A Concurrency-Optimal Binary Search Tree

The paper presents the first \emph{concurrency-optimal} implementation of a binary search tree (BST). The implementation, based on a standard sequential implementation of an internal tree, ensures that every \emph{schedule} is accepted, i.e., interleaving of steps of the sequential code, unless linearizability is violated. To ensure this property, we use a novel read-write locking scheme that protects tree \emph{edges} in addition to nodes. Our implementation outperforms the state-of-the art BSTs on most basic workloads, which suggests that optimizing the set of accepted schedules of the sequential code can be an adequate design principle for efficient concurrent data structures

Distribution-graph based approach and extended tree growing technique in power-constrained block-test scheduling

A distribution-graph based scheduling algorithm is proposed together with an extended tree growing technique to deal with the problem of unequal-length block-test scheduling under power dissipation constraints. The extended tree growing technique is used in combination with the classical scheduling approach in order to improve the test concurrency having assigned power dissipation limits. Its goal is to achieve a balanced test power dissipation by employing a least mean square error function. The least mean square error function is a distribution-graph based global priority function. Test scheduling examples and experiments highlight in the end the efficiency of this approach towards a system-level test scheduling algorithm

A comparison of classical scheduling approaches in power-constrained block-test scheduling

Classical scheduling approaches are applied here to overcome the problem of unequal-length block-test scheduling under power dissipation constraints. List scheduling-like approaches are proposed first as greedy algorithms to tackle the fore mentioned problem. Then, distribution-graph based approaches are described in order to achieve balanced test concurrency and test power dissipation. An extended tree growing technique is also used in combination with these classical approaches in order to improve the test concurrency having assigned power dissipation limits. A comparison between the results of the test scheduling experiments highlights the advantages and disadvantages of applying different classical scheduling algorithms to the power-constrained test scheduling proble

Efficient Management of Short-Lived Data

Motivated by the increasing prominence of loosely-coupled systems, such as mobile and sensor networks, which are characterised by intermittent connectivity and volatile data, we study the tagging of data with so-called expiration times. More specifically, when data are inserted into a database, they may be tagged with time values indicating when they expire, i.e., when they are regarded as stale or invalid and thus are no longer considered part of the database. In a number of applications, expiration times are known and can be assigned at insertion time. We present data structures and algorithms for online management of data tagged with expiration times. The algorithms are based on fully functional, persistent treaps, which are a combination of binary search trees with respect to a primary attribute and heaps with respect to a secondary attribute. The primary attribute implements primary keys, and the secondary attribute stores expiration times in a minimum heap, thus keeping a priority queue of tuples to expire. A detailed and comprehensive experimental study demonstrates the well-behavedness and scalability of the approach as well as its efficiency with respect to a number of competitors.Comment: switched to TimeCenter latex styl

DeltaTree: A Practical Locality-aware Concurrent Search Tree

As other fundamental programming abstractions in energy-efficient computing, search trees are expected to support both high parallelism and data locality. However, existing highly-concurrent search trees such as red-black trees and AVL trees do not consider data locality while existing locality-aware search trees such as those based on the van Emde Boas layout (vEB-based trees), poorly support concurrent (update) operations. This paper presents DeltaTree, a practical locality-aware concurrent search tree that combines both locality-optimisation techniques from vEB-based trees and concurrency-optimisation techniques from non-blocking highly-concurrent search trees. DeltaTree is a $k$-ary leaf-oriented tree of DeltaNodes in which each DeltaNode is a size-fixed tree-container with the van Emde Boas layout. The expected memory transfer costs of DeltaTree's Search, Insert, and Delete operations are $O(\log_B N)$, where $N, B$ are the tree size and the unknown memory block size in the ideal cache model, respectively. DeltaTree's Search operation is wait-free, providing prioritised lanes for Search operations, the dominant operation in search trees. Its Insert and {\em Delete} operations are non-blocking to other Search, Insert, and Delete operations, but they may be occasionally blocked by maintenance operations that are sometimes triggered to keep DeltaTree in good shape. Our experimental evaluation using the latest implementation of AVL, red-black, and speculation friendly trees from the Synchrobench benchmark has shown that DeltaTree is up to 5 times faster than all of the three concurrent search trees for searching operations and up to 1.6 times faster for update operations when the update contention is not too high