Analyzing Market-Based Resource Allocation Strategies for the Computational Grid
By R. Wolski, James S. Plank, J. Brevik, Todd Bryan. The international journal of high performance computing applications, 2001
429 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/011b8286105007ff08adbf38faf758de9b9b9696
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In Computer Networks and Communications
- Rajkumar Buyya
- Srikumar Venugopal
- David Abramson
- Marcos Dias de Assunção
- Sharrukh Zaman
- Nicholas R. Jennings
- Alex Rogers
- Daniel Grosu
In Economics and Econometrics
In Finance
Citations in the corpus
- The Grid Economy (2005, background): “... (see Table 1) have explored the use of different economic models for trading resources to manage resources in different application domains: CPU cycles, storage space, database query processing, and distributed computing, They include Spawn [10], Popcorn [48], Java Market [72], Enhanced MOSIX [7”
- Evaluating the cost-benefit of using cloud computing to extend the capacity of clusters (2009, background): “Market-based resource allocation mechanisms for largescale distributed systems have been investigated [38].”
- Learning the IPA market with individual and social rewards (2007, neutral): “Commonly called Market-based, those mechanisms offer a promising approach [2,4,6,18,24,32,36,38].”
- Self-organized routing for wireless microsensor networks (2005, background): “…serve as a model for future large-scale open computer systems in which resources, such as data storage and computational power, will be physically distributed, continually subject to changes in availability and capability, and will likely be owned by stakeholders with differing objectives [18].”
- Economic-based Distributed Resource Management and Scheduling for Grid Computing (2002, methodology): “rces, users, applications, and brokers. The economic Grid resource broker supports deadline and budget based time, cost, costtime, and conservative time optimisation scheduling algorithms. G-Commerce [120] (U. of California Santa Barbara) Commodity and auctions Simulates hypothetical consumers and p”
- Combinatorial Auction-Based Allocation of Virtual Machine Instances in Clouds (2010, background): “Wolski et al. [7] compared commodities markets and auctions in grids in terms of price stability and market equilibrium.”