14504228
Location dependent data and its management in mobile databases
In traditional ways of managing data, the relationship between the data and the geographical location of the organization it represents, is usually ignored. In wireless computing this property of "location transparency" is in fact often replaced by a "location dependency" property. Furthermore, the mode of issuing queries (the geographical location where the queries originate, the way they are issued, etc.) on such data determines the outcome. Location dependent data is data whose value depends on its location. The objective of the paper is to introduce this topic and spawn further related research.
8261257
TCOT-A Timeout-Based Mobile Transaction Commitment Protocol
We present a transaction commit protocol, "Transaction Commit On Timeout (TCOT)," based on a "timeout" approach for Mobile Database Systems (MDS), which can be universally used to reach a final transaction termination decision (e.g., commit, abort, etc.) in any message-oriented system. Particularly suited for a wireless environment, a timeout mechanism is the only way to minimize the impact of the slow and unreliable wireless link. We compare TCOT to a modified version of 2PC to show its superiority based on commit time.
29393244
Semantic Caching and Query Processing
Semantic caching is very attractive for use in distributed systems due to the reduced network traffic and the improved response time. It is particularly efficient for a mobile computing environment, where the bandwidth of wireless links is a major performance bottleneck. Previous work either does not provide a formal semantic caching model, or lacks efficient query processing strategies. This paper extends the existing research in three ways: formal definitions associated with semantic caching are presented, query processing strategies are investigated and, finally, the performance of the semantic cache model is examined through a detailed simulation study.
16958826
Recent Advances and Research Problems in Data Warehousing
In the recent years, the database community has witnessed the emergence of a new technology, namely data warehousing. A data warehouse is a global repository that stores pre-processed queries on data which resides in multiple, possibly heterogeneous, operational or legacy sources. The information stored in the data warehouse can be easily and efficiently accessed for making effective decisions. The On-Line Analytical Processing (OLAP) tools access data from the data warehouse for complex data analysis, such as multidimensional data analysis, and decision support activities. Current research has lead to new developments in all aspects of data warehousing, however, there are still a number of problems that need to be solved for making data warehousing effective. In this paper, we discuss recent developments in data warehouse modelling, view maintenance, and parallel query processing. A number of technical issues for exploratory research are presented and possible solutions are discussed.
34436430
An Integrated Data Structure with Multiple Access Paths for Database Systems and its Performance
Abstract In the past a number of file organizations have been proposed for processing different types of queries efficiently. To our knowledge none of the existing file organizations is capable of supporting all types of accesses equally efficiently. In this paper we have taken a different approach for designing an integated data structure which offers multiple access paths for processing different types of queries efficiently. The data structure reported here can be implemented on disk based as well as main memory database systems, however, in this paper we report its behavior mainly in main memory database environment. Our approach is to fuse those data structures which offer an efficient access paths for a particular type. To show the feasibility of our scheme we fused the B+-tree, the grid file and extendible hashing structures, using a proper interface. We implemented and measured its performance through simulation modeling. Our results show that the data structure does improve concurrency and offers a higher throughput for a variety of transaction processing workloads. We argue that our scheme is different than creating secondary indexes for improving concurrency. In the absence of a data strucure which can provide all types of access equally efficiently, an integrated data structure is an acceptable solution which offers an efficient way for increasing the performance of database management systems.
35078097
An adaptive location management algorithm for mobile computing
In mobile computing mobile hosts or mobile units move randomly from one place to another within a well-defined geographical area. This requires some mechanism for identifying the exact location of a mobile host. Such mechanisms are usually referred to as location management and is one of the essential components for supporting mobility. In the past a number of efficient location management schemes have been suggested but they lack adaptability. We believe that an adaptable location management scheme is more desirable because of frequent change in the location of mobile hosts. In this paper, we report a location management algorithm, which adapts to the constant changing scenario. Our algorithm makes use of some of the concepts of location management schemes proposed in the past.
1926044
Real-time vision-based control of a nonholonomic mobile robot
This paper considers the problem of vision-based control of a nonholonomic mobile robot. We describe the design and implementation of real-time estimation and control algorithms on a car-like robot platform using a single omni-directional camera as a sensor without explicit use of odometry. We provide experimental results for each of these vision-based control objects. The algorithms are packaged as control modes and can be combined hierarchically to perform higher level tasks involving multiple robots.
41766531
High Performance Data Mining
The current decade has seen an explosive growth in database technology and the amount of data collected. This has created an unprecedented opportunity for ”data mining,” which is a process of efficient supervised or unsupervised discovery of interesting information hidden in the data. The focus of this symposium is to bring together experts from the academia and the industry, including reseachers and practitioners, to discuss issues in this important area. Owing to the huge size of data and computation involved in data mining algorithms, parallel processing is often considered an essential component for a successful data mining solution - which will be a special emphasis of the symposium. Talks in this mini-symposium will cover both the current state-of the-practice as well as state-of-the-research in data mining. A highlight of the symposium is a panel discussion on the theory and practice of data mining.
1842716
Dynamic control of 3-D rolling contacts in two-arm manipulation
When two or more arms are used to manipulate a large object, it is necessary to maintain and control contacts between the object and effector(s) on one or more arms. The dynamic control of two arms manipulating a large object with rolling contacts is addressed. In the framework presented, the motion of the object as well as the loci of the contact points on the surface of the effectors and on the object can be directly controlled. The velocity and acceleration equations for three-dimensional rolling contacts are derived in order to obtain a dynamical model of the system. A nonlinear feedback algorithm that decouples and linearizes the system is used to demonstrate the control of rolling motion along each arm and the adaption of grasps to varying loads.<<ETX>>
1752850
High Performance Data Mining
Recent times have seen an explosive growth in the availability of various kinds of data. It has resulted in an unprecedented opportunity to develop automated data-driven techniques of extracting useful knowledge. Data mining, an important step in this process of knowledge discovery, consists of methods that discover interesting, non-trivial, and useful patterns hidden in the data [SAD+93, CHY96]. The field of data mining builds upon the ideas from diverse fields such as machine learning, pattern recognition, statistics, database systems, and data visualization. But, techniques developed in these traditional disciplines are often unsuitable due to some unique characteristics of today's data-sets, such as their enormous sizes, high-dimensionality, and heterogeneity. There is a necessity to develop effective parallel algorithms for various data mining techniques. However, designing such algorithms is challenging, and the main focus of the paper is a description of the parallel formulations of two important data mining algorithms: discovery of association rules, and induction of decision trees for classification. We also briefly discuss an application of data mining to the analysis of large data sets collected by Earth observing satellites that need to be processed to better understand global scale changes in biosphere processes and patterns.
7638167
Congruences for Visibly Pushdown Languages
We study congruences on words in order to characterize the class of visibly pushdown languages (Vpl), a subclass of context-free languages. For any language L, we define a natural congruence on words that resembles the syntactic congruence for regular languages, such that this congruence is of finite index if, and only if, L is a Vpl. We then study the problem of finding canonical minimal deterministic automata for Vpls. Though Vpls in general do not have unique minimal automata, we consider a subclass of VPAs called k-module single-entry VPAs that correspond to programs with recursive procedures without input parameters, and show that the class of well-matched Vpls do indeed have unique minimal k-module single-entry automata. We also give a polynomial time algorithm that minimizes such k-module single-entry VPAs.