Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...
In pervasive computing environments, conditions are highly variable and resources are limited. In order to meet the needs of applications, systems must adapt dynamically to changi...
Farshad A. Samimi, Philip K. McKinley, Seyed Masou...
Real-time event stream processing (RT-ESP) applications must synchronize continuous data streams despite fluctuations in resource availability. Satisfying these needs of RT-ESP ap...
Joe Hoffert, Douglas C. Schmidt, Aniruddha S. Gokh...
Today, there is an increasing demand to share data with complex data types (e.g., multi-dimensional) over large numbers of data sources. One of the key challenges is sharing these ...
There are many application classes where the users are flexible with respect to the output quality. At the same time, there are other constraints, such as the need for real-time ...