Positions for the China Scholarship Council
The Distributed Systems Lab (LSD) offers positions for students funded partially by the China Scholarship Council.
The offered global salary is 1300 euros/month (300 euros/month extra over the scholarship provided by the Council).
The Distributed Systems Lab excels at distributed systems research, both theory and practice, with emphasis on real problems that can advance the state of the art from a scientific point of view, but also from an industrial point of view. This approach allows to have a high potential impact in both scientific and industrial terms. The lab has a strong participation in international projects such as European projects. We cooperate in these projects with the research lab of the leading industry in computer science such as IBM, Yahoo, SAP, INTEL, etc. Students doing the PhD in the lab have good chances of getting positions in top computer science industry.
The research lines that can be conducted under grants from the China Scholarship Council are the following:
- Cloud computing PaaS. The lab is research of Platforms as a Service that provide transactional multi-tier runtimes (e.g. like J2EE or .NET) exhibiting scalability and elasticity. Current approaches sacrifice consistenty to attain large levels of scalability. We are interested in attaining high scalability, but without sacrificing consistency. We coordinate a European project on this topic in which Yahoo and SAP participate.
- Cloud databases. The has performed leading research in the area of scalable databases. The lab is now seeking how to extend its experience on scalable databases to get elastic cloud databases. This research is performed in the context of the 4CaaSt European project led by Telefonica and in which top industry participates such as Nokia and Ericsson participates.
- Cloud data streaming. The lab is researching how to process massive data flows with continuous queries under the data streaming paradigm. The lab is developing a parallel-distributed cloud data streaming engine able to correlate and aggregate millions of events per second. The research to be conducted in this line is on one hand related to the applications of data streaming such as the processing of the output of large sensor networks (e.g. vehicular networks such as instrumented roads), financial applications (automatic trading), physical security applications, smart grid applications (forecasting consumption, diagnosing failures in real-time, etc.), etc. On the other hand, a new generation data streaming engine, highly efficient will be developed that will be able to process events without having to translate
- Elastic large scale security. Current Security Information and Event Management Systems (SIEMs) are centralized and when distributed they perform disjoint computations. This results in an inherent lack of scalability. In this research line related to the MASSIF European project a new generation SIEM will be built based on data streaming technology. Rules of current SIEMs will be translated into continuous queries with auto-scaling. Correlation of events will be made not within layers, but across layers (security and network devices, SOA servers, etc.).
- Autonomic large scale visualization. Today in cloud computing the number of nodes, applications and services that should be monitored are very high. Visualizing this large scale information is a challenge, especially rendering it in such a way that engineers can spot anomalies and the reason behind them. The research in this area will look into anomaly detection protocols and large scale visualization algorithms that combined will enable to highlight automatically anomalies in running systems within the visualization. Techniques that will adjust the level of detail automatically will develop providing increasing level of details to the areas of higher interest and decreasing levels of details to the areas with lower level of interest.
Interested applicants should contact the lab co-directors:
- Ricardo Jimenez-Peris (rjimenez@fi.upm.es)
- Marta Patiño-Martinez (mpatino@fi.upm.es)
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