No abstract

International audienceDistributed stream processing engines continuously execute series of operators on data streams. Horizontal scaling is achieved by deploying multiple instances of each operator in order to process data tuples in parallel. As the application is distributed on an increasingly high number of servers, the likelihood that the stream is sent to a different server for each operator increases. This is particularly important in the case of stateful applications that rely on keys to deterministically route messages to a specific instance of an operator. Since network is a bottleneck for many stream applications, this behavior significantly degrades their performance. Our objective is to improve stream locality for stateful stream processing applications. We propose to analyse traces of the application to uncover correlations between the keys used in successive routing operations. By assigning correlated keys to instances hosted on the same server, we significantly reduce network consumption and increase performance while preserving load balance. Furthermore, this approach is executed online, so that the assignment can automatically adapt to changes in the characteristics of the data. Data migration is handled seamlessly with each routing configuration update. We implemented and evaluated our protocol using Apache Storm, with a real workload consisting of geo-tagged Flickr pictures as well as Twitter publications. Our results show a significant improvement in throughput

No abstract

In the coming years, cloud environments will increasingly face energy saving issues. While consolidating the virtual machines running in a cloud is a well-accepted solution to reduce the energy consumption, ensuring the scalability of the consolidation service remains a challenging issue. In this paper, we propose an elastic consolidation service that scales according to the dynamic needs of the cloud environment. Our proposition is based on (i) virtualizing the consolidation manager, (ii) partitioning the consolidation work and (iii) regulating the consolidation scalability through an autonomic control loop. Our proposition has been tested and validated through several experiments.