813161
Collaborative Multimedia Systems: Synthesis of Media Objects
When a group {/1,..., l/sub n/} of individuals wishes to collaboratively construct a complex multimedia document, the first requirement is that they be able to manipulate media-objects created by one another. For instance, if individual L/sub j/ wishes to access some media objects present at participant l/sub k/'s site, he must be able to: 1) retrieve this object from across the network, 2) ensure that the object is in a form that is compatible with the viewing/editing resources he has available at his node, and 3) ensure that the object has the desired quality (such as image size and resolution). Furthermore, he must be able to achieve these goals at the lowest possible cost. In this paper, we develop a theory of media objects, and present optimal algorithms for collaborative object sharing/synthesis of the sort envisaged above. We then extend the algorithms to incorporate quality constraints (such as image size) as well as distribution across multiple nodes. The theoretical model is validated by an experimental implementation that supports the theoretical results.
18315365
Towards a theory of collaborative multimedia
We develop a theory of media objects, and present optimal algorithms for collaborative synthesis of media objects. We then extend the algorithms to incorporate quality constraints (such as image size) as well as distribution across multiple nodes. The theoretical model is validated by an experimental implementation that supports the theoretical results.
629579
Query caching and optimization in distributed mediator systems
Query processing and optimization in mediator systems that access distributed non-proprietary sources pose many novel problems. Cost-based query optimization is hard because the mediator does not have access to source statistics information and furthermore it may not be easy to model the source's performance. At the same time, querying remote sources may be very expensive because of high connection overhead, long computation time, financial charges, and temporary unavailability. We propose a cost-based optimization technique that caches statistics of actual calls to the sources and consequently estimates the cost of the possible execution plans based on the statistics cache. We investigate issues pertaining to the design of the statistics cache and experimentally analyze various tradeoffs. We also present a query result caching mechanism that allows us to effectively use results of prior queries when the source is not readily available. We employ the novel invariants mechanism, which shows how semantic information about data sources may be used to discover cached query results of interest.
19021462
Combining Knowledge Bases Consisting of First Order Theories
Consider the construction of an expert system by encoding the knowledge of different experts. Suppose the knowledge provided by each expert is encoded into a knowledge base. Then the process of combining the knowledge of these different experts is an important and non-trivial problem. We study this problem here when the expert systems are considered to be first order theories. We present techniques for resolving inconsistencies in such knowledge bases. We also provide algorithms for implementing these techniques.
18059666
IMPACT: the interactive Maryland platform for agents collaborating together
We describe a platform called IMPACT to support multiagent interactions. The platform provides a set of servers (yellow pages, thesaurus, registration, type, and interface) that facilitate agent interoperability in an application independent manner. In IMPACT agents have an associated set of service descriptions, specifying the services they provide. We develop an HTML-like language for such service descriptions. When an agent wishes to identify another agent that provides a service, the requested service must be matched, using a metric approach, against existing service descriptions. We provide a formal framework within which this may be done, and develop algorithms to compute the k nearest matches, as well as all matches within a given distance from the requested service. We report on experiments evaluating our algorithms with large data sets.