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Abstract. Everybody has to coordinate several tasks everyday, usually in a manual manner. Recently, the concept of Task Automation Services has been introduced to automate and personalize the task coordination problem. Several user centered platforms and applications have arisen in the last years, that let their users configure their very own automations based on third party services. In this paper, we propose a new system architecture for Task Automation Services in a heterogeneous mobile, smart devices, and cloud services environment. Our architecture is based on the novel idea to employ distributed Complex Event Processing to implement innovative mixed execution profiles. The major advantage of the approach is its ability to incorporate context-awareness and real-time coordination in Task Automation Services.

This paper compares the efficiency of two implementations of the PageRank algorithm, one using Hadoop's MapReduce and the other Giraph's Pregel. The implementations are evaluated against CPU usage, CPU I/O wait time, memory usage, and execution time. The result of the evaluation is that Giraph outperforms Hadoop.