Large-scale datacenters that handle continuous data streams require scalable and flexible communication infrastructure. The scalability of publish/subscribe (pub/sub) middleware coupled with fine-grained quality-of-service (QoS) support and adaptive transport protocols constitutes a promising area of research to address the challenges of these types of large-scale datacenters. This paper descri...

The recording, multimodal analysis and archiving of meetings introduce new challenges for research in multimedia information management. Meetings involve multiple media that can be aligned together. This requires a global annotation framework. In particular, meetings often deal with documents, either projected or discussed, which can be aligned with the audio and video streams. This article pre...

The work described in this paper defines a Bayesian framework to use noisy, but redundant data from multiple sensor streams and incorporate it with the contextual and domain knowledge that is provided by both the physical constraints imposed by the local environment where the sensors are located and by the people that are involved in the surveillance tasks. The paper also presents the

The SenseWorld DataNetwork framework addresses the issue of sharing and manipulating multiple data streams among different media systems in a heterogenous interactive performance environment. It is intended to facilitate the creation, rehearsal process and performance practice of collaborative interactive media art works, by making the sharing of data (from sensors or internal processes) betwee...

Interest in large-scale sensor networks for both civilian and military applications is burgeoning. The deployment of such networks will require new approaches in resource discovery, query processing and data routing. This paper presents a framework and some analytic results for query satisfaction and data routing in networks consisting of clients, sensors and data filtering/fusion servers. In t...

Many data sets occur as unaggregated data sets, where multiple data points are associated with each key. In the aggregate view of the data, the weight of a key is the sum of the weights of data points associated with the key. Examples are measurements of IP packet header streams, distributed data streams produced by events registered by sensor networks, and Web page or multimedia requests to co...