanced tree, the

necessary rebalancing after updates may be delayed. This is in contrast to strict balancing

meaning that rebalancing is performed immediately after the update. Relaxed balancing

is important for efficiency in highly dynamic applications where updates can occur in

bursts. The rebalancing tasks can be performed gradually after all urgent updates, allowing

the concurrent use of the dictionary even though the underlying tree structure is not

completely in balance. In this paper we propose a new scheme of how to make known

rebalancing techniques relaxed in an efficient way. The idea is applied to the red-black

trees, but can be applied to any class of balanced trees. The key idea is to accumulate

insertions and deletions such that they can be settled in arbitrary order using the same

rebalancing operations as for standard balanced search trees. As a result it can be shown

that the number of needed rebalancing operations known from the strict balancing scheme

carry over to relaxed balancing.

1 Introduction

A dictionary is a scheme for storing a set of data such that the operations search, insert,

and delete can be carried out efficiently. Standard implementations of dictionaries using

balanced search trees like red-black trees, AVL-trees, half-balanced trees, and others

presuppose that each update operation is followed by a sequence of rebalancing steps

which restore the respective balance condition. Maintaining the balance conditions assures

that the trees cannot degenerate into linear lists and search and update operations

can be performed in a number of steps which is always logarithmic in the number of

keys stored in a tree.

In a concurrent environment, however, uncoupling the updating (insertion and deletion)

from the rebalancing transformations may increase the possible amount of concurrency

and speed up updates considerably. This leads to the notion of relaxed balance.

Instead of requiring that the balance condition is restored immediately after each update

operation the actual rebalancing transformations can be delayed arbitrarily and

interleaved freely with search and update operations.

Relaxed balancing was first suggested in [8] for red-black trees. The first actual

solution, presented by Kessels [10], is for relaxed balancing in AVL-trees [1] where

the allowed updates are only insertions. Nurmi et al. [14] extend the work of Kessels

to the general case in which deletions are also allowed. In [11] the solution of [14]

is analyzed, and it is shown that for each update operation in a tree with maximum

size n, O(log n) new rebalancing operations are needed. Relaxed balanced B-trees are

introduced in [14] and further analyzed in [12]. In [13] Nurmi and Soisalon-Soininen

propose a relaxed version of red-black trees which they call a chromatic tree. Boyar

and Larsen [5] analyze the proposal of [13] and show that after a minor modification

the number of rebalancing operations per update is O(log(n+i)), if i insertions are performed

on a tree which initially contains n leaves. Boyar et al. [3] prove for a slightly

modified set of rebalancing operations that only an amortized constant amount of rebalancing

is necessary after an update in a chromatic tree. In [21] Soisalon-Soininen

and Widmayer propose a relaxed version of AVL-trees which fulfills, despite the local

nature of its operations, some global properties. For example, they show that in their

solution no rotation will be performed if the underlying search tree happens to fulfill

the AVL tree balance condition before any rebalancing has been done.

Except for the recent paper [21], all previous solutions are not wholly based on the

standard balancing transformations but require a large number of different new transformations.

In this paper we propose a new technique of how to make known rebalancing algorithms

relaxed in an efficient way.We show that essentially the same set of rebalancing

transformations as used in the strict case can also be used for the relaxed case, and that

the number of needed rebalancing operations known from the strict balancing scheme

carry over to relaxed balancing.

In order to illustrate the key ideas and to clarify the ideas underlying our solution as

much as possible, we restrict ourselves to the case of red-black trees. But we emphasize

that the ideas of marking items for deletions, allowing trees to grow randomly below the

balanced part, and to settle accumulated update and rebalancing requests in top-down

manner using the standard rebalancing operations carry over to many other classes of

search trees as well. The aim of our proposal is to extend the constant-linkage-cost

update algorithm for red-black trees [19] in such a way that updates and local structural

changes are uncoupled and may be arbitrarily delayed and interleaved.A key idea in our

solution is the assumption that the deletion of a key in a tree leads to a removal request

only; the actual removal of a leaf is considered to be a part of the structural change

to restore the balance condition. In this way we put completely aside the problem of

deletion which has complicated the previous solutions of relaxed balancing.

2 Red-black trees

The trees in this paper are leaf-oriented binary search trees, which are full binary trees

(each node has either two or no children). The nullary nodes of a tree are called the

external nodes or leaves while the other nodes are said to be internal nodes.We assume

that the keys (chosen from a totally ordered universe) are stored in the leaves of the

binary tree. The internal nodes contain routers, which guide the search from the root to

a leaf.

For simplicity, we do not distinguish between search trees with stored items (in

left-to-right order at the leaves) and their underlying graph structure.

A binary search tree is balanced if its height is bounded by O(logN), where N is

the number of keys stored in the tree.

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