article

Scheduling strategies for optimal service deployment across multiple clouds

Authors:

Jose Luis Lucas-Simarro,

Rafael Moreno-Vozmediano,

Ruben S. Montero,

Ignacio M. LlorenteAuthors Info & Claims

Future Generation Computer Systems, Volume 29, Issue 6

Pages 1431 - 1441

https://doi.org/10.1016/j.future.2012.01.007

Published: 01 August 2013 Publication History

Abstract

The current cloud market, constituted by many different public cloud providers, is highly fragmented in terms of interfaces, pricing schemes, virtual machine offers and value-added features. In this context, a cloud broker can provide intermediation and aggregation capabilities to enable users to deploy their virtual infrastructures across multiple clouds. However, most current cloud brokers do not provide advanced service management capabilities to make automatic decisions, based on optimization algorithms, about how to select the optimal cloud to deploy a service, how to distribute optimally the different components of a service among different clouds, or even when to move a given service component from a cloud to another to satisfy some optimization criteria. In this paper we present a modular broker architecture that can work with different scheduling strategies for optimal deployment of virtual services across multiple clouds, based on different optimization criteria (e.g. cost optimization or performance optimization), different user constraints (e.g. budget, performance, instance types, placement, reallocation or load balancing constraints), and different environmental conditions (i.e., static vs. dynamic conditions, regarding instance prices, instance types, service workload, etc.). To probe the benefits of this broker, we analyse the deployment of different clustered services (an HPC cluster and a Web server cluster) on a multi-cloud environment under different conditions, constraints, and optimization criteria.

References

[1]

R. Buyya, C.S. Yeo, S. Venugopal, Market-oriented cloud computing: vision, hype, and reality for delivering it services as computing utilities, in: High Performance Computing and Communications, 2008, HPCC'08, 10th IEEE International Conference on, 2008, pp. 5-13.

[2]

Amazon elastic compute cloud, EC2, December 2011. URL: http://aws.amazon.com/ec2/.

[3]

Gogrid home page, December 2011. URL: http://www.gogrid.com/.

[4]

Rackspace hosting, December 2011. URL: http://www.rackspace.com/.

[5]

Sotomayor, B., Montero, R., Llorente, I. and Foster, I., Virtual infrastructure management in private and hybrid clouds. IEEE Internet Computing. v13 i5. 14-22.

[6]

D. Nurmi, R. Wolski, C. Grzegoczyk, The eucalyptus open-source cloud-computing system, in: Proceedings of Cloud Computing and its Applications. URL: http://www.cca08.org/papers/Paper32-Daniel-Nurmi.pdf.

[7]

Open stack open source cloud computing software, December 2011. URL: http://www.openstack.org/.

[8]

VMware virtualization software for desktops, servers and virtual machines for a private cloud, December 2011. URL: http://www.vmware.com/.

[9]

Mateescu, G., Gentzsch, W. and Ribbens, C.J., Hy brid computing: where HPC meets grid and cloud computing. Future Generation Computer Systems. v27 i5. 440-453.

[10]

Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J. and Brandic, I., Cloud computing and emerging it platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Generation Computer Systems. v25 i6. 599-616.

[11]

Ferrer, A.J., Optimis: a holistic approach to cloud service provisioning. Future Generation Computer Systems. v28 i1. 66-77.

[12]

Tordsson, J., Montero, R.S., Moreno-Vozmediano, R. and Llorente, I.M., Cloud brokering mechanisms for optimized placement of virtual machines across multiple providers. Future Generation Computer Systems. v28 i2. 358-367.

[13]

Announcing the AWS Asia Pacific (Singapore) region, April 2010. URL: http://aws.amazon.com/about-aws/whats-new/2010/04/29/announcing-asia-pacific-singapore-region/.

[14]

Announcing GPU instances for Amazon EC2, November 2010. URL: http://aws.amazon.com/es/about-aws/whats-new/2010/11/15/announcing-cluster-gpu-instances-for-amazon-ec2/.

[15]

Announcing micro instances for Amazon EC2, September 2010. URL: http://aws.amazon.com/es/about-aws/whats-new/2010/09/09/announcing-micro-instances-for-amazon-ec2/.

