Compute Power Market: towards a market-oriented grid

Buyya, Rajkumar; Vazhkudai, S.

doi:10.1109/ccgrid.2001.923245

Cited by 72 publications

(47 citation statements)

References 10 publications

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“…This marketplace is composed of three entities; 1) Consumer (buyer), 2) Provider (seller) and 3) Marketplace system [7,12,15]. The consumer can be a) end-consumer who will consume the resource(s) individually and b) business consumer (e.g.…”

Section: Cn% Rd= W J ×mentioning

confidence: 99%

“…This is supported by the need for, specifying architecture of and defining notation for combinatorial marketplace of Cloud resources. Although there are proposed market architectures and algorithms [6,7,8,12,16,23,27,31,32,35,37], this architecture addresses and offsets the limitations exhibited by the existing offerings and some proposed solutions.…”

Section: Introductionmentioning

confidence: 99%

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Multi-attribute Combinatorial Marketplaces for Cloud Resource Trading

Alrawahi

Lee

2012

2012 Second International Conference on Cloud and Green Computing

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Abstract-Cloud Computing represents a new era where computing is offered as a service rather than as a physical product. The next level of flexibility will be achieved when Cloud Computing services can be automatically traded. This paper focuses on providing the foundation for simple and flexible Cloud resource trading. This is achieved by proposing vocabularies for the trading of Cloud resources and algorithms for a Cloud marketplace. A multi-attribute combinatorial marketplace is proposed as a solution for situations where Cloud resources need to be traded in combination (bundles). Vocabularies are introduced to serve as a foundation to build standards for Cloud resources trading.

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Section: Cn% Rd= W J ×mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-attribute Combinatorial Marketplaces for Cloud Resource Trading

Alrawahi

Lee

2012

2012 Second International Conference on Cloud and Green Computing

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“…Furthermore, these entities need to coordinate their activities in a scalable manner to achieve the desired systemwide objective functions. One such mechanism is the Compute Power Market [14], built using the JXTA infrastructure from Sun Microsystems, which allows the trading of computational power over peer-to-peer networks. Another more recent advancement with respect to coordinated Grid resource management has been the GridFederation [18] model, which encapsulates decentralized protocols and algorithms for efficient discovery and coordinated provisioning of resources in federated Grid and peer-to-peer systems.…”

Section: Architecturementioning

confidence: 99%

“…It has been envisioned that Grids enable the creation of virtual organizations (VOs) [11] and virtual enterprises (VEs) [13] or computing marketplaces [14]. In a typical marketbased model VO/VE, Grid service providers (GSPs) publish their offerings in a market directory (or a catalog), and Grid service consumers (GSCs) employ a Grid resource broker (GRB) that identifies GSPs through the market directory and utilize the services of suitable resources that meet their QoS requirements (see Fig.…”

Section: Grid Market Directory (Gmd)mentioning

confidence: 99%

The Gridbus Middleware for Market‐Oriented Computing

Buyya

Venugopal

Ranjan

et al. 2009

Market‐Oriented Grid and Utility Computing

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“…P2P networks have been designed and implemented for many target areas such as compute resource sharing (e.g. SETI@Home [25], Compute Power Market [26]), content and file sharing (Napster [27], Gnutella [28], Kazaa [29]) and collaborative applications such as instant messengers (Jabber [30]). A detailed taxonomy and survey of peer-to-peer systems can be found in [31].…”

Section: Peer-to-peer Networkmentioning

confidence: 99%

A taxonomy of Data Grids for distributed data sharing, management, and processing

2006

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Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration.Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.

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Compute Power Market: towards a market-oriented grid

Abstract: Abstract

Cited by 72 publications

References 10 publications

Multi-attribute Combinatorial Marketplaces for Cloud Resource Trading

Multi-attribute Combinatorial Marketplaces for Cloud Resource Trading

The Gridbus Middleware for Market‐Oriented Computing

A taxonomy of Data Grids for distributed data sharing, management, and processing

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