98,490 research outputs found
Next-Generation EU DataGrid Data Management Services
We describe the architecture and initial implementation of the
next-generation of Grid Data Management Middleware in the EU DataGrid (EDG)
project.
The new architecture stems out of our experience and the users requirements
gathered during the two years of running our initial set of Grid Data
Management Services. All of our new services are based on the Web Service
technology paradigm, very much in line with the emerging Open Grid Services
Architecture (OGSA). We have modularized our components and invested a great
amount of effort towards a secure, extensible and robust service, starting from
the design but also using a streamlined build and testing framework.
Our service components are: Replica Location Service, Replica Metadata
Service, Replica Optimization Service, Replica Subscription and high-level
replica management. The service security infrastructure is fully GSI-enabled,
hence compatible with the existing Globus Toolkit 2-based services; moreover,
it allows for fine-grained authorization mechanisms that can be adjusted
depending on the service semantics.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics
(CHEP03), La Jolla,Ca, USA, March 2003 8 pages, LaTeX, the file contains all
LaTeX sources - figures are in the directory "figures
Implementation of Distributed Time Exchange Based Cooperative Forwarding
In this paper, we design and implement time exchange (TE) based cooperative
forwarding where nodes use transmission time slots as incentives for relaying.
We focus on distributed joint time slot exchange and relay selection in the sum
goodput maximization of the overall network. We formulate the design objective
as a mixed integer nonlinear programming (MINLP) problem and provide a
polynomial time distributed solution of the MINLP. We implement the designed
algorithm in the software defined radio enabled USRP nodes of the ORBIT indoor
wireless testbed. The ORBIT grid is used as a global control plane for exchange
of control information between the USRP nodes. Experimental results suggest
that TE can significantly increase the sum goodput of the network. We also
demonstrate the performance of a goodput optimization algorithm that is
proportionally fair.Comment: Accepted in 2012 Military Communications Conferenc
Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems
Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data. In particular, big data analytics alludes to applications of artificial intelligence, machine learning techniques, data mining techniques, time-series forecasting methods. Decision-makers in power systems have been long plagued by incapability and weakness of classical methods in dealing with large-scale real practical cases due to the existence of thousands or millions of variables, being time-consuming, the requirement of a high computation burden, divergence of results, unjustifiable errors, and poor accuracy of the model. Big data analytics is an ongoing topic, which pinpoints how to extract insights from these large data sets. The extant article has enumerated the applications of big data analytics in future power systems through several layers from grid-scale to local-scale. Big data analytics has many applications in the areas of smart grid implementation, electricity markets, execution of collaborative operation schemes, enhancement of microgrid operation autonomy, management of electric vehicle operations in smart grids, active distribution network control, district hub system management, multi-agent energy systems, electricity theft detection, stability and security assessment by PMUs, and better exploitation of renewable energy sources. The employment of big data analytics entails some prerequisites, such as the proliferation of IoT-enabled devices, easily-accessible cloud space, blockchain, etc. This paper has comprehensively conducted an extensive review of the applications of big data analytics along with the prevailing challenges and solutions
Job Interactivity Using a Steering Service in an Interactive Grid Analysis Environment
Grid computing has been dominated by the execution of batch jobs. Interactive data analysis is a new domain in the area of grid job execution. The Grid-Enabled Analysis Environment (GAE) attempts to address this in HEP grids by the use of a Steering Service. This service will provide physicists with the continuous feedback of their jobs and will provide them with the ability to control and steer the execution of their submitted jobs. It will enable them to move their jobs to different grid nodes when desired. The Steering Service will also act autonomously to make steering decisions on behalf of the user, attempting to optimize the execution of the job. This service will also ensure the optimal consumption of the Grid user's resource quota. The Steering Service will provide a web service interface defined by standard WSDL. In this paper we have discussed how the Steering Service will facilitate interactive remote analysis of data generated in Interactive Grid Analysis Environment
RF Energy Harvesting Enabled Power Sharing in Relay Networks
Through simultaneous energy and information transfer, radio frequency (RF)
energy harvesting (EH) reduces the energy consumption of the wireless networks.
It also provides a new approach for the wireless devices to share each other's
energy storage, without relying on the power grid or traffic offloading. In
this paper, we study RF energy harvesting enabled power balancing within the
decode-and-forward (DF) relaying-enhanced cooperative wireless system. An
optimal power allocation policy is proposed for the scenario where both source
and relay nodes can draw power from the radio frequency signals transmitted by
each other. To maximize the overall throughput while meeting the energy
constraints imposed by the RF sources, an optimization problem is formulated
and solved. Based on different harvesting efficiency and channel condition,
closed form solutions for optimal joint source and relay power allocation are
derived.Comment: An abbreviated version will be presented at IEEE online GreenComm,
Nov., 201
Lightweight Blockchain Framework for Location-aware Peer-to-Peer Energy Trading
Peer-to-Peer (P2P) energy trading can facilitate integration of a large
number of small-scale producers and consumers into energy markets.
Decentralized management of these new market participants is challenging in
terms of market settlement, participant reputation and consideration of grid
constraints. This paper proposes a blockchain-enabled framework for P2P energy
trading among producer and consumer agents in a smart grid. A fully
decentralized market settlement mechanism is designed, which does not rely on a
centralized entity to settle the market and encourages producers and consumers
to negotiate on energy trading with their nearby agents truthfully. To this
end, the electrical distance of agents is considered in the pricing mechanism
to encourage agents to trade with their neighboring agents. In addition, a
reputation factor is considered for each agent, reflecting its past performance
in delivering the committed energy. Before starting the negotiation, agents
select their trading partners based on their preferences over the reputation
and proximity of the trading partners. An Anonymous Proof of Location (A-PoL)
algorithm is proposed that allows agents to prove their location without
revealing their real identity. The practicality of the proposed framework is
illustrated through several case studies, and its security and privacy are
analyzed in detail
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