-
Matthew Newby,
Nathan Cole,
Heidi Jo Newberg,
Travis Desell,
Malik Magdon-Ismail,
Boleslaw Szymanski,
Carlos Varela,
Benjamin Willett,
and Brian Yanny.
A Spatial Characterization of the Sagittarius Dwarf Galaxy Tidal Tails.
The Astronomical Journal,
145(163),
May 2013.
Keyword(s): scientific computing,
distributed computing.
Abstract: |
We measure the spatial density of F turnoff stars in the Sagittarius dwarf tidal stream, from Sloan Digital Sky Survey data, using statistical photometric parallax. We find a set of continuous, consistent parameters that describe the leading Sgr stream's position, direction, and width for 15 stripes in the north Galactic cap, and three stripes in the south Galactic cap. We produce a catalog of stars that has the density characteristics of the dominant leading Sgr tidal stream that can be compared with simulations. We find that the width of the leading (north) tidal tail is consistent with recent triaxial and axisymmetric halo model simulations. The density along the stream is roughly consistent with common disruption models in the north, but possibly not in the south. We explore the possibility that one or more of the dominant Sgr streams has been misidentified, and that one or more of the "bifurcated" pieces is the real Sgr tidal tail, but we do not reach definite conclusions. If two dwarf progenitors are assumed, fits to the planes of the dominant and "bifurcated" tidal tails favor an association of the Sgr dwarf spheroidal galaxy with the dominant southern stream and the "bifurcated" stream in the north. In the north Galactic cap, the best fit Hernquist density profile for the smooth component of the stellar halo is oblate, with a flattening parameter q = 0.53, and a scale length of r 0 = 6.73. The southern data for both the tidal debris and the smooth component of the stellar halo do not match the model fits to the north, although the stellar halo is still overwhelmingly oblate. Finally, we verify that we can reproduce the parameter fits on the asynchronous MilkyWay@home volunteer computing platform. |
@article{newby-sagittarius-aj-2013,
author = "Matthew Newby and Nathan Cole and Heidi Jo Newberg and Travis Desell and Malik Magdon-Ismail and Boleslaw Szymanski and Carlos Varela and Benjamin Willett and Brian Yanny",
title = "A Spatial Characterization of the Sagittarius Dwarf Galaxy Tidal Tails",
journal = {The Astronomical Journal},
year = 2013,
month = "May",
volume = 145,
number = 163,
keywords = "scientific computing, distributed computing",
abstract = {We measure the spatial density of F turnoff stars in the Sagittarius dwarf tidal stream, from Sloan Digital Sky Survey data, using statistical photometric parallax. We find a set of continuous, consistent parameters that describe the leading Sgr stream's position, direction, and width for 15 stripes in the north Galactic cap, and three stripes in the south Galactic cap. We produce a catalog of stars that has the density characteristics of the dominant leading Sgr tidal stream that can be compared with simulations. We find that the width of the leading (north) tidal tail is consistent with recent triaxial and axisymmetric halo model simulations. The density along the stream is roughly consistent with common disruption models in the north, but possibly not in the south. We explore the possibility that one or more of the dominant Sgr streams has been misidentified, and that one or more of the "bifurcated" pieces is the real Sgr tidal tail, but we do not reach definite conclusions. If two dwarf progenitors are assumed, fits to the planes of the dominant and "bifurcated" tidal tails favor an association of the Sgr dwarf spheroidal galaxy with the dominant southern stream and the "bifurcated" stream in the north. In the north Galactic cap, the best fit Hernquist density profile for the smooth component of the stellar halo is oblate, with a flattening parameter q = 0.53, and a scale length of r 0 = 6.73. The southern data for both the tidal debris and the smooth component of the stellar halo do not match the model fits to the north, although the stellar halo is still overwhelmingly oblate. Finally, we verify that we can reproduce the parameter fits on the asynchronous MilkyWay@home volunteer computing platform.}
}
-
Shigeru Imai,
Thomas Chestna,
and Carlos A. Varela.
Accurate Resource Prediction for Hybrid IaaS Clouds Using Workload-Tailored Elastic Compute Units.
In 6th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2013),
Dresden, Germany,
December 2013.
Keyword(s): distributed computing,
distributed systems,
cloud computing.
