A concurrent object is a data object shared by concurrent processes. Linearizability is a correctness condition for concurrent objects that exploits the semantics of abstract data types. It permits a high degree of concurrency, yet it permits programmers to specify and reason about concurrent objects using known techniques from the sequential domain. Linearizability provides the illusion that each operation applied by concurrent processes takes effect instantaneously at some point between its invocation and its response, implying that the meaning of a concurrent object’s operations can be given by pre- and post-conditions. This paper defines linearizability, compares it to other correctness conditions, presents and demonstrates a method for proving the correctness of implementations, and shows how to reason about concurrent objects, given they are linearizable.

Search operations in databases require special support at the physical level. This is true for conventional databases as well as spatial databases, where typical search operations include the point query (find all objects that contain a given search point) and the region query (find all objects that overlap a given search region). More

Most current approaches to concurrency control in database systems rely on locking of data objects as a control mechanism. In this paper, two families of nonlocking concurrency controls are presented. The methods used are “optimistic ” in the sense that they rely mainly on transaction backup as a control mechanism, “hoping ” that conflicts between transactions will not occur. Applications for which these methods should be more efficient than locking are discussed.

A con.curren.t object is a data structure shared by concurrent processes. Conventional techniques for implementing concurrent objects typically rely on criticaI sections: ensuring that only one process at a time can operate on the object. Nevertheless, critical sections are poorly suited for asynchronous systems: if one process is halted or delayed in a critical section, other, non-faulty processes will be unable to progress. By contrast, a concurrent object implementation is non-blocking if it always guarantees that some process will complete an operation in a finite number of steps, and it is wait-free if it guarantees that each process will complete an operation in a finite number of steps. This paper proposes a new methodology for constructing non-blocking aud wait-free implementations of concurrent objects. The object’s representation and operations are written as st,ylized sequential programs, with no explicit synchronization. Each sequential operation is automatically transformed into a non-blocking or wait-free operation usiug novel synchronization and memory management algorithms. These algorithms are presented for a multiple instruction/multiple data (MIM D) architecture in which n processes communicate by applying read, write, and comparekYswa,p operations to a shared memory. 1

We propose a new form of software transactional memory (STM) designed to support dynamic-sized data structures, and we describe a novel non-blocking implementation. The non-blocking property we consider is obstruction-freedom. Obstruction-freedom is weaker than lock-freedom; as a result, it admits substantially simpler and more efficient implementations. A novel feature of our obstruction-free STM implementation is its use of modular contention managers to ensure progress in practice. We illustrate the utility of our dynamic STM with a straightforward implementation of an obstruction-free red-black tree, thereby demonstrating a sophisticated non-blocking dynamic data structure that would be difficult to implement by other means. We also present the results of simple preliminary performance experiments that demonstrate that an "early release " feature of our STM is useful for reducing contention, and that our STM lends itself to the effective use of modular contention managers.

The B-tree and its variants have been found to be highly useful (both theoretically and in practice) for storing large amounts ofinformation, especially on secondary storage devices. We examine the problem of overcoming the inherent difficulty of concurrent operations on such structures, using a practical storage model. A single additional “link ” pointer in each node allows a process to easily recover from tree modifications performed by other concurrent processes. Our solution compares favorably with earlier solutions in that the locking scheme is simpler (no read-locks are used) and only a (small) constant number of nodes are locked by any update process at any given time. An informal correctness proof for our system is given,

This paper presents an overview of EXODUS, an extensible database system project that is addressing data management problems posed by a variety of challenging new applications. The goal of the project is to facilitate the fast development of high-performance, application-specific database systems. EXODUS provides certain kernel facilities, including a versatile storage manager. In addition, it provides an architectural framework for building application-specific database systems; powerful tools to help automate the generation of such systems, including a rule-based query optimizer generator and a persistent programming language; and libraries of generic software components (e.g., access methods) that are likely to be useful for many application domains. We briefly describe each of the components of EXODUS in this paper, and we also describe a next-generation DBMS that we are now building using the EXODUS tools. 1.

This survey concerns the role of data structures for compactly storing and representing various types of information in a localized and distributed fashion. Traditional approaches to data representation are based on global data structures, which require access to the entire structure even if the sought information involves only a small and local set of entities. In contrast, localized data representation schemes are based on breaking the information into small local pieces, or labels, selected in a way that allows one to infer information regarding a small set of entities directly from their labels, without using any additional (global) information. The survey focuses on combinatorial and algorithmic techniques, and covers complexity results on various applications, including compact localized schemes for message routing in communication networks, and adjacency and distance labeling schemes.

With non-traditional application areas such as engineering design, image/voice data management, scientific/statistical applications, and artificial intelligence systems all clamoring for ways to store and efficiently process larger and larger volumes of data, it is clear that traditional database technology has been pushed to its lim-its. It also seems clear that no single database system will be capable of simultaneously meeting the functionality and performance requirements of such a diverse set of applications. In this paper we describe the initial design of EXODUS, an extensible database system that will facilitate the fast development of high-performance, application-specific database systems. EXODUS provides certain kernel facilities, including a versatile storage manager and a type manager. In addition, it provides an architectural framework for building application-specific database sys-tems, tools to partially automate the generation of such systems, and libraries of software components (e.g., access methods) that are likely to be useful for many application domains.

. High-performance transaction system applications typically insert rows in a History table to provide an activity trace; at the same time the transaction system generates log records for purposes of system recovery. Both types of generated information can benefit from efficient indexing. An example in a well-known setting is the TPC-A benchmark application, modified to support efficient queries on the History for account activity for specific accounts. This requires an index by account-id on the fast-growing History table. Unfortunately, standard disk-based index structures such as the B-tree will effectively double the I/O cost of the transaction to maintain an index such as this in real time, increasing the total system cost up to fifty percent. Clearly a method for maintaining a real-time index at low cost is desirable. The Log-Structured Merge-tree (LSM-tree) is a disk-based data structure designed to provide low-cost indexing for a file experiencing a high rate of record inserts ...