Abstract
The area of storage solutions is becoming more and more heterogeneous. Even in the case of relational databases, there are several offerings, which differ from vendor to vendor and are offered for different deployments like on-premises or in the Cloud, as Platform-as-a-Service (PaaS) or as a special Virtual Machine on the Infrastructure-as-a-Service (IaaS) level. Beyond traditional relational databases, the NoSQL idea has gained a lot of attraction. Indeed, there are various services and products available from several providers. Each storage solution has virtues of its own even within the same product category for certain aspects. For example, some systems are offered as cloud services and pursue a pay-as-you-go principle without upfront investments or license costs. Others can be installed on premises, thus achieving higher privacy and security. Some store redundantly to achieve high reliability for higher costs. This paper suggests a multi-criteria approach for finding appropriate storage for large objects. Large objects might be, for instance, images of virtual machines, high resolution analysis images, or consumer videos. Multi-criteria means that individual storage requirements can be attached to objects and containers having the overall goal in mind to relieve applications from the burden to find corresponding appropriate storage systems. For efficient storage and retrieval, a metadata-based approach is presented that relies on an association with storage objects and containers. The heterogeneity of involved systems and their interfaces is handled by a federation approach that allows for transparent usage of several storages in parallel. All together applications benefit from the specific advantages of particular storage solutions for specific problems. In particular, the paper presents the required extensions for an object storage developed by the VISION Cloud project.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abu-Libdeh, H., Princehouse, L., Weatherspoon, H.: RACS: a case for cloud storage diversity. In: Proceedings of the 1st ACM Symposium on Cloud Computing, SoCC 2010, pp. 229–240. ACM, New York (2010)
Apache Libcloud: a unified interface to the cloud. http://libcloud.apache.org/. Accessed 15 Nov 2017
Bermbach, D., Klems, M., Tai, S., Menzel, M.: Metastorage: a federated cloud storage system to manage consistency-latency tradeoffs. In: Proceedings of the 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011, pp. 452–459. IEEE Computer Society, Washington, DC (2011)
Brantner, M., Florescu, D., Graf, D., Kossmann, D., Kraska, T.: Building a database on S3. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, p. 251 (2008)
Broberg, J., Buyya, R., Tari, Z.: Creating a ‘Cloud Storage’ mashup for high performance, low cost content delivery. In: Feuerlicht, G., Lamersdorf, W. (eds.) ICSOC 2008. LNCS, vol. 5472, pp. 178–183. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-01247-1_17
Bunch, C., et al.: An evaluation of distributed datastores using the appscale cloud platform. In: Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing, CLOUD 2010, pp. 305–312. IEEE Computer Society, Washington, DC (2010)
CDMI: Cloud data management interface version 1.1.1. https://www.snia.org/sites/default/files/CDMI_Spec_v1.1.1.pdf. Accessed 15 Nov 2017
CloudSwitch Homepage. http://www.cloudswitch.com. Accessed 15 Nov 2017
Deltacloud Homepage. http://deltacloud.apache.org/. Accessed 15 Nov 2017
Fielding, R., Taylor, R.: Principled design of the modern web architecture. ACM Trans. Internet Technol. 2(2), 115–150 (2002)
Fox, A., et al.: Above the clouds: a Berkeley view of cloud computing. Report UCB/EECS, 28, Department of Electrical Engineering and Computer Sciences, University of California, Berkeley (2009)
Gogouvitis, S.V., Katsaros, G., Kyriazis, D., Voulodimos, A., Talyansky, R., Varvarigou, T.: Retrieving, storing, correlating and distributing information for cloud management. In: Vanmechelen, K., Altmann, J., Rana, O.F. (eds.) GECON 2012. LNCS, vol. 7714, pp. 114–124. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35194-5_9
