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Jorge Andrale Ortiz

dblp:55/4797 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 44% Cloud and datacenter computing · 44% High-performance computing · 13%
Computer networks
1 paper
Network optimization and economics · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network optimization and economics › resource allocation
market-based resource allocation
0.112006
Market-Based Resource Allocation using Price Prediction in a High Performance Computing Grid for Scientific Applications · HPDC 2006
Distributed systems
grid computing
0.112006
Market-Based Resource Allocation using Price Prediction in a High Performance Computing Grid for Scientific Applications · HPDC 2006
Cloud and datacenter computing
resource allocation
0.112006
Market-Based Resource Allocation using Price Prediction in a High Performance Computing Grid for Scientific Applications · HPDC 2006
High-performance computing
scientific computing systems
0.012006
Market-Based Resource Allocation using Price Prediction in a High Performance Computing Grid for Scientific Applications · HPDC 2006

Methods — techniques the papers use, named apart from their topics

signed money-transfer tokens · 0.1market-based allocation · 0.1
YearPublicationVenuePosition
2006 Market-Based Resource Allocation using Price Prediction in a High Performance Computing Grid for Scientific Applications
abstract
We present the implementation and analysis of a market-based resource allocation system for computational grids. Although grids provide a way to share resources and take advantage of statistical multiplexing, a variety of challenges remain. One is the economically efficient allocation of resources to users from disparate organizations who have their own and sometimes conflicting requirements for both the quantity and quality of services. Another is secure and scalable authorization despite rapidly changing allocations. Our solution to both of these challenges is to use a market-based resource allocation system. This system allows users to express diverse quantity- and quality-of-service requirements, yet prevents them from denying service to other users. It does this by providing tools to the user to predict and tradeoff risk and expected return in the computational market. In addition, the system enables secure and scalable authorization by using signed money-transfer tokens instead of identity-based authorization. This removes the overhead of maintaining and updating access control lists, while restricting usage based on the amount of money transferred. We examine the performance of the system by running a bioinformatics application on a fully operational implementation of an integrated grid market
Thomas Sandholm, Jorge Andrale Ortiz, Jacob Odeberg
HPDC3