[16]

S. Yi, D. Kondo, A. Andrzejak, Reducing costs of spot instances via checkpointing in the Amazon elastic compute cloud, in: Cloud Computing, IEEE International Conference on, vol. 0, 2010, pp. 236-243.

[17]

Cloud computing brokers: a resource guide, December 2011. URL:http://www.datacenterknowledge.com/archives/2010/01/22/cloud-computing-brokers-a-resource-guide/.

[18]

RightScale home page, December 2011. URL: http://www.rightscale.com/.

[19]

SpotCloud home page, December 2011. URL: http://www.spotcloud.com/.

[20]

Aeolus home page, December 2011. URL: http://www.aeolusproject.org/index.html.

[21]

S. Chaisiri, B.-S. Lee, D. Niyato, Optimal virtual machine placement across multiple cloud providers, in: Services Computing Conference, 2009, APSCC 2009, IEEE Asia-Pacific, 2009, pp. 103-110.

[22]

Andreolini, M., Casolari, S., Colajanni, M. and Messori, M., Dynamic load management of virtual machines in cloud architectures. In: Lecture Notes of the Institute for Computer Sciences, vol. 34. pp. 201-214.

[23]

E. Elmroth, F. Marquez, D. Henriksson, D. Ferrera, Accounting and billing for federated cloud infrastructures, in: Grid and Cooperative Computing, 2009, GCC'09, Eighth International Conference on, 2009, pp. 268-275.

[24]

Rochwerger, B., Breitgand, D., Levy, E., Galis, A., Nagin, K., Llorente, I.M., Montero, R., Wolfsthal, Y., Elmroth, E., Caceres, J., Ben-Yehuda, M., Emmerich, W. and Galan, F., The reservoir model and architecture for open federated cloud computing. IBM Journal of Research and Development. v53 i4. 4:1-4:11.

Digital Library

[25]

J.L. Lucas-Simarro, R. Moreno-Vozmediano, R.S. Montero, I.M. Llorente, Dynamic placement of virtual machines for cost optimization in multi-cloud environments, in: Proceedings of the 2011 International Conference on High Performance Computing and Simulation, HPCS 2011, 2011, pp. 1-7.

[26]

Delta cloud home page, December 2011. URL: http://deltacloud.org/.

[27]

A modeling language for mathematical programming. Management Science. v36 i5. 519-554.

[28]

AMPL solvers, December 2011. URL: http://www.ampl.com/solvers.html.

[29]

Ostermann, S., Iosup, A., Yigitbasi, N., Prodan, R., Fahringer, T. and Epema, D., A performance analysis of EC2 cloud computing services for scientific computing. In: Lecture Notes of the Institute for Computer Sciences, vol. 34. pp. 115-131.

[30]

Moreno-Vozmediano, R., Montero, R. and Llorente, I., Multicloud deployment of computing clusters for loosely coupled MTC applications. IEEE Transactions on Parallel and Distributed Systems. v22 i6. 924-930.

[31]

Montero, R., Moreno-Vozmediano, R. and Llorente, I., An elasticity model for high throughput computing clusters. Journal of Parallel and Distributed Computing. v71 i6. 750-757.

[32]

Dongarra, J., Luszczek, P. and Petitet, A., The linpack benchmark: past, present, and future. Concurrency and Computation: Practice and Experience. v15.

[33]

Moreno-Vozmediano, R., Montero, R. and Llorente, I., Elastic management of web server clusters on distributed virtual infrastructures. Concurrency and Computation: Practice and Experience. v23 i13. 1474-1490.

[34]

Nginx web server, December 2011. URL: http://nginx.org/.

[35]

Httperf home page, December 2011. URL: http://www.hpl.hp.com/research/linux/httperf/.

