Objectives

The objective of this project is to investigate how internal and external types of traffic can be efficiently handled in a parallel distributed system like Apache Flink: (i) with different levels of parallelization, task jobs may communicate in the same node using shared memory or between different working nodes using files or some sort of network connection. Strategies to handle this type of traffic, such as chaining tasks, stateless and stateful tasks and different output buffers sizes have not yet been applied in a dynamic, mobile edge environment; (ii) The analysis of massive amount of data from a high number of streams is a difficult challenge for real-time data stream processing, in particular under external constraints and problems inherent to mobile edge computing, such as intermittent connectivity, network bandwidth, synchronization of shared state in mobile environments, fault tolerance and robust mechanisms when connectivity cannot be estimated.

Expected results

  • Review of the state of art and analysis of parallel distributed strategies such as chaining tasks, stateless and stateful tasks and different output buffers sizes, as possibilities of implementation in a mobile edge environment.
  • Design and implementation of strategies in Apache Flink, taking into account external constraints and problems inherent to mobile edge computing.
  • Design of a use case or application suitable to test the implemented improvements in Apache Flink.
  • Exhaustive testing under real time conditions of load and traffic.

 

Location

TU Berlin is an internationally renowned research-intensive university dedicated to promoting science and technology for the benefit of broader society and committed to the principles of sustainability and research for peaceful purposes. The DIMA group is the original author of Apache Flink.

Planned secondments

14 months at Elastisys (Umeå, Sweden); 7 months at Las Naves (Valencia, Spain).

Conditions

Please write your application in English, as it will be examined by multiple people in different European countries. Please do not apply to more than two positions within the FogGuru project.

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