Kenneth Nitz

On the feasibility of deploying cell anomaly detection in operational cellular networks

The Self-Organizing Networks (SON) concept includes the functional area known as self-healing, which aims to automate the detection and diagnosis of, and recovery from, network degradations and outages. In this paper, we build on our previous work [19] and study the feasibility of an operational deployment of an adaptive ensemble-method framework for modeling cell behavior. The framework uses Key Performance Indicators (KPIs) to determine cell-performance status. Our results, generated using real cellular network data, show that the computational overhead and the detection delay are sufficiently low for practical use of our methods to perform cell anomaly detection in operational networks.

Conflict negotiation among personal calendar agents

We will demonstrate distributed conflict resolution in the context of personalized meeting scheduling. The demonstration will show how distributed constraint optimization can be used to facilitate interaction between cognitive agents and their users. The system is part of the CALO personal cognitive assistant that will also be explored during the demonstration.

An image-based mail facing and orientation system for enhanced postal automation

When mixed mail enters a postal facility, it must firstbe faced and oriented so that the address is readable bymail processors.Existing USPS systems face and orientdomestic mail by searching for flourescing indicia oneach mail piece.However, stamps on foreign-originatedmail do not flouresce, so the processing systems cannotsort foreign mail.Furthermore, even the facing ofdomestic mail is subject to processing problems such asmechanical malfunction and misplaced or partiallyflourescing indicia, which cause a significant fraction ofmail to be rejected.Previously, rejected domestic mailand all foreign mail had to be faced and oriented byhand, thus increasing mail processing costs for the USPS.This work aims to eliminate these costs by developing animage-based facing system that processes scannedimages of both sides of each envelope and automaticallyfaces and orients it in real time.TheUSPS began todeploy this technology nationwide in November 2002.

DCAD: Dynamic Cell Anomaly Detection for operational cellular networks

The Self-Organizing Networks (SON) concept includes the functional area known as self-healing, which aims to automate the detection and diagnosis of, and recovery from, network degradations and outages. In this paper, we present Dynamic Cell Anomaly Detection (DCAD), a tool that implements an adaptive ensemble method for modeling cell behavior [5], [6]. DCAD uses Key Performance Indicators (KPIs) from real cellular networks to determine cell-performance status; enables KPI data exploration; visualizes anomalies; reduces the time required for successful detection of anomalies; and accepts user input.

Demo: SONVer: SON verification for operational cellular networks

The Self-Organizing Networks (SON) concept includes the functional area known as self-healing, which aims to automate the detection and diagnosis of, and recovery from, network degradations and outages. Changes to the configuration management (CM) parameters for network elements could be a cause for degraded network performance and stability; hence, the verification of their effects becomes crucial. In this paper, we present SONVer, a tool that performs SON verification, using anomaly detection and diagnosis techniques that operate within a specified spatial scope larger than an individual cell. SONVer automatically classifies the state of the network in the presence of CM changes, indicating the root cause for anomalous conditions. SONVer uses Key Performance Indicators (KPIs) and CM history from real cellular networks to determine the state of the network; visualize anomalies at a large scale; and identify the causes of anomalies and the group of cells that were affected.

Real-time display and development of an aerometric data base for a field experiment

Abstract An innovative data center responsible for collecting, displaying, and analyzing near real-time meteorological and air quality measurements from a variety of sources was operated in Camarillo, California, during September–October 1985. This data center was part of a multi-million dollar study conducted for the South Central Coast Cooperative Monitoring Program sponsored by the Western Oil and Gas Association, a consortium of petroleum and fuel-producing organizations, to gain a better understanding of air quality conditions in the southern California coastal areas, and to produce a comprehensive data base for which coastal air quality models could be developed and evaluated. Led by the Atmospheric Science Center of SRI International, the program included a large number of contractor organizations responsible for collecting air quality measurements from land, sea, and air instrumentation for future analysis and model development. The data center integrated near real-time air quality and meteorological data with weather services forecasts to develop day-to-day environmental predictions governing the data collection activities.