Cited By

Cotroneo DNatella RRosiello S(2024)DRACOJournal of Parallel and Distributed Computing10.1016/j.jpdc.2024.104935192:COnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.jpdc.2024.104935
Kholdi EBabamir S(2024)Reserve policy-aware VM positioning based on prediction in multi-cloud environmentThe Journal of Supercomputing10.1007/s11227-024-06349-680:16(23736-23766)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1007/s11227-024-06349-6
Li XPan LLiu S(2023)A DRL-based online VM scheduler for cost optimization in cloud brokersWorld Wide Web10.1007/s11280-023-01145-326:5(2399-2425)Online publication date: 14-Mar-2023
https://dl.acm.org/doi/10.1007/s11280-023-01145-3
Show More Cited By

Scheduling strategies for optimal service deployment across multiple clouds

Recommendations

On-Demand Optimal Cloud Service Provisioning Composition across Multi-cloud
ICCIS '13: Proceedings of the 2013 International Conference on Computational and Information Sciences

The current cloud environment, constituted by many different public cloud providers, is highly independent in terms of pricing models, interfaces and virtualization standard while the ideal cloud environment is homogenous and standardization. In this ...
Managing elasticity across multiple cloud providers
MultiCloud '13: Proceedings of the 2013 international workshop on Multi-cloud applications and federated clouds

In the context of cloud computing, elasticity is the capacity to scale computing resources up and down easily. Currently, most Platforms as a Service (PaaS) manage application elasticity within a single cloud provider. However, the not so infrequent ...
Enhancing Federated Cloud Management with an Integrated Service Monitoring Approach

Cloud Computing enables the construction and the provisioning of virtualized service-based applications in a simple and cost effective outsourcing to dynamic service environments. Cloud Federations envisage a distributed, heterogeneous environment ...

Comments

Information & Contributors

Information

Published In

cover image Future Generation Computer Systems

Future Generation Computer Systems Volume 29, Issue 6

August, 2013

324 pages

ISSN:0167-739X

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2012.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 August 2013

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

48
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 08 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Cotroneo DNatella RRosiello S(2024)DRACOJournal of Parallel and Distributed Computing10.1016/j.jpdc.2024.104935192:COnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.jpdc.2024.104935
Kholdi EBabamir S(2024)Reserve policy-aware VM positioning based on prediction in multi-cloud environmentThe Journal of Supercomputing10.1007/s11227-024-06349-680:16(23736-23766)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1007/s11227-024-06349-6
Li XPan LLiu S(2023)A DRL-based online VM scheduler for cost optimization in cloud brokersWorld Wide Web10.1007/s11280-023-01145-326:5(2399-2425)Online publication date: 14-Mar-2023
https://dl.acm.org/doi/10.1007/s11280-023-01145-3
Melissaris TNabar KRadut RRehmtulla SShi AChandrashekar SPapapanagiotou IGavrilovska AAltınbüken DBinnig C(2022)Elastic cloud servicesProceedings of the 13th Symposium on Cloud Computing10.1145/3542929.3563483(142-157)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3542929.3563483
Aron RAbraham A(2022)Resource scheduling methods for cloud computing environmentEngineering Applications of Artificial Intelligence10.1016/j.engappai.2022.105345116:COnline publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1016/j.engappai.2022.105345
Hedhli AMezni H(2021)A Survey of Service Placement in Cloud EnvironmentsJournal of Grid Computing10.1007/s10723-021-09565-z19:3Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/s10723-021-09565-z
Khan M(2020)Optimized hybrid service brokering for multi-cloud architecturesThe Journal of Supercomputing10.1007/s11227-019-03048-576:1(666-687)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1007/s11227-019-03048-5
Kirthica SSaravanan ISridhar R(2020)Enhancing the Cloud Inter-operation Toolkit (CIT) to Support Multiple Cloud Service ModelsJournal of Grid Computing10.1007/s10723-020-09516-018:3(419-439)Online publication date: 1-Sep-2020
https://dl.acm.org/doi/10.1007/s10723-020-09516-0
Talebian HGani ASookhak MAbdelatif AYousafzai AVasilakos AYu F(2020)Optimizing virtual machine placement in IaaS data centers: taxonomy, review and open issuesCluster Computing10.1007/s10586-019-02954-w23:2(837-878)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s10586-019-02954-w
Verba NChao KLewandowski JShah NJames ATian F(2019)Modeling industry 4.0 based fog computing environments for application analysis and deploymentFuture Generation Computer Systems10.1016/j.future.2018.08.04391:C(48-60)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1016/j.future.2018.08.043
Show More Cited By

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents