September 01, 2017

Empowering Stream Processing through Edge Clouds

  • Janssens N.
  • Luis Veiga
  • Sergio Esteves
  • Theeten B.

CHive is a new streaming analytics platform to run distributed SQL-style queries on edge clouds. However, CHive is currently tightly coupled to a specific stream processing system (SPS), Apache Storm. In this paper we address the decoupling of the CHive query planner and optimizer from the runtime environment, and also extend the latter to support pluggable runtimes through a common API. As runtimes, we currently support Apache Spark and Flink streaming. The fundamental contribution of this paper is to assess the cost of employing inter-stream parallelism in SPS. Experimental evaluation indicates that we can enable popular SPS to be distributed on edge clouds with stable overhead in terms of throughput.

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Recent Publications

August 09, 2017

A Cloud Native Approach to 5G Network Slicing

  • Francini A.
  • Miller R.
  • Sharma S.

5G networks will have to support a set of very diverse and often extreme requirements. Network slicing offers an effective way to unlock the full potential of 5G networks and meet those requirements on a shared network infrastructure. This paper presents a cloud native approach to network slicing. The cloud ...

August 01, 2017

Modeling and simulation of RSOA with a dual-electrode configuration

  • De Valicourt G.
  • Liu Z.
  • Violas M.
  • Wang H.
  • Wu Q.

Based on the physical model of a bulk reflective semiconductor optical amplifier (RSOA) used as a modulator in radio over fiber (RoF) links, the distributions of carrier density, signal photon density, and amplified spontaneous emission photon density are demonstrated. One of limits in the use of RSOA is the lower ...

July 12, 2017

PrivApprox: Privacy-Preserving Stream Analytics

  • Chen R.
  • Christof Fetzer
  • Le D.
  • Martin Beck
  • Pramod Bhatotia
  • Thorsten Strufe

How to preserve users' privacy while supporting high-utility analytics for low-latency stream processing? To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream processing. PRIVAPPROX provides three properties: (i) Privacy: zero-knowledge privacy (ezk) guarantees for users, a privacy bound tighter ...