1,516 research outputs found
Computing an Optimal Control Policy for an Energy Storage
We introduce StoDynProg, a small library created to solve Optimal Control
problems arising in the management of Renewable Power Sources, in particular
when coupled with an Energy Storage System. The library implements generic
Stochastic Dynamic Programming (SDP) numerical methods which can solve a large
class of Dynamic Optimization problems. We demonstrate the library capabilities
with a prototype problem: smoothing the power of an Ocean Wave Energy
Converter. First we use time series analysis to derive a stochastic Markovian
model of this system since it is required by Dynamic Programming. Then, we
briefly describe the "policy iteration" algorithm we have implemented and the
numerical tools being used. We show how the API design of the library is
generic enough to address Dynamic Optimization problems outside the field of
Energy Management. Finally, we solve the power smoothing problem and compare
the optimal control with a simpler heuristic control.Comment: Part of the Proceedings of the 6th European Conference on Python in
Science (EuroSciPy 2013), Pierre de Buyl and Nelle Varoquaux editors, (2014
Modeling cloud resources using machine learning
Cloud computing is a new Internet infrastructure paradigm where management optimization has become a challenge to be solved, as all current management systems are human-driven or ad-hoc automatic systems that must be tuned manually by experts. Management of cloud resources require accurate information about all the elements involved (host machines, resources, offered services, and clients), and some of this information can only be obtained a posteriori. Here we present the cloud and part of its architecture as a new scenario where data mining and machine learning can be applied to discover information and improve its management thanks to modeling and prediction. As a novel case of study we show in this work the modeling of basic cloud resources using machine learning, predicting resource requirements from context information like amount of load and clients, and also predicting the quality of service from resource planning, in order to feed cloud schedulers. Further, this work is an important part of our ongoing research program, where accurate models and predictors are essential to optimize cloud management autonomic systems.Postprint (published version
A survey on fault-models for QoS studies of service-oriented systems
This survey paper presents an overview of the fault-models available to the
researcher who wants to parameterise system-models in order to study Quality-
of-Service (QoS) properties of systems with service-oriented architecture. The
concept of a system-model subsumes the whole spectrum between abstract
mathematical models and testbeds based on actual implementations. Fault-
models, on the other hand, are parameters to system-models. They introduce
faults and disturbances into the system-model, thereby allowing the study of
QoS under realistic conditions. In addition to a survey of existing fault-
models, the paper also provides a discussion of available fault-classification
schemes
FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting
Forecasting of multivariate time-series is an important problem that has
applications in traffic management, cellular network configuration, and
quantitative finance. A special case of the problem arises when there is a
graph available that captures the relationships between the time-series. In
this paper we propose a novel learning architecture that achieves performance
competitive with or better than the best existing algorithms, without requiring
knowledge of the graph. The key element of our proposed architecture is the
learnable fully connected hard graph gating mechanism that enables the use of
the state-of-the-art and highly computationally efficient fully connected
time-series forecasting architecture in traffic forecasting applications.
Experimental results for two public traffic network datasets illustrate the
value of our approach, and ablation studies confirm the importance of each
element of the architecture. The code is available here:
https://github.com/boreshkinai/fc-gaga
Towards Autonomic Service Provisioning Systems
This paper discusses our experience in building SPIRE, an autonomic system
for service provision. The architecture consists of a set of hosted Web
Services subject to QoS constraints, and a certain number of servers used to
run session-based traffic. Customers pay for having their jobs run, but require
in turn certain quality guarantees: there are different SLAs specifying charges
for running jobs and penalties for failing to meet promised performance
metrics. The system is driven by an utility function, aiming at optimizing the
average earned revenue per unit time. Demand and performance statistics are
collected, while traffic parameters are estimated in order to make dynamic
decisions concerning server allocation and admission control. Different utility
functions are introduced and a number of experiments aiming at testing their
performance are discussed. Results show that revenues can be dramatically
improved by imposing suitable conditions for accepting incoming traffic; the
proposed system performs well under different traffic settings, and it
successfully adapts to changes in the operating environment.Comment: 11 pages, 9 Figures,
http://www.wipo.int/pctdb/en/wo.jsp?WO=201002636
Selected topics in robotics for space exploration
Papers and abstracts included represent both formal presentations and experimental demonstrations at the Workshop on Selected Topics in Robotics for Space Exploration which took place at NASA Langley Research Center, 17-18 March 1993. The workshop was cosponsored by the Guidance, Navigation, and Control Technical Committee of the NASA Langley Research Center and the Center for Intelligent Robotic Systems for Space Exploration (CIRSSE) at RPI, Troy, NY. Participation was from industry, government, and other universities with close ties to either Langley Research Center or to CIRSSE. The presentations were very broad in scope with attention given to space assembly, space exploration, flexible structure control, and telerobotics
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