A self-managing wide-area data streaming service

2007 ◽  
Vol 10 (4) ◽  
pp. 365-383 ◽  
Author(s):  
Viraj Bhat ◽  
Manish Parashar ◽  
Hua Liu ◽  
Nagarajan Kandasamy ◽  
Mohit Khandekar ◽  
...  
Keyword(s):  
Wide Area ◽  
Data Streaming ◽  
Streaming Service ◽  
Area Data

A Self-Managing Wide-Area Data Streaming Service using Model-based Online Control

2006 ◽  
Author(s):  
Viraj Bhat ◽  
Manish Parashar ◽  
Mohit Khandekar ◽  
Nagarajan Kandasamy ◽  
Scott Klasky
Keyword(s):  
Online Control ◽  
Wide Area ◽  
Data Streaming ◽  
Model Based ◽  
Streaming Service ◽  
Area Data

Development and field experiments of a human-portable towed ROV for high-speed and wide area data acquisition

2020 ◽  
Author(s):  
Norimitsu Sakagami ◽  
Keita Hirayama ◽  
Ryo Taba ◽  
Shota Kobashigawa ◽  
Seita Arashiro ◽  
...  
Keyword(s):  
Data Acquisition ◽  
High Speed ◽  
Field Experiments ◽  
Wide Area ◽  
Area Data

scholarly journals Multi-Level Elasticity for Wide-Area Data Streaming Systems: A Reinforcement Learning Approach

Algorithms ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 134 ◽  
Author(s):  
Gabriele Russo Russo ◽  
Matteo Nardelli ◽  
Valeria Cardellini ◽  
Francesco Lo Presti
Keyword(s):  
Reinforcement Learning ◽  
High Volume ◽  
Wide Area ◽  
Data Streaming ◽  
Application Performance ◽  
Ubiquitous Sensing ◽  
Self Adaptation ◽  
Adaptation Policies ◽  
Multi Level ◽  
Dsp Applications

The capability of efficiently processing the data streams emitted by nowadays ubiquitous sensing devices enables the development of new intelligent services. Data Stream Processing (DSP) applications allow for processing huge volumes of data in near real-time. To keep up with the high volume and velocity of data, these applications can elastically scale their execution on multiple computing resources to process the incoming data flow in parallel. Being that data sources and consumers are usually located at the network edges, nowadays the presence of geo-distributed computing resources represents an attractive environment for DSP. However, controlling the applications and the processing infrastructure in such wide-area environments represents a significant challenge. In this paper, we present a hierarchical solution for the autonomous control of elastic DSP applications and infrastructures. It consists of a two-layered hierarchical solution, where centralized components coordinate subordinated distributed managers, which, in turn, locally control the elastic adaptation of the application components and deployment regions. Exploiting this framework, we design several self-adaptation policies, including reinforcement learning based solutions. We show the benefits of the presented self-adaptation policies with respect to static provisioning solutions, and discuss the strengths of reinforcement learning based approaches, which learn from experience how to optimize the application performance and resource allocation.

How It Started

2009 ◽  
Vol 1 (4) ◽  
pp. 1-3 ◽  
Author(s):  
Evan Koblentz
Keyword(s):  
New Technology ◽  
Economic Recession ◽  
Internet Access ◽  
Wide Area ◽  
Handheld Devices ◽  
Personal Digital Assistants ◽  
Cellular Phones ◽  
Area Data

Internet access on cellular phones, after emerging as a new technology in the mid-1990s, is now a thriving activity despite the global economic recession. IDC reported smartphone sales of 1.18 billion units in 2008 (IDC, 2009), compared to the unconnected personal digital assistants approaching merely 1 million units per quarter in the second half of 2003.However, the concept of using handheld devices for wide area data applications began 25 years prior to the beginning of the end of PDAs

Wide area data replication for scientific collaborations

2008 ◽  
Vol 5 (3) ◽  
pp. 124 ◽  
Author(s):  
Ann Chervenak ◽  
Robert Schuler ◽  
Carl Kesselman ◽  
Scott Koranda ◽  
Brian Moe
Keyword(s):  
Data Replication ◽  
Wide Area ◽  
Area Data ◽  
Scientific Collaborations

Wide area data replication in an ITER-relevant data environment

2005 ◽  
Vol 74 (1-4) ◽  
pp. 809-813 ◽  
Author(s):  
C. Centioli ◽  
F. Iannone ◽  
M. Panella ◽  
V. Vitale ◽  
G. Bracco ◽  
...  
Keyword(s):  
Data Replication ◽  
Wide Area ◽  
Data Environment ◽  
Area Data

A Relationship Between Rainfall and Burned Area for Portugal

1994 ◽  
Vol 4 (1) ◽  
pp. 11 ◽  
Author(s):  
DX Viegas ◽  
MT Viegas
Keyword(s):  
Early Spring ◽  
Wide Area ◽  
Fire Season ◽  
Burned Area ◽  
Weather Station ◽  
Inverse Relation ◽  
Area Burned ◽  
Water Reserve ◽  
Area Data

Total area burned yearly in Portugal in the period of 1975 to 1992 is related to rainfall during particular periods of the year. Precipitation in the period of January to April, corresponding to Winter and early Spring, related to fine fuel growth and to the water reserve in the soil, shows a non monotonic relationship with burned area each year, due to the conflicting mechanisms of the these two processes. Rainfall between June and September, corresponding to the main fire season in Portugal, exhibits an inverse relation with burned area. Data of a single weather station were used in the analysis and it was demonstrated that they are representative of a wide area in the country.

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