Abstract
Cloud computing seeks to provide a global computing utility service to a broad base of users. Resource management and scheduling are prime challenges in building such a service. In this paper, we first provide an overview of clouds from a resource management and scheduling perspective. We then discuss key challenges in these areas, describing prime opportunities for new research.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ben-Yehuda, O.A., Ben-Yehuda, M., Schuster, A., Tsafrir, D.: Deconstructing Amazon EC2 spot instance pricing. ACM Trans. Econ. Comput. 1(3), 1–20 (2013)
Carvalho, M., Cirne, W., Brasileiro, F.V., Wilkes, J.: Long-term SLOs for reclaimed cloud computing resources. In: Lazowska, E., Terry, D., Arpaci-Dusseau, R.H., Gehrke, J. (eds.) Proceedings of the ACM Symposium on Cloud Computing, pp. 20:1–20:13. ACM (2014). https://research.google.com/pubs/pub43017.html
Cycle Computing LLC, February 2017. https://cyclecomputing.com/
Di, S., Kondo, D., Cirne, W.: Characterization and comparison of cloud versus grid workloads. In: IEEE International Conference on Cluster Computing, CLUSTER 2012, pp. 230–238 (2012)
Di, S., Kondo, D., Cirne, W.: Google hostload prediction based on Bayesian model with optimized feature combination. J. Parallel Distrib. Comput. 74(1), 1820–1832 (2014)
Feitelson, G.D.: Workload Modeling for Computer Systems Performance Evaluation, 1st edn. Cambridge University Press, New York (2015)
Feitelson, D.G., Rudolph, L.: Metrics and benchmarking for parallel job scheduling. In: Feitelson, D.G., Rudolph, L. (eds.) JSSPP 1998. LNCS, vol. 1459, pp. 1–24. Springer, Heidelberg (1998). doi:10.1007/BFb0053978
Huang, H., Wang, L., Tak, B.C., Wang, L., Tang, C.: CAP3: a cloud auto-provisioning framework for parallel processing using on-demand and spot instances. In: Proceedings of the 2013 IEEE Sixth International Conference on Cloud Computing, CLOUD 2013, Washington, DC, pp. 228–235. IEEE Computer Society (2013)
Jones, C., Wilkes, J., Murphy, N., Smith, C., Beyer, B.: Service level objectives. In: Beyer, B., Jones, C., Petoff, J., Murphy, N. (eds.) Site Reliability Engineering: How Google Runs Production Systems. O’Reilly Media (2016). https://landing.google.com/sre/book.html
Mell, P., Grance, T.: The NIST definition of cloud computing. Technical report 800-145, National Institute of Standards and Technology, Gaithersburg, MD, USA (2011)
Google cloud platform: Preemptible VM instances. https://cloud.google.com/compute/docs/instances/preemptible
Tian, W., Zhao, Y.: Optimized Cloud Resource Management and Scheduling. Theory and Practice, 1st edn. Morgan Kaufmann (2014)
Google Cloud Platform: Machine types, February 2017. https://cloud.google.com/compute/docs/machine-types
Acknowledgments
We would like to acknowledge the comments and suggestions of John Wilkes and Dalibor Klusáček.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Desai, N., Cirne, W. (2017). Open Issues in Cloud Resource Management. In: Desai, N., Cirne, W. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP JSSPP 2015 2016. Lecture Notes in Computer Science(), vol 10353. Springer, Cham. https://doi.org/10.1007/978-3-319-61756-5_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-61756-5_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-61755-8
Online ISBN: 978-3-319-61756-5
eBook Packages: Computer ScienceComputer Science (R0)