Hohenstein, U., Jaeger, M., Dippl, S., Bahar, E., Vernik, G., Kolodner, E.: An approach for hybrid clouds using vision cloud federation. In: 5th International Conference on Cloud Computing, GRIDs, and Virtualization (Cloud Computing), Venice, pp. 100–107 (2014)
Hohenstein, U., Jaeger, M., Gogouvitis, S.: A multi-criteria approach for large-object cloud storage. In: 6th International Conference on Data Science, Technology and Applications (DATA 2017), Madrid, Spain, pp. 75–86 (2017)
Jaeger, M.C., Messina, A., Lorenz, M., Gogouvitis, S.V., Kyriazis, D., Kolodner, E.K., Suk, X., Bahar, E.: Cloud-based content centric storage for large systems. In: Proceedings of Federated Conference on Computer Science and Information Systems - FedCSIS 2012, Wroclaw, Poland, 9–12 September 2012, pp. 987–994 (2012)
Kolodner, E., et al.: A cloud environment for data intensive storage services. In: CloudCom, pp. 357–366 (2011)
Kolodner, E., et al.: Data intensive storage services on clouds: limitations, challenges and enablers. In: Petcu, D., Vazquez-Poletti, J. (eds.) European Research Activities in Cloud Computing, pp. 68–96. Cambridge Scholars Publishing, New Castle upon Tyne (2011)
Mell, P., Grance, T.: The NIST definition of cloud computing. NIST special publication 800-145, Sept 2011
Nasuni Homepage. http://www.nasuni.com/. Accessed 15 Nov 2017
Nimbula Homepage. http://en.wikipedia.org/wiki/Nimbula. Accessed 15 Nov 2017
Nirvanix Homepage. http://www.nirvanix.com/products-services/cloudcomplete-hybrid-cloud-storage/index.aspx. Accessed 15 Nov 2017
NoSQL databases. http://nosql-database.org. Accessed 15 Nov 2017
Sandalage, P., Fowler, M.: NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence. Pearson Education, Upper Saddle River (2013)
Sheth, A., Larson, J.: Federated database systems for managing distributed, heterogeneous, and autonomous databases. ACM Comput. Surv. 22(3), 183–236 (1990)
SmeStorage Homepage. https://code.google.com/p/smestorage. Accessed 15 Nov 2017
Vernik, G., et al.: Data on-boarding in federated storage clouds. In: Proceedings of the 2013 IEEE Sixth International Conference on Cloud Computing, CLOUD 2013, pp. 244–251. IEEE Computer Society, Washington, DC (2013)
VISION-Cloud project consortium: high level architectural specification release 1.0, vision cloud project deliverable D10.2, June 2011. http://www.visioncloud.com. Accessed 15 May 2017
VISION-Cloud project consortium: data access layer: design and open specification release 2.0, deliverable D30.3b, Sept 2012. http://www.visioncloud.com/. Accessed 15 May 2017
Junker, U.: QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems. In: Proceedings of the 19th National Conference on Artificial Intelligence (AAAI 2004), pp. 167–172 (2004)
ZeroMQ. http://zeromq.org/. Accessed 15 Nov 2017
Acknowledgements
The research leading to the results presented in this paper has partially received funding from the European Union’s Seventh Framework Programme (FP7 2007-2013) Project VISION Cloud under grant agreement number 217019 and is accordingly based on its deliverables and research publications as citations have pointed out.
Author information
Authors and Affiliations
Corresponding authors
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
Hohenstein, U., Gogouvitis, S.V., Jaeger, M.C. (2018). Determining Appropriate Large Object Stores with a Multi-criteria Approach. In: Filipe, J., Bernardino, J., Quix, C. (eds) Data Management Technologies and Applications. DATA 2017. Communications in Computer and Information Science, vol 814. Springer, Cham. https://doi.org/10.1007/978-3-319-94809-6_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-94809-6_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-94808-9
Online ISBN: 978-3-319-94809-6
eBook Packages: Computer ScienceComputer Science (R0)