Abstract: |
Cloud computing's pay-per-use model greatly reduces upfront cost and also enables on-demand scalability as service demand grows or shrinks. Hybrid clouds are an attractive option in terms of cost benefit, however, without proper elastic resource management, computational resources could be over-provisioned or under-provisioned, resulting in wasting money or failing to satisfy service demand. In this paper, to accomplish accurate performance prediction and cost-optimal resource management for hybrid clouds, we introduce Workload-tailored Elastic Compute Units (WECU) as a measure of computing resources analogous to Amazon EC2's ECUs, but customized for a specific workload. We present a dynamic programming-based scheduling algorithm to select a combination of private and public resources which satisfy a desired throughput. Using a loosely-coupled benchmark, we confirmed WECUs have 24 (J\% better runtime prediction ability than ECUs on average. Moreover, simulation results with a real workload distribution of web service requests show that our WECU-based algorithm reduces costs by 8-31\% compared to a fixed provisioning approach.) |
@InProceedings{imai-chestna-varela-ucc-2013,
author = {Shigeru Imai and Thomas Chestna and Carlos A. Varela},
title = {Accurate Resource Prediction for Hybrid IaaS Clouds Using Workload-Tailored Elastic Compute Units},
booktitle = {6th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2013)},
year = 2013,
address = {Dresden, Germany},
month = {December},
pdf = {http://wcl.cs.rpi.edu/papers/ucc2013.pdf},
keywords = {distributed computing, distributed systems, cloud computing},
abstract = {Cloud computing's pay-per-use model greatly reduces upfront cost and also enables on-demand scalability as service demand grows or shrinks. Hybrid clouds are an attractive option in terms of cost benefit, however, without proper elastic resource management, computational resources could be over-provisioned or under-provisioned, resulting in wasting money or failing to satisfy service demand. In this paper, to accomplish accurate performance prediction and cost-optimal resource management for hybrid clouds, we introduce Workload-tailored Elastic Compute Units (WECU) as a measure of computing resources analogous to Amazon EC2's ECUs, but customized for a specific workload. We present a dynamic programming-based scheduling algorithm to select a combination of private and public resources which satisfy a desired throughput. Using a loosely-coupled benchmark, we confirmed WECUs have 24 (J\% better runtime prediction ability than ECUs on average. Moreover, simulation results with a real workload distribution of web service requests show that our WECU-based algorithm reduces costs by 8-31\% compared to a fixed provisioning approach.)}
}
-
Shigeru Imai,
Richard Klockowski,
and Carlos A. Varela.
Self-Healing Spatio-Temporal Data Streams Using Error Signatures.
In 2nd International Conference on Big Data Science and Engineering (BDSE 2013),
Sydney, Australia,
December 2013.
Keyword(s): programming languages,
data streaming,
cyber physical systems.
Abstract: |
Self-healing spatio-temporal data streaming systems enable error detection and data correction based on error signatures. Error signatures are mathematical function patterns with constraints and are used to identify and categorize errors in redundant spatio-temporal data streams. In this paper, we apply these methods to real data from a private Cessna flight and from the Air France AF447 accident in June 2009. For the private Cessna flight, three error scenarios are simulated: pitot tube failure, GPS failure, and simultaneous pitot tube and GPS failures. The error detection accuracy is approximately 93% and the response time to correct data is at most 5 seconds. For the AF447 flight, 162 seconds of available flight data including the pitot tubes failure is collected from the accident report. The pitot tube failure of the AF447 flight is successfully detected and corrected after 5 seconds from the beginning of the failure. Overall error mode detection accuracy reaches 96.31%.Furthermore, our simulations show that the system never corrects data incorrectly, i.e., all inaccurate mode detections produce either unknown or unrecoverable errors. |
@InProceedings{imai-klockr-varela-bdse-2013,
author = {Shigeru Imai and Richard Klockowski and Carlos A. Varela},
title = {Self-Healing Spatio-Temporal Data Streams Using Error Signatures},
booktitle = {2nd International Conference on Big Data Science and Engineering (BDSE 2013)},
year = 2013,
address = {Sydney, Australia},
month = {December},
pdf = {http://wcl.cs.rpi.edu/papers/bdse2013.pdf},
keywords = {programming languages, data streaming, cyber physical systems},
abstract = {Self-healing spatio-temporal data streaming systems enable error detection and data correction based on error signatures. Error signatures are mathematical function patterns with constraints and are used to identify and categorize errors in redundant spatio-temporal data streams. In this paper, we apply these methods to real data from a private Cessna flight and from the Air France AF447 accident in June 2009. For the private Cessna flight, three error scenarios are simulated: pitot tube failure, GPS failure, and simultaneous pitot tube and GPS failures. The error detection accuracy is approximately 93% and the response time to correct data is at most 5 seconds. For the AF447 flight, 162 seconds of available flight data including the pitot tubes failure is collected from the accident report. The pitot tube failure of the AF447 flight is successfully detected and corrected after 5 seconds from the beginning of the failure. Overall error mode detection accuracy reaches 96.31%.Furthermore, our simulations show that the system never corrects data incorrectly, i.e., all inaccurate mode detections produce either unknown or unrecoverable errors.}
}
-
Richard S. Klockowski,
Shigeru Imai,
Colin Rice,
and Carlos A. Varela.
Autonomous Data Error Detection and Recovery in Streaming Applications.
In Proceedings of the International Conference on Computational Science (ICCS 2013). Dynamic Data-Driven Application Systems (DDDAS 2013) Workshop,
pages 2036-2045,
May 2013.
Keyword(s): programming languages,
data streaming,
cyber physical systems.
