December 22, 2016

A robust algorithm for anomaly detection in mobile networks

  • Bodrog L.
  • Kajo M.
  • Kocsis S.
  • Schultz B.

Self-Organizing Network (SON) functions aim at automating mobile network management in three key areas: self-configuration, self-optimization and self-healing. This paper's focus is self-healing, the detection of outages and other faults in the network. The first step in every healing process is the detection of abnormal operation, also called anomaly or outlier detection. In this paper we propose a simple but effective statistics-based method for anomaly detection in mobile networks, using performance and failure Key Performance Indicators (KPI) to detect anomalies in cell behavior. The algorithm is aimed to be easy to setup, and is computationally less demanding than machine learning based algorithms, making it suitable for large networks or environments with low processing power. Results are presented on real mobile network data showing that the detector yields good results, outperforming basic failure indicator mechanisms.

View Original Article

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 ...