Peter Scheuermann - US grants

The workshop on Research Issues in the Integration of Heterogenous Database Systems will bring together a small group of approximately forty participants including both designers and users of large heterogenous systems that require integration. The objective of the workshop is to provide new perspectives on theoretical and experimental issues on this timely topic and to identify the basic research needed before the next generation of distributed heterogenous database systems is built. The workshop will examine the technical issues that arise in designing multidatabase or federated database systems where the individual systems have various degrees of autonomy and different capabilities. Some of the topics to be discussed are semantic heterogeneity and schema integration, transaction processing, and query processing.

9303583 Scheuermann This is the first year funding of a three-year continuing award. Large arrays of small disks provide an attractive approach for high performance systems since they allow for low-cost, reliable storage and can achieve higher throughput compared to large disks. This project proposes to develop an integrated set of algorithms and an intelligent file manager which is applicable to any multi-disk architecture in which the operating system can access the disks independently. The emphasis of the approach is on the use of modular building blocks for file partitioning, allocation, load balancing, and reorganization that can be invoked independently of each other. Thus, the procedure for load balancing can be called regardless of whether striping or declustering is employed and does not depend upon the unit of declustering. The development of a generalized method for load balancing is considered which can be applied to an environment where some files exhibit periodical access patterns and which considers explicitly the cost of performing the cooling actions. The investigation also focuses on reorganization procedures that perform restriping when higher performance standards need to be enforced. The anticipated results of this project are of importance to massively parallel computers to support scalability and to ensure that the I/O is not the limiting factor in achieving high speedup. ***

CDA-9703228 Prithviraj Banerjee Northwestern University A Distributed High-Performance Computing Infrastructure This award is for the acquisition of 20 high-end UNIX workstations, 50 low-end UNIX workstations, three UNIX fileservers, an 8-processor distributed shared memory multiprocessor, and a 64-ported ATM switching hub. The machines would be networked together using high-speed OC-3 ATM networks with bandwidths of 155 Mbps. As the use of high-speed networking moves from the laboratory to the workplace, new opportunities arise for the design and implementation of a high-speed distributed computing environment. The goals of this project are: (1) to explore the use of high-speed networking and computing to investigate file systems and data management issues for high-performance distributed computing, (2) to investigate the parallel programming support of networks of high-speed workstations and personal computers as an alternative to stand-alone parallel computers, (3) to study high-performance computer-aided design of electronic systems in a heterogeneous environment, and to develop a Web-based CAD computing center, that takes advantage of high-speed networking, (4) to explore new instructional techniques that take advantage of the high bandwidth and high speed.

Proposal Number : CCR-9902023
TITLE : SCALAR : Scalable Architecture for Replication on the Web
PI: Peter Scheuermann
Project Summary:

The wide use of the World-Wide Web and the ease of access to the Internet
are changing
drastically our requirements in distributed systems. The exponentially
growing scale of use of the
Web is stressing the capacity of the Internet and leads to poor performance
and low reliability of
Web service. Replication is one of the major techniques that have been
proposed to overcome these problems.

This project will focus on the development of a prototype system that will
provide a scalable
architecture for replication on the Web. A new client/server architecture
that will allow for user-transparent geographic replication is
investigated. In this system, the clients are downloaded as
signed applets to commercially available browsers. Web servers that support
servlets can be
directly extended with servlets, otherwise with server-side proxies that
support servlets. Unlike
other proposed Web architectures, both clients and servers take active
roles in this architecture.
Server machines determine the documents to be replicated/migrated and best
locations for the
documents, while client machines choose the best server to submit their
requests based on estimates of the servers' prior response times. Heuristic
algorithms based on clustering techniques
will be developed in order to determine sets of documents that be
beneficially migrated/replicated as a unit.

EIA-0000536
Scheuermann, Peter
Northwestern University

CISE Postdoctoral Associates in Experimental Computer Science: An
Architecture for Mining of Semi-Structured Data on the Web

With the explosion of the Web and the advent of digital libraries, the
demand for knowledge discovery techniques for semi-structured data has
increased greatly. Semi-structured HTML documents are characterized by a
rich data model, i.e., they contain both structured values and unstructured
concepts. Exploring the semantic knowledge about the relationships among
these unstructured concepts is important but costly as an on-line process.

The postdoctoral associate will assist in developing a prototype Web mining
system that will allow its users to specify a set of constraints, either
data values or concepts, and obtain a set of rules that contain the given
constraints and other items related to the constraint set. In order to
derive these rules, the system makes use of a concept library that
differentiates between general concepts and concepts associated with
specialized domains. Specifically, the associate will 1) develop new
methods for generating partially constrained association rules and
classifications rules that make use of the extended concept hierarchies
kept in the library, 2) investigate the various lexical tools available and
see how to integrate them into Wordnet (which forms the basis of the
concept library), 3) explore various heuristic methods for deciding when a
given concept belongs to a specialized concept library or to the general
concept library, and 4) explore the use of sampling techniques in reducing
the search space of rule generation.

Mobile computing and wireless networks have dramatically changed both the distributed systems communication paradigm and the ways that people access and manipulate information. Consequently, there is now widespread recognition of a strong need for context-aware computing in numerous application domains, particularly applications that assist in the management of emergency situations. Such applications will dynamically adjust to individual user profiles, user locations, the local environment, and the task being performed.

This project focuses on context-aware computing with applications to public health management. Core research issues in data management that are relevant to context-aware computing will be investigated. Also, the architecture of a system that supports context-aware applications with dynamically evolving data will be developed. Data integration tools and ontologies will be studied and then applied to actual source data and user profiles. This activity will be augmented with techniques for building spatio-temporal context from location traces. Methodologies will be developed to ensure the scalability of the system, including the use of request aggregation and of data cubes for caching user profiles and retrieved data. Security issues will be addressed by investigating an authentication model for spatio-temporal context based on a distributed trust framework. The architecture will also incorporate a component for the arbitration of services that can manage on-demand resource allocation in a competitive environment.

The successful completion of this project will significantly improve the quality, responsiveness, and delivery accuracy of services using context-aware computing. The focus on health care services, both in routine and in crisis situations (e.g., terrorist attacks, natural disasters) has the potential to contribute to an improved technology infrastructure for the public health sector nationwide.

Wireless sensor networks (WSNs) composed of smart sensors interconnected over wireless links are quickly becoming the technology of choice for monitoring and measuring geographically distributed physical, chemical, or biological phenomena in real time. Dynamic WSN environments encountered in environmental monitoring, surveillance, pollution control, and reconnaissance applications, require responsive management of WSN resources and their adaptive allocation to sensing, networking support, localization, and planning tasks, based on user requests and changes in the environment. A specified quality of service should however be ensured for criteria such as resolution of the raw-data, latency, network reconfiguration delay, and resource utilization in the steady-state. This project develops an integrated cross-layered approach to networking, databases, control, mobility management, and information processing in WSNs. In particular, context-aware and energy-efficient solutions are pursued that are based on opportunistic sensing and processing techniques, dynamic indexing structures, novel query language constructs, reactive mobility control algorithms, and distributed compression based routing algorithms.

The technological advances from this research will significantly simplify the deployment of WSNs and lead to novel context-aware applications. The advances will directly benefit domains such as emergency-response management, environmental threat remediation, and biological habitat monitoring. Apart from developing the required algorithms, the project will implement simulation platforms and a monitoring environment using physical devices. The platforms will provide students with new educational opportunities to actively explore information acquisition and resource management in resource-constrained environments. All project resources will be shared with the public through a project webpage.