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Found 16 papers, 4 papers with code
LEAD: Towards Learning-Based Equity-Aware Decarbonization in Ridesharing Platforms
Extensive experiments based on a real-world ride-sharing dataset show that LEAD improves fairness by 2$\times$ when compared to emission-aware ride-assignment and reduces emissions by 70% while ensuring fairness within 66% of the fair baseline.
CarbonClipper: Optimal Algorithms for Carbon-Aware Spatiotemporal Workload Management
We formalize this as an online problem called spatiotemporal online allocation with deadline constraints ($\mathsf{SOAD}$), in which an online player completes a workload (e. g., a batch compute job) by moving and scheduling the workload across a network subject to a deadline $T$.
LACS: Learning-Augmented Algorithms for Carbon-Aware Resource Scaling with Uncertain Demand
The task is to dynamically scale resources (e. g., the number of servers) assigned to a job of unknown length such that it is completed before a deadline, with the objective of reducing the carbon emissions of executing the workload.
Chasing Convex Functions with Long-term Constraints
We introduce and study a family of online metric problems with long-term constraints.
SODA: Protecting Proprietary Information in On-Device Machine Learning Models
The growth of low-end hardware has led to a proliferation of machine learning-based services in edge applications.
Online Conversion with Switching Costs: Robust and Learning-Augmented Algorithms
We introduce competitive (robust) threshold-based algorithms for both the minimization and maximization variants of this problem, and show they are optimal among deterministic online algorithms.
SleepMore: Inferring Sleep Duration at Scale via Multi-Device WiFi Sensing
In this paper, we propose SleepMore, an accurate and easy-to-deploy sleep-tracking approach based on machine learning over the user's WiFi network activity.
Sustainable Computing -- Without the Hot Air
This growth will translate to exponential growth in computing's energy consumption unless improvements in its energy-efficiency can outpace increases in its demand.
FlowSense: Monitoring Airflow in Building Ventilation Systems Using Audio Sensing
With a motivation to monitor airflow from building ventilation systems through commodity sensing devices, we present FlowSense, a machine learning-based algorithm to predict airflow rate from sensed audio data in indoor spaces.
WiSleep: Inferring Sleep Duration at Scale Using Passive WiFi Sensing
With a motivation to expand sleep monitoring capabilities at a large scale and contribute sleep data to public health understanding, we present Wisleep, a system for inferring sleep duration using smartphone network connections that are passively sensed from WiFi infrastructure.
Preserving Privacy in Personalized Models for Distributed Mobile Services
We present Pelican, a privacy-preserving personalization system for context-aware mobile services that leverages both device and cloud resources to personalize ML models while minimizing the risk of privacy leakage for users.
WattScale: A Data-driven Approach for Energy Efficiency Analytics of Buildings at Scale
In this paper, we present \texttt{WattScale}, a data-driven approach to identify the least energy-efficient buildings from a large population of buildings in a city or a region.
SunDown: Model-driven Per-Panel Solar Anomaly Detection for Residential Arrays
There has been significant growth in both utility-scale and residential-scale solar installations in recent years, driven by rapid technology improvements and falling prices.
WiFiTrace: Network-based Contact Tracing for Infectious Diseases Using Passive WiFi Sensing
Contact tracing is a well-established and effective approach for the containment of the spread of infectious diseases.
Networking and Internet Architecture Computers and Society
Peak Forecasting for Battery-based Energy Optimizations in Campus Microgrids
Battery-based energy storage has emerged as an enabling technology for a variety of grid energy optimizations, such as peak shaving and cost arbitrage.
Empirical Characterization of Mobility of Multi-Device Internet Users
Also, prior work has analyzed mobility at the spatial scale of the underlying mobile dataset and has not analyzed mobility characteristics at different spatial scales and its implications on system design.
Computers and Society
