Down for Failure: Active Power Status Monitoring

TL;DR

This paper proposes an innovative method for detecting power outages by monitoring residential IP address availability, achieving high accuracy and offering a complementary tool to traditional power outage detection methods.

Contribution

It introduces a novel approach using residential IP monitoring to identify power outages, demonstrating effectiveness during hurricane-induced outages and analyzing accuracy versus false alarms.

Findings

Achieved 90% detection accuracy during Hurricane Florence outages.

Residential IP availability correlates strongly with regional power status.

Method can detect outages at state and county levels.

Abstract

Despite society's strong dependence on electricity, power outages remain prevalent. Standard methods for directly measuring power availability are complex, often inaccurate, and are prone to attack. This paper explores an alternative approach to identifying power outages through intelligent monitoring of IP address availability. In finding these outages, we explore the trade-off between the accuracy of detection and false alarms. We begin by experimentally demonstrating that static, residential Internet connections serve as good indicators of power, as they are mostly active unless power fails and rarely have battery backups. We construct metrics that dynamically score the reliability of each residential IP, where a higher score indicates a higher correlation between that IP's availability and its regional power. We monitor specifically selected subsets of residential IPs and evaluate the accuracy with which they can indicate current county power status. Using data gathered during the power outages caused by Hurricane Florence, we demonstrate that we can track power outages at different granularities, state and county, in both sparse and dense regions. By comparing our detection with the reports gathered from power utility companies, we achieve an average detection accuracy of $90\%$, where we also show some of our false alarms and missed outage events could be due to imperfect ground truth data. Therefore, our method can be used as a complementary technique of power outage detection.