Information-Centric Networks for Distributed Computing

  • Pianese F.

Information-centric Networking (ICN), a paradigm that operates on self-contained named data, naturally extends the role and capabilities of in-network elements. The flexible naming of ICN can be used to convey instructions for content routers to perform a target computation. In this paper, we consider ICN's potential of integrating distributed computing frameworks with the network layer in datacenter scenarios. By representing computation requests as named data, we aim to seamlessly integrate processing - executing a set of operations on a target input to generate the expected output - and storage - retrieving data and the cached output of previous processing requests - with the network, enabling computations to be distributed among nodes on the request's network path. Here we consider simple examples of distributed computation models that can be supported using an ICN syntax. We discuss mechanisms by which appropriate naming can oversee the distribution of a computation across network topologies, present the advantages of ICN integration, and survey the open research challenges.

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
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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 ...