Abstract
Energy conservation is important to protect available resources in the world. Computer technology is the same. In order to realize this idea in computer technology, renewable computing will be important. It is desirable for a computer to adopt technologies that are suitable to their era and environment in order to reduce their energy use. However, many computers used in business are large. It is difficult for them to adopt such technologies dynamically. For this reason, their computers are not capable of reducing their energy usage at this time. Therefore, we propose a computing system that adapts to environments and whose continued development will be made possible by replacing faulty and aging component in the system dynamically. A system whose components can easily be replaced will be achieved using the metabolic architecture. In this paper, we implement the two functions of self-recognition and fault awareness for a calculating unit in the system.
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
Uehara, M.: Research trends on renewable computing system. In: Reports from WReCS-2013 Workshop-IEICE TR RIS No. 8, vol. 6, pp. 1–6 (2013) (2013.10.19) (in Japanese)
Nakada, Takashi, Nakamura, Hiroshi (Eds.): Normally-Off Computing, Springer (2017)
Uehara, M.: Metabolic Computing. In: Proceedings of the 5th International Workshop on Advanced Distributed and Parallel Network Applications(ADPNA2011) in conjunction with the 14th International Conference on Network-Based Information Systems(NBiS2011), pp. 370-375 (2011) (2011.9.7-9,Tirana,Albania)
Uehara, M.: “Metabolic Computing: Toward Truly Renewable Systems”. IGI Global, Int. J. Distrib. Syst. Technol. (IJDST), 3(3), pp. 27-39 (2012) (July-September 2012)
Raspberry Pi Foundation: Raspberry Pi - Teach, Learn, and Make with Raspberry Pi. https://www.raspberrypi.org/
McKeown, Nick, et al. “OpenFlow: enabling innovation in campus networks.” ACM SIGCOMM Comput. Commun. Rev. 38(2), 69-74 (2008)
Open vSwitch: http://openvswitch.org/
Open Networking Foundation: Open Flow Switch Specification. https://www.opennetworking.org/images/stories/downloads/sdn-resources/onf-specifications/openflow/openflow-switch-v1.5.0.noipr.pdf
Ryu SDN Framework Community: Ryu SDN Framework. https://osrg.github.io/ryu/
Congdon, P.: Link Layer Discovery Protocol and MIB ver.0.0. http://www.ieee802.org/1/files/public/docs2002/lldp-protocol-00.pdf
Uehara, M., et al. : “OpenFlow Mesh for Metabolic Computing”. In: Barolli, L. (eds.) Advances on Broad-Band Wireless Computing, Communication and Applications, pp. 613-620 In: Proceedings of the 18-th International Symposium on Multimedia Network Systems and Applications (MNSA-2016) in conjunction with the 11-th International Conference On Broad-Band Wireless Computing, Communication and Applications (BWCCA-2016), (November 5–7, 2016, Soonchunhyang University, Asan, Korea)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Yasui, S., Uehara, M. (2018). Self-recognition and Fault Awareness in OpenFlow Mesh. In: Lee, R. (eds) Computational Science/Intelligence and Applied Informatics. CSII 2017. Studies in Computational Intelligence, vol 726. Springer, Cham. https://doi.org/10.1007/978-3-319-63618-4_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-63618-4_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-63617-7
Online ISBN: 978-3-319-63618-4
eBook Packages: EngineeringEngineering (R0)