skip to main content


Title: Efficient Data Diffusion and Elimination Control Method for Spatio-Temporal Data Retention System
With the development and spread of Internet of Things technologies, various types of data for IoT applications can be generated anywhere and at any time. Among such data, there are data that depend heavily on generation time and location. We define these data as spatiotemporal data (STD). In previous studies, we proposed a STD retention system using vehicular networks to achieve the “Local production and consumption of STD” paradigm. The system can quickly provide STD for users within a specific location by retaining the STD within the area. However, this system does not take into account that each type of STD has different requirements for STD retention. In particular, the lifetime of STD and the diffusion time to the entire area directly influence the performance of STD retention. Therefore, we propose an efficient diffusion and elimination control method for retention based on the requirements of STD. The results of simulation evaluation demonstrated that the proposed method can satisfy the requirements of STD, while maintaining a high coverage rate in the area.  more » « less
Award ID(s):
1818884
NSF-PAR ID:
10289949
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
IEICE transactions on communications
Volume:
E104-B
ISSN:
0916-8516
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    Producing high-resolution near-real-time forecasts of fire behavior and smoke impact that are useful for fire and air quality management requires accurate initialization of the fire location. One common representation of the fire progression is through the fire arrival time, which defines the time that the fire arrives at a given location. Estimating the fire arrival time is critical for initializing the fire location within coupled fire-atmosphere models. We present a new method that utilizes machine learning to estimate the fire arrival time from satellite data in the form of burning/not burning/no data rasters. The proposed method, based on a support vector machine (SVM), is tested on the 10 largest California wildfires of the 2020 fire season, and evaluated using independent observed data from airborne infrared (IR) fire perimeters. The SVM method results indicate a good agreement with airborne fire observations in terms of the fire growth and a spatial representation of the fire extent. A 12% burned area absolute percentage error, a 5% total burned area mean percentage error, a 0.21 False Alarm Ratio average, a 0.86 Probability of Detection average, and a 0.82 Sørensen’s coefficient average suggest that this method can be used to monitor wildfires in near-real-time and provide accurate fire arrival times for improving fire modeling even in the absence of IR fire perimeters. 
    more » « less
  2. Data privacy requirements are a complex and quickly evolving part of the data management domain. Especially in Healthcare (e.g., United States Health Insurance Portability and Accountability Act and Veterans Affairs requirements), there has been a strong emphasis on data privacy and protection. Data storage is governed by multiple sources of policy requirements, including internal policies and legal requirements imposed by external governing organizations. Within a database, a single value can be subject to multiple requirements on how long it must be preserved and when it must be irrecoverably destroyed. This often results in a complex set of overlapping and potentially conflicting policies. Existing storage systems are lacking sufficient support functionality for these critical and evolving rules, making compliance an underdeveloped aspect of data management. As a result, many organizations must implement manual ad-hoc solutions to ensure compliance. As long as organizations depend on manual approaches, there is an increased risk of non-compliance and threat to customer data privacy. In this paper, we detail and implement an automated comprehensive data management compliance framework facilitating retention and purging compliance within a database management system. This framework can be integrated into existing databases without requiring changes to existing business processes. Our proposed implementation uses SQL to set policies and automate compliance. We validate this framework on a Postgres database, and measure the factors that contribute to our reasonable performance overhead (13% in a simulated real-world workload). 
    more » « less
  3. null (Ed.)
    Abstract. Stratospheric sulfate aerosol geoengineering is a proposed methodto temporarily intervene in the climate system to increase the reflectance of shortwave radiation and reduce mean global temperature. In previous climate modeling studies, choosing injection locations for geoengineering aerosols has, thus far, only utilized the average dynamics of stratospheric wind fields instead of accounting for the essential role of time-varying material transport barriers in turbulent atmospheric flows. Here we conduct the first analysis of sulfate aerosol dispersion in the stratosphere, comparing what is now a standard fixed-injection scheme with time-varying injection locations that harness short-term stratospheric diffusion barriers. We show how diffusive transport barriers can quickly be identified, and we provide an automated injection location selection algorithm using short forecast and reanalysis data. Within the first 7 d days of transport, the dynamics-based approach is able to produce particle distributions with greater global coverage than fixed-site methods with fewer injections. Additionally, this enhanced dispersion slows aerosol microphysical growth and can reduce the effective radii of aerosols up to 200–300 d after injection. While the long-term dynamics of aerosol dispersion are accurately predicted with transport barriers calculated from short forecasts, the long-term influence on radiative forcing is more difficult to predict and warrants deeper investigation. Statistically significant changes in radiative forcing at timescales beyond the forecasting window showed mixed results, potentially increasing or decreasing forcing after 1 year when compared to fixed injections. We conclude that future feasibility studies of geoengineering should consider the cooling benefits possible by strategically injecting sulfate aerosols at optimized time-varying locations. Our method of utilizing time-varying attracting and repelling structures shows great promise for identifying optimal dispersion locations, and radiative forcing impacts can be improved by considering additional meteorological variables. 
    more » « less
  4. Abstract

