Abstract
The addition of heterogeneous resources to conventional homogeneous cloud environments has enabled clouds to embrace a wide variety of new applications that heretofore were traditionally confined to specialized computing environments. The enhanced and extended features offered by heterogeneous resources enable service offerings that pose challenges to traditional cloud management throughout the entire service delivery stack. The accelerated uptake of heterogeneous resources is exacerbating these challenges, which no longer can be efficiently addressed in an ad-hoc manner. Therefore, an integrated approach to heterogeneous resource management that is cognizant of the unique advantages of different hardware types is needed. In this paper, two candidate approaches, a platform-integration scheme and a server-integration scheme, are introduced to address this management challenge. The platform-integration scheme integrates and coordinates the management of various coexisting resource managers and associated environments each of which may be managing resources of different types using the most appropriate resource abstraction method. In contrast, the server-integration scheme provides a single, lower level, fine-grained management mechanism across all hardware resource types. Ultimately, the goal of each schemes is to provide a unified view of resources from a capability perspective to consumers.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barr, J.: Developer Preview-EC2 Instances (F1) with Programmable Hardware. Amazon Web Services (2016)
Russinovich, M.: Inside the Microsoft FPGA-based configurable cloud. Microsoft Developer Network (MSDN) (2017)
OpenStack, L.: The openstack project (2011)
Kubernetes (2017). http://kubernetes.io/
Hindman, B., Konwinski, A., Zaharia, M., Ghodsi, A., Joseph, A.D., Katz, R., Shenker, S., Stoica, I.: Mesos: a platform for fine-grained resource sharing in the data center. In: Proceedings of the 8th USENIX Conference on Networked Systems Design and Implementation, NSDI 2011, pp. 295–308. USENIX Association, Berkeley (2011)
Merkel, D.: Docker: lightweight Linux containers for consistent development and deployment. Linux J. 2014, 2 (2014)
Turnbull, J.: The Docker Book. Lulu.com, Morrisville (2014)
OpenStack Magnum (2017). http://git.openstack.org/cgit/openstack/magnum
OpenStack Ironic (2016). https://docs.openstack.org/ironic/latest/
Dong, D., Stack, P., Xiong, H., Morrison, J.P.: Managing and unifying heterogeneous resources in cloud environments. In: Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, pp. 143–150. INSTICC, ScitePress (2017)
Popek, G.J., Goldberg, R.P.: Formal requirements for virtualizable third generation architectures. Commun. ACM 17, 412–421 (1974)
Smith, J.E., Nair, R.: The architecture of virtual machines. Computer 38, 32–38 (2005)
OpenStack: Architecture design guide. Technical report 15.0.0 (2017)
Fontán, J., Vázquez, T., Gonzalez, L., Montero, R.S., Llorente, I.: OpenNebula: the open source virtual machine manager for cluster computing. In: Open Source Grid and Cluster Software Conference, vol. 86 (2008)
OpenNebula: OpenNebula 5.2 deployment guide. Technical report 5.2.1, OpenNebula Systems (2017)
OpenNebula: OpenNebula 5.2 operation guide. Technical report 5.2.1, OpenNebula Systems (2017)
Nimbus (2017). http://www.nimbusproject.org
Keahey, K., Armstrong, P., Bresnahan, J., LaBissoniere, D., Riteau, P.: Infrastructure outsourcing in multi-cloud environment. In: Proceedings of the 2012 Workshop on Cloud Services, Federation, and the 8th Open Cirrus Summit, FederatedClouds 2012, pp. 33–38. ACM, New York (2012)
Verma, A., Pedrosa, L., Korupolu, M., Oppenheimer, D., Tune, E., Wilkes, J.: Large-scale cluster management at Google with Borg. In: Proceedings of the Tenth European Conference on Computer Systems, EuroSys 2015, pp. 18:1–18:17. ACM, New York (2015)
Schwarzkopf, M., Konwinski, A., Abd-El-Malek, M., Wilkes, J.: Omega: flexible, scalable schedulers for large compute clusters. In: Proceedings of the 8th ACM European Conference on Computer Systems, EuroSys 2013, pp. 351–364. ACM, New York (2013)
Rensin, D.K.: Kubernetes - Scheduling the Future at Cloud Scale, 1005 Gravenstein Highway North Sebastopol, CA 95472 (2015)
Burns, B., Grant, B., Oppenheimer, D., Brewer, E., Wilkes, J.: Borg, Omega, and Kubernetes. Commun. ACM 59, 50–57 (2016)
Zhang, Z., Li, C., Tao, Y., Yang, R., Tang, H., Xu, J.: Fuxi: a fault-tolerant resource management and job scheduling system at Internet scale. Proc. VLDB Endow. 7, 1393–1404 (2014)
Razor Server (2017). https://github.com/puppetlabs/razor-server
Foreman (2017). https://theforeman.org
OpenStack Neutron (2017). https://github.com/openstack/neutron
Flannel (2017). https://github.com/coreos/flannel
Weaveworks WeaveNet (2017). https://www.weave.works/docs/net/latest/introducing-weave/
Libnetwork (2017). https://github.com/docker/libnetwork
Kuryr (2017). http://docs.openstack.org/developer/kuryr/
Lynn, T., Xiong, H., Dong, D., Momani, B., Gravvanis, G., Filelis-Papadopoulos, C., Elster, A., Khan, M.M.Z.M., Tzovaras, D., Giannoutakis, K., Petcu, D., Neagul, M., Dragon, I., Kuppudayar, P., Natarajan, S., McGrath, M., Gaydadjiev, G., Becker, T., Gourinovitch, A., Kenny, D., Morrison, J.: CloudLightning: a framework for a self-organising and self-managing heterogeneous cloud. In: Proceedings of the 6th International Conference on Cloud Computing and Services Science, pp. 333–338 (2016)
Intel Embree (2017). https://embree.github.io
Benthin, C., Wald, I., Woop, S., Ernst, M., Mark, W.R.: Combining single and packet-ray tracing for arbitrary ray distributions on the Intel MIC architecture. IEEE Trans. Visual Comput. Graph. 18, 1438–1448 (2012)
Wald, I.: Fast construction of SAH BVHs on the intel many integrated core (MIC) architecture. IEEE Trans. Visual Comput. Graph. 18, 47–57 (2012)
Acknowledgment
This work is funded by the European Unions Horizon 2020 Research and Innovation Programme through the CloudLightning project under Grant Agreement Number 643946.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Dong, D., Xiong, H., Castañé, G.G., Stack, P., Morrison, J.P. (2018). Heterogeneous Resource Management and Orchestration in Cloud Environments. In: Ferguson, D., Muñoz, V., Cardoso, J., Helfert, M., Pahl, C. (eds) Cloud Computing and Service Science. CLOSER 2017. Communications in Computer and Information Science, vol 864. Springer, Cham. https://doi.org/10.1007/978-3-319-94959-8_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-94959-8_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-94958-1
Online ISBN: 978-3-319-94959-8
eBook Packages: Computer ScienceComputer Science (R0)