SORMA – Business Cases for an Open Grid Market: Concept and Implementation

Nimis, Jens; Anandasivam, Arun; Borissov, Nikolay; Smith, Garriet W.; Neumann, Dirk; Wirström, Niklas; Erel, Rosenberg; Matteo, Villa

doi:10.1007/978-3-540-85485-2_14

Cited by 18 publications

(10 citation statements)

References 18 publications

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“…In formula (6), it can be ensured that a random integer between 0 and 1 can appear in the crossover process, and there is at least one component coming from , …”

Section: Differential Genetic Algorithmmentioning

confidence: 99%

“…The simulation experiment has shown that resource utilization rate has been improved. In Literature [6][7], a random integer programming is proposed to optimize resources, and make dynamic allocation of resources by examining resource overhead of various stages. In Literature [8], genetic algorithm, basic ant colony algorithm and resource scheduling algorithm are proposed to allocate cloud computing resources for users reasonably with the target of the completion time of the best overall task.…”

Section: Introductionmentioning

confidence: 99%

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Research of Resource Allocation in Cloud Computing Based on Improved Dual Bee Colony Algorithm

Ju-Hua¹

2015

IJGDC

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“…In formula (6), it can be ensured that a random integer between 0 and 1 can appear in the crossover process, and there is at least one component coming from , …”

Section: Differential Genetic Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research of Resource Allocation in Cloud Computing Based on Improved Dual Bee Colony Algorithm

Ju-Hua¹

2015

IJGDC

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“…Several market-based allocation systems for grids, such as Sorma [22] and Nimrod/G [13], use bargaining or negotiation to determine the resource price. The advantage of this approach is that sellers and buyers communicate directly, without a third party mediating an allocation.…”

Section: Related Workmentioning

confidence: 99%

Strategy-Proof Dynamic Resource Pricing of Multiple Resource Types on Federated Clouds

Mihailescu

Teo

2010

Lecture Notes in Computer Science

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Abstract. There is growing interest in large-scale resource sharing with emerging architectures such as cloud computing, where globally distributed and commoditized resources can be shared and traded. Federated clouds, a topic of recent interest, aims to integrate different types of cloud resources from different providers, to increase scalability and reliability. In federated clouds, users are rational and maximize their own interest when consuming and contributing shared resources, while globally distributed resource supply and demand changes as users join and leave the cloud dynamically over time. In this paper, we propose a dynamic pricing scheme for multiple types of shared resources in federated clouds and evaluate its performance. Fixed pricing, currently used by cloud providers, does not reflect the dynamic resource price due to the changes in supply and demand. Using simulations, we compare the economic and computational efficiencies of our proposed dynamic pricing scheme with fixed pricing. We show that the user utility is increased, while the percentage of successful buyer requests and the percentage of allocated seller resources is higher with dynamic pricing.

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“…Several market-based allocation systems for grids, such as Sorma [16] and Nimrod/G [3], use bargaining or negotiation to determine the resource price. The advantage of this approach is that sellers and buyers communicate directly, without a third party mediating an allocation.…”

Section: Related Workmentioning

confidence: 99%

A Distributed Market Framework for Large-Scale Resource Sharing

Mihailescu

Teo

2010

Euro-Par 2010 - Parallel Processing

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Abstract. Current distributed computing infrastructures, such as peerto-peer networks, grids, and more recently clouds, make sharing and trading resources ubiquitous. In these large distributed systems, rational users are both providers and consumers of resources. Currently, there is growing interest in exploiting economic models for the allocation of shared computing resources that incentivize rational users. However, when the number of resource types and users increases, computational complexity of the allocation algorithms grows rapidly and efficiency deteriorates. In this paper, we propose a scalable distributed market framework for the allocation of shared resources in large distributed systems. We use mechanism design to create a pricing scheme that allocates a request for multiple resource types, by trading economic efficiency for computational efficiency, strategy-proof and budget-balance. To address scalability, our proposed framework leverages on a peer-to-peer overlay for resource discovery and management. We prototype our framework using FreePastry, a popular overlay network based on the Pastry protocol. We show that our scheme is efficient and scalable using both simulation experiments and results from the deployment on PlantLab.

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SORMA – Business Cases for an Open Grid Market: Concept and Implementation

Cited by 18 publications

References 18 publications

Research of Resource Allocation in Cloud Computing Based on Improved Dual Bee Colony Algorithm

Research of Resource Allocation in Cloud Computing Based on Improved Dual Bee Colony Algorithm

Strategy-Proof Dynamic Resource Pricing of Multiple Resource Types on Federated Clouds

A Distributed Market Framework for Large-Scale Resource Sharing

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