The Environmental Protection Agency (EPA) provides access to information on a variety of topics related to the environment and strives to inform citizens of health risks. The EPA also has an extensive library network that consists of 26 libraries throughout the United States, which provide access to a plethora of information to EPA employees, scientists, and researchers. The EPA implemented a reorganization project to digitize their materials so they would be more accessible to a wider range of users, but this plan was drastically accelerated when the EPA was threatened with a budget cut. It chose to close and reduce the hours and services of some of their libraries. As a result, the agency was accused of denying users the “right to know” by making information unavailable, not providing an adequate strategic plan, and discarding vital materials. This case study explores the background of the digitization project, the practices implemented, and the critiques of the project.

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The Environmental Protection Agency

Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On the contrary, modern data models exacerbate the problem: In order to manipulate large sets of complex objects as efficiently as today's database systems manipulate simple records, query-processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software. This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.

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Query evaluation techniques for large databases

Static scheduling of a program represented by a directed task graph on a multiprocessor system to minimize the program completion time is a well-known problem in parallel processing. Since finding an optimal schedule is an NP-complete problem in general, researchers have resorted to devising efficient heuristics. A plethora of heuristics have been proposed based on a wide spectrum of techniques, including branch-and-bound, integer-programming, searching, graph-theory, randomization, genetic algorithms, and evolutionary methods. The objective of this survey is to describe various scheduling algorithms and their functionalities in a contrasting fashion as well as examine their relative merits in terms of performance and time-complexity. Since these algorithms are based on diverse assumptions, they differ in their functionalities, and hence are difficult to describe in a unified context. We propose a taxonomy that classifies these algorithms into different categories. We consider 27 scheduling algorithms, with each algorithm explained through an easy-to-understand description followed by an illustrative example to demonstrate its operation. We also outline some of the novel and promising optimization approaches and current research trends in the area. Finally, we give an overview of the software tools that provide scheduling/mapping functionalities.

http://charm.cs.uiuc.edu/users/arya/docs/6.pdf

Static scheduling algorithms for allocating directed task graphs to multiprocessors

The technologies, architectures, and methodologies traditionally used to develop distributed applications exhibit a variety of limitations and drawbacks when applied to large scale distributed settings (e.g., the Internet). In particular, they fail in providing the desired degree of configurability, scalability, and customizability. To address these issues, researchers are investigating a variety of innovative approaches. The most promising and intriguing ones are those based on the ability of moving code across the nodes of a network, exploiting the notion of mobile code. As an emerging research field, code mobility is generating a growing body of scientific literature and industrial developments. Nevertheless, the field is still characterized by the lack of a sound and comprehensive body of concepts and terms. As a consequence, it is rather difficult to understand, assess, and compare the existing approaches. In turn, this limits our ability to fully exploit them in practice, and to further promote the research work on mobile code. Indeed, a significant symptom of this situation is the lack of a commonly accepted and sound definition of the term mobile code itself. This paper presents a conceptual framework for understanding code mobility. The framework is centered around a classification that introduces three dimensions: technologies, design paradigms, and applications. The contribution of the paper is two-fold. First, it provides a set of terms and concepts to understand and compare the approaches based on the notion of mobile code. Second, it introduces criteria and guidelines that support the developer in the identification of the classes of applications that can leverage off of mobile code, in the design of these applications, and, finally, in the selection of the most appropriate implementation technologies. The presentation of the classification is intertwined with a review of state-of-the-art in the field. Finally, the use of the classification is exemplified in a case study.

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Understanding code mobility

We review a model of computation used in industrial practice in signal processing software environments and experimentally and other contexts. We give this model the name "dataflow process networks," and study its formal properties as well as its utility as a basis for programming language design. Variants of this model are used in commercial visual programming systems such as SPW from the Alta Group of Cadence (formerly Comdisco Systems), COSSAP from Synopsys (formerly Cadis), the DSP Station from Mentor Graphics, and Hypersignal from Hyperception. They are also used in research software such as Khoros from the University of New Mexico and Ptolemy from the University of California at Berkeley, among many others. Dataflow process networks are shown to be a special case of Kahn process networks, a model of computation where a number of concurrent processes communicate through unidirectional FIFO channels, where writes to the channel are nonblocking, and reads are blocking. In dataflow process networks, each process consists of repeated "firings" of a dataflow "actor." An actor defines a (often functional) quantum of computation. By dividing processes into actor firings, the considerable overhead of context switching incurred in most implementations of Kahn process networks is avoided. We relate dataflow process networks to other dataflow models, including those used in dataflow machines, such as static dataflow and the tagged-token model. We also relate dataflow process networks to functional languages such as Haskell, and show that modern language concepts such as higher-order functions and polymorphism can be used effectively in dataflow process networks. A number of programming examples using a visual syntax are given. >