Abstract: |
Detecting and recovering from errors in data streams is paramount to developing successful autonomous real-time streaming applications. In this paper, we devise a multi-modal data error detection and recovery architecture to enable automated recovery from data errors in streaming applications based on available redundancy. We formally define error signatures as a way to identify classes of abnormal conditions and mode likelihood vectors as a quantitative discriminator of data stream condition modes. Finally, we design an extension to our own declarative programming language, PILOTS, to include error correction code. We define performance metrics for our approach, and evaluate the impact of monitored data window size and mode likelihood change threshold on the accuracy and responsiveness of our data-driven multi-modal error detection and correction software. Tragic accidents—such as Air France's flight from Rio de Janeiro to Paris in June 2009 killing all people on board— can be prevented by implementing auto-pilot systems with an airspeed data stream error detection and correction algorithm following the fundamental principles illustrated in this work. |
@InProceedings{klockr-errorsignatures-dddas-2013,
author = {Richard S. Klockowski and Shigeru Imai and Colin Rice and Carlos A. Varela},
title = {Autonomous Data Error Detection and Recovery in Streaming Applications},
booktitle = {Proceedings of the International Conference on Computational Science (ICCS 2013). Dynamic Data-Driven Application Systems (DDDAS 2013) Workshop},
institution = {Rensselaer Polytechnic Institute Worldwide Computing Laboratory},
year = 2013,
month = {May},
pages = {2036-2045},
pdf = {http://wcl.cs.rpi.edu/papers/dddas2013.pdf},
keywords = {programming languages, data streaming, cyber physical systems},
abstract = {Detecting and recovering from errors in data streams is paramount to developing successful autonomous real-time streaming applications. In this paper, we devise a multi-modal data error detection and recovery architecture to enable automated recovery from data errors in streaming applications based on available redundancy. We formally define error signatures as a way to identify classes of abnormal conditions and mode likelihood vectors as a quantitative discriminator of data stream condition modes. Finally, we design an extension to our own declarative programming language, PILOTS, to include error correction code. We define performance metrics for our approach, and evaluate the impact of monitored data window size and mode likelihood change threshold on the accuracy and responsiveness of our data-driven multi-modal error detection and correction software. Tragic accidents—such as Air France's flight from Rio de Janeiro to Paris in June 2009 killing all people on board— can be prevented by implementing auto-pilot systems with an airspeed data stream error detection and correction algorithm following the fundamental principles illustrated in this work.}
}
-
David R. Musser and Carlos A. Varela.
Structured Reasoning About Actor Systems.
In Proceedings of the 2013 Workshop on Programming Based on Actors, Agents, and Decentralized Control,
AGERE! 2013,
New York, NY, USA,
pages 37-48,
2013.
ACM.
ISBN: 978-1-4503-2602-5.
Keyword(s): programming languages,
actor model,
concurrent programming,
formal verification.
Abstract: |
The actor model of distributed computing imposes important restrictions on concurrent computations in order to be valid. In particular, an actor language implementation must provide fairness, the property that if a system transition is infinitely often enabled, the transition must eventually happen. Fairness is fundamental to proving progress properties. We show that many properties of actor computation can be expressed and proved at an abstract level, independently of the details of a particular system of actors. As in abstract algebra, we formulate and prove theorems at the most abstract level possible, so that they can be applied at all more refined levels of the theory hierarchy. Our most useful abstract-level theorems concern persistence of actors, conditional persistence of messages, preservation of unique actor identifiers, monotonicity properties of actor local states, guaranteed message delivery, and general consequences of fairness. We apply the general actor theory to a concrete ticker and clock actor system, proving several system-specific properties, including conditional invariants and a progress theorem. We develop our framework within the Athena proof system, in which proofs are both human-readable and machine-checkable, taking advantage of it library of algebraic and relational theories. |
@inproceedings{musser-varela-agere-2013,
author = {Musser, David R. and Varela, Carlos A.},
title = {Structured Reasoning About Actor Systems},
booktitle = {Proceedings of the 2013 Workshop on Programming Based on Actors, Agents, and Decentralized Control},
series = {AGERE! 2013},
year = {2013},
isbn = {978-1-4503-2602-5},
location = {Indianapolis, Indiana, USA},
pages = {37--48},
pdf = {http://wcl.cs.rpi.edu/papers/agere-paper.pdf},
url = {http://doi.acm.org/10.1145/2541329.2541334},
doi = {10.1145/2541329.2541334},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {programming languages, actor model, concurrent programming, formal verification},
abstract = {The actor model of distributed computing imposes important restrictions on concurrent computations in order to be valid. In particular, an actor language implementation must provide fairness, the property that if a system transition is infinitely often enabled, the transition must eventually happen. Fairness is fundamental to proving progress properties. We show that many properties of actor computation can be expressed and proved at an abstract level, independently of the details of a particular system of actors. As in abstract algebra, we formulate and prove theorems at the most abstract level possible, so that they can be applied at all more refined levels of the theory hierarchy. Our most useful abstract-level theorems concern persistence of actors, conditional persistence of messages, preservation of unique actor identifiers, monotonicity properties of actor local states, guaranteed message delivery, and general consequences of fairness. We apply the general actor theory to a concrete ticker and clock actor system, proving several system-specific properties, including conditional invariants and a progress theorem. We develop our framework within the Athena proof system, in which proofs are both human-readable and machine-checkable, taking advantage of it library of algebraic and relational theories.}
}