To manage load on large and dynamic networks we have developed Autonomous Mobile Programs (AMPs) that periodically use a cost model to decide where to execute. A disadvantage of d...
Batched stream processing is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired...
Bingsheng He, Mao Yang, Zhenyu Guo, Rishan Chen, B...
Grid applications often need to distribute large amounts of data efficiently from one cluster to multiple others (multicast). Existing methods usually arrange nodes in optimized t...
The MapReduce framework is increasingly being used to analyze large volumes of data. One important type of data analysis done with MapReduce is log processing, in which a click-st...
Spyros Blanas, Jignesh M. Patel, Vuk Ercegovac, Ju...
Parallel dataflow programming frameworks such as Map-Reduce are increasingly being used for large scale data analysis on computing clouds. It is therefore becoming important to a...