Network-Aware Workload Scheduling for Scalable Linked Data Stream Processing

Using our approach with a semantic knowledge base and Linked Data prosuming Web APIs according to SPARQL pattern, pre-processing pipelines of wrapped MITK command line tools are

Figure 10 represents a test to measure the execution time in the wide tree data set using negative queries.. We noticed that execution time increases with the increasing of the data

We configure KerA similarly to Kafka: the number of active groups is 1 so the number of streamlets gives a number of active groups equal to the number of partitions in Kafka (one

In this work, we propose a general-purpose Virtual Channel allocation technique for wormhole switching with priority pre-emption which is able to schedule soft real-time applications

If the state of the Markov chain were known at each time step, the probability could be estimated thanks to the total number of infected and the length of the epidemic.. But given

Because of that metagraph processing framework can read data stored in the form of textual predicate representation and import it into flat graph data structure handled by

We have shown that our solution and Linked Data can be applied successfully in a real world scenario with significant advantages over established Open Data solutions, e.g., a

The algorithm uses different types of local user data: profile, friendship graph, posts, and social interactions (likes, comments, tags).. Ex- perimental evaluation using