Accurate Event Distribution Monitoring for Very Large Wireless Systems

  • Bejerano Y.
  • Raman C.
  • Yu C.

In a network of large number of devices, we address the problem of estimation of the probability distribution of quantities measured by the set of nodes in a geographical area. Queries are sent to the nodes by the network with the reporting condition and reporting probability. Nodes that satisfy the reporting condition report the measurement with the specified probability. It is shown that the probability distribution of the measurement can be estimated accurately with bounded number of reports, by careful selection of reporting conditions and reporting probability. A general framework for designing the report rates is developed. Simple expressions for distance measures between the estimated and the true distribution is provided. Based on the concepts that are developed, we present a two-phase process and an iterative process for inferring the measurements' distribution in the cases of one time querying as well as periodic querying.

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 ...