    Roll-to-Roll (R2R) printing techniques are promising for high-volume continuous production of substrate-based products, as opposed to sheet-to-sheet (S2S) approach suited for low-volume work. However, meeting the tight alignment tolerance requirements of additive multi-layer printed electronics specified by device resolution that is usually at micrometer scale has become a major challenge in R2R flexible electronics printing, preventing the fabrication technology from being transferred from conventional S2S to high-speed R2R production. Print registration in a R2R process is to align successive print patterns on the flexible substrate and to ensure quality printed devices through effective control of various process variables. Conventional model-based control methods require an accurate web-handling dynamic model and real-time tension measurements to ensure control laws can be faithfully derived. For complex multistage R2R systems, physics-based state-space models are difficult to derive, and real-time tension measurements are not always acquirable. In this paper, we present a novel data-driven model predictive control (DD-MPC) method to minimize the multistage register errors effectively. We show that the DD-MPC can handle multi-input and multi-output systems and obtain the plant model from sensor data via an Eigensystem Realization Algorithm (ERA) and Observer Kalman filter identification (OKID) system identification method. In addition, the proposed control scheme works for systems with partially measurable system states.

     
    more » « less
  5. null (Ed.)
    Abstract This study presents a new method, called the Radial Interpolation Method, to interpolate data characterized by an approximately radial pattern around a relatively constrained central zone, such as the ground deformation patterns shown in many active volcanic areas. The method enables the fast production of short-term deformation maps on the base of spatially sparse ground deformation measurements and can provide uncertainty quantification on the interpolated values, fundamental for hazard assessment purposes and deformation source reconstruction. The presented approach is not dependent on a priori assumptions about the geometry, location and physical properties of the source, except for the requirement of a locally radial pattern, i.e., allowing multiple centers of symmetry. We test the new method on a synthetic point source example, and then, we apply the method to selected time intervals of real geodetic data collected at the Campi Flegrei caldera during the last 39 years, including examples of leveling, Geodetic Precise Traversing measurements and Global Positioning System. The maps of horizontal displacement, calculated inland, show maximum values lying along a semicircular annular region with a radius of about 2–3 km in size. This semi-annular area is marked by mesoscale structures such as faults, sand dikes and fractures. The maps of vertical displacement describe a linear relation between the maximum vertical uplift measured and the volume variation. The multiplicative factor in the linear relation is about 0.3 × 10 6  m 3 /cm if we estimate the proportion of the Δ V that is captured by the GPS network onland and we use this to estimate the full Δ V . In this case, the 95% confidence interval on K because of linear regression is ± 5%. Finally, we briefly discuss how the new method could be used for the production of short-term vent opening maps on the base of real-time geodetic measurements of the horizontal and vertical displacements. 
    more » « less