Lubomir Bic

Distributed computing using autonomous objects

Most existing distributed systems are structured as statically compiled processes communicating with each other via messages. The systems 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 applications 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 programs 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.

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

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 arsenic intake (at the 10th and 90th percentiles), which were 1.8 to 11.4 µg/day for males and 1.3 to 9.4 µg/day for females. Regional differences in inorganic arsenic exposure were due mostly to consumption of drinking water containing differing inorganic arsenic content rather than to food preferences.

Interest Management in Large-Scale Virtual Environments

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.

A mobile-agent-based PC grid

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.

Evaluating aggregates in possibilistic relational databases

Abstract The need for extending information management systems to handle the imprecision iof information found in the real world has been recognized. Fuzzy set theory together with possibility theory represent a uniform framework for extending the relational database model with these features. However, none of the existing proposals for handling imprecision in the literature had dealt with queries involving a functional evaluation of a set of items, traditionally refered to as aggregation. Two kinds of aggregate operators, namely, scalar aggregates and aggregate functions, exist. Both are important for most real-world applciations, and thus this paper presents a framework for handling these two types of aggregates in the context of imprecise information. We consider three cases, specifically, aggregates within vague queries on precise data, aggregates within precisely specified queries on possibilistic data, and aggregates within vague queries on imprecise data. The consistency of the proposed operations is shown. An extended operator is defined to be consistent if it defaults to its classical counterpart when evaluated on crisp data.

Set operations in object-based data models

The semantics of set operations are not adequate for the richer data models of object-based database systems that include object-oriented and semantic data modeling concepts. The reason is that precise semantics of set operations on complex objects require a clear distinction between the dual notions of a set and a type, both of which are present in the class construct found in object-based data models. This gap is filled here by a framework for executing set theoretic operations on the class construct. The proposed set operations, including set difference, union, intersection and symmetric difference, determine both the type description of the derived class as well as its set membership. For the former, inheritance rules are developed for property characteristics such as single-valued versus multivalued and required versus optional. For the latter, the object identity concept is developed if borrowed from data modeling research. The framework allows for property inheritance among classes that are not necessarily IS-A related. >

An application-transparent, platform-independent approach to rollback-recovery for mobile agent systems

This paper proposes a new approach to rollback-recovery for mobile agent systems, and describes its implementation in the MESSENGERS mobile agents system. The used checkpointing method allows the implementation of a space and time efficient, user-transparent rollback-recovery in heterogeneous distributed environments. Together with an efficient non-blocking system snapshot algorithm this checkpointing method is an attractive choice for implementing a rollback-recovery mechanism in a mobile agent system, because it exploits features specific to such systems during the recovery. This paper also presents an optimization technique, called concurrent checkpointing, that increases the effectiveness of the proposed rollback-recovery mechanism.

Iterative grid-based computing using mobile agents

We describe an environment for the distributed solution of iterative grid-based applications. The environment is built using the MESSENGERS mobile agent system. The main advantage of paradigm-oriented distributed computing is that the user only needs to specify the application-specific sequential code, while the underlying infrastructure takes care of the parallelization and distribution. The two paradigms discussed in this papers are: the finite difference method, and individual-based simulation. These paradigms present some interesting challenges, both in terms of performance (because they require frequent synchronized communication between nodes) and in terms of repeatability (because the mapping of the user space onto the network may change due to load balancing or due to changes in the underlying logical network). We describe their use, implementation, and performance within a mobile agent-based environment.

Messages versus Messengers in Distributed Programming

Messengers are autonomous objects, each capable of navigating through the underlying network and performing various tasks at each node. Messengers applications are written usingnavigationalcommands rather than thesend/receiveprimitives of conventional message-passing approaches. In this paper we contrast the two programming styles. From a software engineering viewpoint, the navigational style generally results in a smaller semantic gap between abstract algorithm descriptions and their actual implementations, which makes programs easier to construct, understand, and maintain. In terms of performance, Messengers programs are highly competitive with message-passing. We demonstrate these advantages using two concrete applications programmed using Messengers and PVM.

A data-driven model for a subset of logic programming

There is a direct correspondence between semantic networks and a subset of logic programs, restricted only to binary predicates. The advantage of the latter is that it can describe not only the nodes and arcs comprising a semantic net, but also the data-retrieval operations applied to such nets. The main objective of this paper is to present a data-driven model of computation that permits this subset of logic programs to be executed on a highly parallel computer architecture. We demonstrate how logic programs may be converted into collections of data-flow graphs in which resolution is viewed as a process of finding matches between certain graph templates and portions of the data-flow graphs. This graph fitting process is carried out by messages propagating asynchronously through the data-flow graph; thus computation is entirely data driven, without the need for any centralized control and centralized memory. This permits a potentially large number of independent processing elements to cooperate in solving a given query.