156,579 research outputs found
SensorCloud: Towards the Interdisciplinary Development of a Trustworthy Platform for Globally Interconnected Sensors and Actuators
Although Cloud Computing promises to lower IT costs and increase users'
productivity in everyday life, the unattractive aspect of this new technology
is that the user no longer owns all the devices which process personal data. To
lower scepticism, the project SensorCloud investigates techniques to understand
and compensate these adoption barriers in a scenario consisting of cloud
applications that utilize sensors and actuators placed in private places. This
work provides an interdisciplinary overview of the social and technical core
research challenges for the trustworthy integration of sensor and actuator
devices with the Cloud Computing paradigm. Most importantly, these challenges
include i) ease of development, ii) security and privacy, and iii) social
dimensions of a cloud-based system which integrates into private life. When
these challenges are tackled in the development of future cloud systems, the
attractiveness of new use cases in a sensor-enabled world will considerably be
increased for users who currently do not trust the Cloud.Comment: 14 pages, 3 figures, published as technical report of the Department
of Computer Science of RWTH Aachen Universit
European White Book on Real-Time Power Hardware in the Loop Testing : DERlab Report No. R- 005.0
The European White Book on Real-Time-Powerhardware-in-the-Loop testing is intended to serve as a reference document on the future of testing of electrical power equipment, with speciïŹ c focus on the emerging hardware-in-the-loop activities and application thereof within testing facilities and procedures. It will provide an outlook of how this powerful tool can be utilised to support the development, testing and validation of speciïŹ cally DER equipment. It aims to report on international experience gained thus far and provides case studies on developments and speciïŹ c technical issues, such as the hardware/software interface. This white book compliments the already existing series of DERlab European white books, covering topics such as grid-inverters and grid-connected storag
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
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A review of microgrid development in the United States â A decade of progress on policies, demonstrations, controls, and software tools
Microgrids have become increasingly popular in the United States. Supported by favorable federal and local policies, microgrid projects can provide greater energy stability and resilience within a project site or community. This paper reviews major federal, state, and utility-level policies driving microgrid development in the United States. Representative U.S. demonstration projects are selected and their technical characteristics and non-technical features are introduced. The paper discusses trends in the technology development of microgrid systems as well as microgrid control methods and interactions within the electricity market. Software tools for microgrid design, planning, and performance analysis are illustrated with each tool's core capability. Finally, the paper summarizes the successes and lessons learned during the recent expansion of the U.S. microgrid industry that may serve as a reference for other countries developing their own microgrid industries
Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches
Peer-to-peer (P2P) energy trading has emerged as a next-generation energy
management mechanism for the smart grid that enables each prosumer of the
network to participate in energy trading with one another and the grid. This
poses a significant challenge in terms of modeling the decision-making process
of each participant with conflicting interest and motivating prosumers to
participate in energy trading and to cooperate, if necessary, for achieving
different energy management goals. Therefore, such decision-making process
needs to be built on solid mathematical and signal processing tools that can
ensure an efficient operation of the smart grid. This paper provides an
overview of the use of game theoretic approaches for P2P energy trading as a
feasible and effective means of energy management. As such, we discuss various
games and auction theoretic approaches by following a systematic classification
to provide information on the importance of game theory for smart energy
research. Then, the paper focuses on the P2P energy trading describing its key
features and giving an introduction to an existing P2P testbed. Further, the
paper zooms into the detail of some specific game and auction theoretic models
that have recently been used in P2P energy trading and discusses some important
finding of these schemes.Comment: 38 pages, single column, double spac
Requirements to Testing of Power System Services Provided by DER Units
The present report forms the Project Deliverable âD 2.2â of the DERlab NoE project, supported by the EC under Contract No. SES6-CT-518299 NoE DERlab. The present document discuss the power system services that may be provided from DER units and the related methods to test the services actually provided, both at component level and at system level
Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks
Deep neural networks (DNNs) are known vulnerable to adversarial attacks. That
is, adversarial examples, obtained by adding delicately crafted distortions
onto original legal inputs, can mislead a DNN to classify them as any target
labels. This work provides a solution to hardening DNNs under adversarial
attacks through defensive dropout. Besides using dropout during training for
the best test accuracy, we propose to use dropout also at test time to achieve
strong defense effects. We consider the problem of building robust DNNs as an
attacker-defender two-player game, where the attacker and the defender know
each others' strategies and try to optimize their own strategies towards an
equilibrium. Based on the observations of the effect of test dropout rate on
test accuracy and attack success rate, we propose a defensive dropout algorithm
to determine an optimal test dropout rate given the neural network model and
the attacker's strategy for generating adversarial examples.We also investigate
the mechanism behind the outstanding defense effects achieved by the proposed
defensive dropout. Comparing with stochastic activation pruning (SAP), another
defense method through introducing randomness into the DNN model, we find that
our defensive dropout achieves much larger variances of the gradients, which is
the key for the improved defense effects (much lower attack success rate). For
example, our defensive dropout can reduce the attack success rate from 100% to
13.89% under the currently strongest attack i.e., C&W attack on MNIST dataset.Comment: Accepted as conference paper on ICCAD 201
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