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Dataflow process networks

Arsenic is widely distributed in the environment by natural and human means. The potential for adverse health effects from inorganic arsenic depends on the level and route of exposure. To estimate potential health risks of inorganic arsenic, the apportionment of exposure among sources of inorganic arsenic is critical. In this study, daily inorganic arsenic intake of U.S. adults from food, water, and soil ingestion and from airborne particle inhalation was estimated. To account for variations in exposure across the U.S., a Monte Carlo approach was taken using simulations for 100,000 individuals representing the age, gender, and county of residence of the U.S. population based on census data. Our analysis found that food is the greatest source of inorganic arsenic intake and that drinking water is the next highest contributor. Inhalation of airborne arsenic-containing particles and ingestion of arsenic-containing soils were negligible contributors. The exposure is best represented by the ranges of inorganic...

https://www.ics.uci.edu/~bic/papers/Menzel-Arsenic.pdf

Estimation of Multimedia Inorganic Arsenic Intake in the U.S. Population

Most existing distributed systems are structured as statically compiled processes communicating with each other via messages. The system's intelligence is embodied in the processes, while the messages contain simple, passive pieces of information. This is referred to as the communicating objects paradigm. In the autonomous objects paradigm, a message has its own identity and behavior. It decides at runtime where it wants to propagate and what tasks to perform there; the nodes become simply generic interpreters that enable messages to navigate and compute. In this scenario, an application's intelligence is embodied in and carried by messages as they propagate through the network. The autonomous objects paradigm is more flexible than the communicating objects paradigm because it allows developers to change the program's behavior after it has started to run. We based our system, MESSENGERS, on autonomous objects, and intended it for the composition and coordination of concurrent activities in a distributed environment. It combines powerful navigational capabilities found in other autonomous objects based systems with efficient dynamic linking mechanisms supported by some new programming languages, like Java.

Distributed computing using autonomous objects

A research monograph demonstrating the advances that have been made in data-flow computing since the basic principles were first introduced some 20 years ago. It also points out the immediate applications of this approach and assesses its future for large-scale multiprocessing.

Advanced Topics in Data-Flow Computing

Large-scale distributed simulations model the activities of thousands of entities interacting in a virtual environment simulated over wide-area networks. Originally these systems used protocols that dictated that all entities broadcast messages about all activities, including remaining immobile or inactive, to all other entities, resulting in an explosion of incoming messages for all entities, most of which were of no interest. Using a filtering mechanism called interest management, some of these systems now allow entities to express interest in only the subset of information that is relevant to them. This paper surveys ten such systems, describing the purpose of the system, its scope, and the salient characteristics of its interest management scheme. We present the first taxonomy for such systems and classify the ten systems according to the taxonomy. The analysis of the classification reveals the fundamental nature of interest management and points to potential areas of research.

Interest Management in Large-Scale Virtual Environments

This paper proposes a mobile-agent-based middleware that benefits remote computer users who wish to mutually offer their desktop computing resource to other Internet group members while their computers are not being used. Key to this resource exchange grid is the use of mobile agents. Each agent represents a client user, carries his/her job requests, searches for resources available for the request, executes the job at suitable computers, and migrates it to others when the current ones have become unavailable for use. All the features of job migration will be encapsulated in a user program wrapper that is implemented on Java layer between a mobile agent and the corresponding user program. The wrapper maintains the complete execution state of the user program, is carried by the mobile agent upon a job migration, and restores its user program its destination. For this purpose, a user program is preprocessed with JavaCC and ANTLR to include check-pointing functions before its execution. These functions periodically save the execution state of a user program into its corresponding program wrapper, which can thus be carried by an agent smoothly.

Lubomir Bic

Papers

Estimation of Multimedia Inorganic Arsenic Intake in the U.S. Population

Distributed computing using autonomous objects

Advanced Topics in Data-Flow Computing

Interest Management in Large-Scale Virtual Environments

A mobile-agent-based PC grid