5640715
A Multi-Resolution Relational Data Model
The use of data at different levels of information content is essential to the performance of multimedia, scientific, and other large databases because it can significantly decrease I/O and communication costs. The performance advantages of such a multi-resolution scheme can only be fully exploited by a data model that supports the convenient retrieval of data at different levels of information content. In this paper we extend the relational data model to support multi-resolution data retrieval. In particular, we introduce a new partial set construct, called the sandbag, that can support multi-resolution for the types of data used in a wide variety of next-generation database applications, as well as traditional applications. We extend the relational algebra operators to analogous operators on sandbags. The resulting extension of the relational algebra is sound and forms a foundation for future database management systems that support these types of next-generation applications.
17840897
Research issues in multimedia storage servers
Multimedia applications require support for the storage and retrieval of multimedia data, which typically consist of video, audio, text, and images. These data can be categorized into continuous media (CM) data (e.g., video, audio) and noncontinuous media data (e.g., text, images). CM data, in contrast to nonCM data, have certain timing characteristics associated with them. For example, video clips, which are typically stored in units of frames, must be delivered to viewers at a certain rate (typically 30 frames/ see). For video compressed using the MPEG-I standard, this translates to a data rate of approximately 1.5 Mbps. CM data are also voluminous. For example, a 100-minute video compressed using the MPEG-I compression algorithm requires about 1.25 GB of storage space. The timing characteristics and the large volumes of CM data make the design of a multimedia storage server a challenging task. Such a server should:
5892105
Topology discovery in heterogeneous IP networks
Knowledge of the up-to-date physical topology of an IP network is crucial to a number of critical network management tasks, including reactive and proactive resource management, event correlation, and root-cause analysis. Given the dynamic nature of today's IP networks, keeping track of topology information manually is a daunting (if not impossible) task. Thus, effective algorithms for automatically discovering physical network topology are necessary. Earlier work has typically concentrated on either: (a) discovering logical (i.e., layer-3) topology, which implies that the connectivity of all layer-2 elements (e.g., switches and bridges) is ignored; or (b) proprietary solutions targeting specific product families. In this paper, we present novel algorithms for discovering physical topology in heterogeneous (i.e., multi-vendor) IP networks. Our algorithms rely on standard SNMP MIB information that is widely supported by modern IP network elements and require no modifications to the operating system software running on elements or hosts. We have implemented the algorithms presented in this paper in the context of a topology discovery tool that has been tested on Lucent's own research network. The experimental results clearly validate our approach, demonstrating that our tool can consistently discover the accurate physical network topology in time that is roughly quadratic in the number of network elements.
10403742
Consistency in Hierarchical Database Systems
The problems of locking and consistency m database systems are examined It is assumed that each transacuon, when executed alone, transforms a consistent state into a consistent state A set of conditions is derived to guarantee that when transactions are processed concurrently, the results are the same as would be obtained by processing the transactmns serially These conditions are used to estabhsh a locking protocol in Merarchmal database systems The locking protocol allows transaeuons to request new locks after releasing a lock. However, a data item may be locked at most once as a result of each transacUon It ~s shown that the protocol ensures consistency and that tt ts deadlock free.
2374841
The Lowell database research self-assessment
Database needs are changing, driven by the Internet and increasing amounts of scientific and sensor data. In this article, the authors propose research into several important new directions for database management systems.
6287800
Ensuring consistency in multidatabases by preserving two-level serializability
The concept of serializability has been the traditionally accepted correctness criterion in database systems. However in multidatabase systems (MDBSs), ensuring global serializability is a difficult task. The difficulty arises due to the heterogeneity of the concurrency control protocols used by the participating local database management systems (DBMSs), and the desire to preserve the autonomy of the local DBMSs. In general, solutions to the global serializability problem result in executions with a low degree of concurrency. The alternative, relaxed serializability, may result in data inconsistency.
In this article, we introduce a systematic approach to relaxing the serializability requirement in MDBS environments. Our approach exploits the structure of the integrity constraints and the nature of transaction programs to ensure consistency without requiring executions to be serializable. We develop a simple yet powerful classification of MDBSs based on the nature of integrity constraints and transaction programs. For each of the identified models we show how consistency can be preserved by ensuring that executions are two-level serializable (2LSR). 2LSR is a correctness criterion for MDBS environments weaker than serializability. What makes our approach interesting is that unlike global serializability, ensuring 2LSR in MDBS environments is relatively simple and protocols to ensure 2LSR permit a high degree of concurrency. Furthermore, we believe the range of models we consider cover many practical MDBS environments to which the results of this article can be applied to preserve database consistency.
520564
Cyclic association rules
We study the problem of discovering association rules that display regular cyclic variation over time. For example, if we compute association rules over monthly sales data, we may observe seasonal variation where certain rules are true at approximately the same month each year. Similarly, association rules can also display regular hourly, daily, weekly, etc., variation that is cyclical in nature. We demonstrate that existing methods cannot be naively extended to solve this problem of cyclic association rules. We then present two new algorithms for discovering such rules. The first one, which we call the sequential algorithm, treats association rules and cycles more or less independently. By studying the interaction between association rules and time, we devise a new technique called cycle pruning, which reduces the amount of time needed to find cyclic association rules. The second algorithm, which we call the interleaved algorithm, uses cycle pruning and other optimization techniques for discovering cyclic association rules. We demonstrate the effectiveness of the interleaved algorithm through a series of experiments. These experiments show that the interleaved algorithm can yield significant performance benefits when compared to the sequential algorithm. Performance improvements range from 5% to several hundred percent.