Load management and high availability in the Medusa distributed stream processing system
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
A dynamic time warping approach to real-time activity recognition for food preparation
AmI'10 Proceedings of the First international joint conference on Ambient intelligence
| Hi-index | 0.00 |
Stream-processing systems inevitably face unpredictable variations in incoming event loads. One way of handling this without affecting end-to-end performance metrics, will be to dynamically distribute event-processing on multiple computers and thus avail compute power for optimal performance. More precisely, data streams are processed in part or in parallel on multiple computers connected by a high bandwidth network. The number of computers being used is to be varied dynamically to cope with input load fluctuations. This paper uses data from ambient kitchen to make a preliminary assessment of performance advantages by distribution of real-time data stream processing. The motivation is to leverage cloud computing for optimal realtime event processing.