Abstract
Managing data produced in the Internet of Things according to the traditional data-center based approach is becoming no longer appropriate. Devices are improving their computational power as the processors installed on them are more and more powerful and diverse. Moreover, devices cannot guarantee a continuous connection due their mobility and limitation of battery life.
Goal of this paper is to tackle this issue focusing on data movement to eliminate the unnecessary storage, transfer and processing of datasets by concentrating only the data subsets that are relevant. A cross-layered framework is proposed to give to both applications and developers the abstracted ability to choose which aspect to optimize, based on their goals and requirements and to data providers an environment that facilitates data provisioning according to users’ needs.
Chapter PDF
Similar content being viewed by others
References
Asnar, Y., Giorgini, P., Mylopoulos, J.: Goal-driven risk assessment in requirements engineering. Requir. Eng. 16(2), 101–116 (2011)
Boru, D., Kliazovich, D., Granelli, F., Bouvry, P., Zomaya, A.Y.: Energy-efficient data replication in cloud computing datacenters. Cluster Computing 18(1), 385–402 (2015). http://dx.doi.org/10.1007/s10586-014-0404-x
Cappiello, C., Schreiber, F.A.: Quality- and energy-aware data compression by aggregation in wsn data streams. In: Proc. of the 2009 IEEE Int’l Conf. on Pervasive Computing and Communications, PERCOM 2009, pp. 1–6. IEEE Computer Society, Washington, DC (2009)
Gantz, J., Reinsel, D.: Extracting values from chaos. IDC, June 2011. http://www.emc.com/collateral/analyst-reports/idc-extracting-value-from-chaos-ar.pdf
Guyer, S.Z., Lin, C.: An annotation language for optimizing software libraries. In: Proc. of the 2nd Conf, on Domain-specific Languages, DSL 1999, pp. 39–52. ACM, New York (1999). http://doi.acm.org/10.1145/331960.331970
Heinrich, M., Grüneberger, F.J., Springer, T., Gaedke, M.: Exploiting annotations for the rapid development of collaborative web applications. In: Proc. of the 22nd Int’l Conf. on World Wide Web, WWW 2013, Rio de Janeiro, Brazil, pp. 551–560 (2013)
Kousiouris, G., Kyriazis, D., Gogouvitis, S., Menychtas, A., Konstanteli, K., Varvarigou, T.: Translation of application-level terms to resource-level attributes across the cloud stack layers. In: 2011 IEEE Symposium on Computers and Communications (ISCC), pp. 153–160, June 2011
Kousiouris, G., Menychtas, A., Kyriazis, D., Konstanteli, K., Gogouvitis, S., Katsaros, G., Varvarigou, T.: Parametric design and performance analysis of a decoupled service-oriented prediction framework based on embedded numerical software. IEEE Transactions on Services Computing 6(4), 511–524 (2013)
Nguyen, T., Cicotti, P., Bylaska, E., Quinlan, D., Baden, S.B.: Bamboo: translating mpi applications to a latency-tolerant, data-driven form. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC 2012, pp. 39:1–39:11. IEEE Computer Society Press, Los Alamitos (2012). http://dl.acm.org/citation.cfm?id=2388996.2389050
Quinlan, D., Schordan, M., Vuduc, R., Yi, Q.: Annotating user-defined abstractions for optimization. In: 20th International on Parallel and Distributed Processing Symposium, IPDPS 2006, p. 8, April 2006
Wang, R., Strong, D.: Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems 12(4), 5–33 (1996)
Ren, Y., Li, T., Yu, D., Jin, S., Robertazzi, T., Tierney, B.L., Pouyoul, E.: Protocols for wide-area data-intensive applications: design and performance issues. In: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC 2012, pp. 34:1–34:11. IEEE Computer Society Press, Los Alamitos (2012)
Tai, J., Sheng, B., Yao, Y., Mi, N.: Live data migration for reducing sla violations in multi-tiered storage systems. In: Proceedings of the 2014 IEEE International Conference on Cloud Engineering, IC2E 2014, pp. 361–366. IEEE Computer Society, Washington, DC (2014). http://dx.doi.org/10.1109/IC2E.2014.8
Vitali, M., Pernici, B., OReilly, U.M.: Learning a goal-oriented model for energy efficient adaptive applications in data centers. Information Sciences (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 IFIP International Federation for Information Processing
About this paper
Cite this paper
D’Andria, F. et al. (2015). Data Movement in the Internet of Things Domain. In: Dustdar, S., Leymann, F., Villari, M. (eds) Service Oriented and Cloud Computing. ESOCC 2015. Lecture Notes in Computer Science(), vol 9306. Springer, Cham. https://doi.org/10.1007/978-3-319-24072-5_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-24072-5_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24071-8
Online ISBN: 978-3-319-24072-5
eBook Packages: Computer ScienceComputer Science (R0)