A Cloud Computing Resource Pricing Strategy Research-Based on Resource Swarm Algorithm

Hao Li; Yu Pu; Joan Lu

doi:10.1109/CSSS.2012.551

A Cloud Computing Resource Pricing Strategy Research-Based on Resource Swarm Algorithm

Hao Li, Yu Pu, Joan Lu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

Cloud computing arise as an efficient way to allocate resources for execution of task and services within a set of geographically dispersed providers from different organizations. In cloud computing, an IaaS computing model called Cloud Bank. Cloud Bank model [1] is an IaaS model on the basis of economics principal and cloud computing features. It can be partly distinguished from other traditional IaaS providers by the sources of infrastructure resources. In Cloud Bank, pricing resources is the key problem. Client applications and services providers meet in Cloud Bank and negotiate for the sales of services by means of the signature of a service level agreement. This paper come up with a resource pricing strategy based on Resource Swarm Optimization to solve the problem of how to price computing resources in Cloud Bank model.

Original language	English
Title of host publication	Proceedings - 2012 International Conference on Computer Science and Service System, CSSS 2012
Publisher	IEEE
Pages	2217-2222
Number of pages	6
ISBN (Electronic)	9780769547190
ISBN (Print)	9781467307215
DOIs	https://doi.org/10.1109/CSSS.2012.551
Publication status	Published - 31 Dec 2012
Event	2012 International Conference on Computer Science and Service System - Nanjing, China Duration: 11 Aug 2012 → 13 Aug 2012

Conference

Conference	2012 International Conference on Computer Science and Service System
Abbreviated title	CSSS2012
Country/Territory	China
City	Nanjing
Period	11/08/12 → 13/08/12

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title = "A Cloud Computing Resource Pricing Strategy Research-Based on Resource Swarm Algorithm",

abstract = "Cloud computing arise as an efficient way to allocate resources for execution of task and services within a set of geographically dispersed providers from different organizations. In cloud computing, an IaaS computing model called Cloud Bank. Cloud Bank model [1] is an IaaS model on the basis of economics principal and cloud computing features. It can be partly distinguished from other traditional IaaS providers by the sources of infrastructure resources. In Cloud Bank, pricing resources is the key problem. Client applications and services providers meet in Cloud Bank and negotiate for the sales of services by means of the signature of a service level agreement. This paper come up with a resource pricing strategy based on Resource Swarm Optimization to solve the problem of how to price computing resources in Cloud Bank model.",

keywords = "Cloud Bank model, IaaS, Resource Swarm Optimization, pricing, computational modeling, cloud computing, algorithm design and analysis, equations, mathematical model, vectors",

author = "Hao Li and Yu Pu and Joan Lu",

year = "2012",

month = dec,

day = "31",

doi = "10.1109/CSSS.2012.551",

language = "English",

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pages = "2217--2222",

booktitle = "Proceedings - 2012 International Conference on Computer Science and Service System, CSSS 2012",

publisher = "IEEE",

address = "United States",

note = "2012 International Conference on Computer Science and Service System, CSSS2012 ; Conference date: 11-08-2012 Through 13-08-2012",

}

Li, H, Pu, Y & Lu, J 2012, A Cloud Computing Resource Pricing Strategy Research-Based on Resource Swarm Algorithm. in Proceedings - 2012 International Conference on Computer Science and Service System, CSSS 2012., 6394869, IEEE, pp. 2217-2222, 2012 International Conference on Computer Science and Service System, Nanjing, China, 11/08/12. https://doi.org/10.1109/CSSS.2012.551

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T1 - A Cloud Computing Resource Pricing Strategy Research-Based on Resource Swarm Algorithm

AU - Li, Hao

AU - Pu, Yu

AU - Lu, Joan

PY - 2012/12/31

Y1 - 2012/12/31

N2 - Cloud computing arise as an efficient way to allocate resources for execution of task and services within a set of geographically dispersed providers from different organizations. In cloud computing, an IaaS computing model called Cloud Bank. Cloud Bank model [1] is an IaaS model on the basis of economics principal and cloud computing features. It can be partly distinguished from other traditional IaaS providers by the sources of infrastructure resources. In Cloud Bank, pricing resources is the key problem. Client applications and services providers meet in Cloud Bank and negotiate for the sales of services by means of the signature of a service level agreement. This paper come up with a resource pricing strategy based on Resource Swarm Optimization to solve the problem of how to price computing resources in Cloud Bank model.

AB - Cloud computing arise as an efficient way to allocate resources for execution of task and services within a set of geographically dispersed providers from different organizations. In cloud computing, an IaaS computing model called Cloud Bank. Cloud Bank model [1] is an IaaS model on the basis of economics principal and cloud computing features. It can be partly distinguished from other traditional IaaS providers by the sources of infrastructure resources. In Cloud Bank, pricing resources is the key problem. Client applications and services providers meet in Cloud Bank and negotiate for the sales of services by means of the signature of a service level agreement. This paper come up with a resource pricing strategy based on Resource Swarm Optimization to solve the problem of how to price computing resources in Cloud Bank model.

KW - Cloud Bank model

KW - IaaS

KW - Resource Swarm Optimization

KW - pricing

KW - computational modeling

KW - cloud computing

KW - algorithm design and analysis

KW - equations

KW - mathematical model

KW - vectors

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BT - Proceedings - 2012 International Conference on Computer Science and Service System, CSSS 2012

PB - IEEE

T2 - 2012 International Conference on Computer Science and Service System

Y2 - 11 August 2012 through 13 August 2012

ER -

A Cloud Computing Resource Pricing Strategy Research-Based on Resource Swarm Algorithm

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