Improving data locality in P2P-based fog computing platforms

Procedia Computer Science

Volumn 141, Issue , 2018, Pages 72-79

  Steffenel, Luiz Angelo ^a   Pinheiro, Manuele Kirsch ^b  

^a UNIVERSITÉ DE REIMS CHAMPAGNE ARDENNE   (France)

^b UNIVERSITÉ PARIS 1 PANTHÉON SORBONNE   (France)

Author keywords

Big data; Data locality; Distributed hash table; Fog computing; P2P overlay

Indexed keywords

BIG DATA; DATA COMMUNICATION SYSTEMS; FOG; INFORMATION MANAGEMENT; SCHEDULING;

COMMUNICATION LATENCY; COMPUTING PLATFORM; COMPUTING SERVICES; COMPUTING-TASK; DATA LOCALITY; DISTRIBUTED HASH TABLE; LOCATION-AWARE; P2P OVERLAYS;

FOG COMPUTING;

EID: 85058342116     PISSN: None     EISSN: 18770509     Source Type: Conference Proceeding    
DOI: 10.1016/j.procs.2018.10.151     Document Type: Conference Paper

References (32)

1. Baldauf, M., Dustdar, S., Rosenberg, F., 2007. A survey on context-aware systems. International Journal of Ad Hoc and Ubiquitous Computing 2, 263-277. doi:10.1504/IJAHUC.2007.014070.
2. Ben Brahim, M., Drira, W., Filali, F., Hamdi, N., 2016. Spatial data extension for cassandra nosql database. Journal of Big Data 3, 11. URL: https://doi.org/10.1186/s40537-016-0045-4, doi:10.1186/s40537-016-0045-4.
3. Bonomi, F., Milito, R., Zhu, J., Addepalli, S., 2012. Fog computing and its role in the internet of things, in: Proceedings of the 1st MCC Workshop on Mobile Cloud Computing, ACM, New York, NY, USA. pp. 13-16. doi:10.1145/2342509.2342513.
4. Cisco,. Cisco iox. URL: https://developer.cisco.com/site/iox/docs/.
5. Cisco Research Center Requests for Proposals (RFPs),. Fog computing, ecosystem, architecture and applications. http://www.cisco.com/ web/about/ac50/ac207/crc-new/university/RFP/rfp13078.html.
6. Consortium, O., 2017. Openfog reference architecture. https://www.openfogconsortium.org/ra/.
7. Dey, A., 2001. Understanding and using context. Personal and Ubiquitous Computing 5, 4-7.
8. Dey, S., Mukherjee, A., Paul, H.S., Pal, A., 2013. Challenges of using edge devices in iot computation grids, in: Int. Conf. on Parallel and Distributed Systems, pp. 564-569. doi:http://doi.ieeecomputersociety.org/10.1109/ICPADS.2013.101.
9. Elkhatib, Y., Porter, B., Ribeiro, H.B., Zhani, M.F., Qadir, J., Riviere, E., 2017. On using micro-clouds to deliver the fog. IEEE Internet Computing 21, 8-15. doi:doi.ieeecomputersociety.org/10.1109/MIC.2017.35.
10. ETSI,. Mobile-edge computing-introductory technical white paper. https://portal.etsi.org/.
11. Fazio, M., Celesti, A., Puliafito, A., Villari, M., 2015. Big data storage in the cloud for smart environment monitoring. Procedia Computer Science 52, 500-506. doi:10.1016/j.procs.2015.05.023. the 6th International Conference on Ambient Systems, Networks and Technologies (ANT-2015).
12. Fox, A., Eichelberger, C., Hughes, J., Lyon, S., 2013. Spatio-temporal indexing in nonrelational distributed databases, in: IEEE International Conference in Big Data, pp. 291-299.
13. Freepastry, 2012. http://freepastry.rice.edu.
14. Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M., 2013. Internet of things (iot): A vision, architectural elements, and future directions. Future Generation Computer Systems 29, 1645-1660. doi:http://dx.doi.org/10.1016/j.future.2013.01.010.
15. Hao, Z., Novak, E., Yi, S., Li, Q., 2017. Challenges and software architecture for fog computing. IEEE Internet Computing 21, 44-53. doi:doi.ieeecomputersociety.org/10.1109/MIC.2017.26.
16. Hu, S.Y., Chen, J.F., Chen, T.H., 2006. Von: a scalable peer-to-peer network for virtual environments. IEEE Network 20, 22-31. doi:10. 1109/MNET.2006.1668400.
17. Parashar, M., Pierson, J.M., 2010. Pervasive grids: Challenges and opportunities, in: Li, K., Hsu, C., Yang, L., Dongarra, J., Zima, H. (Eds.), Handbook of Research on Scalable Computing Technologies. IGI Global, pp. 14-30. doi: 10.4018/978-1-60566-661-7.ch002.
18. Ratnasamy, S., Francis, P., Handley, M., Karp, R., Shenker, S., 2001. A scalable content-addressable network. ACM SIGCOMM Computer Communication Review 31, 161-172.
19. Satyanarayanan, M., Bahl, P., Caceres, R., Davies, N., 2009. The case for vm-based cloudlets in mobile computing. IEEE Pervasive Computing 8, 14-23.
20. Shekhar, S., Gokhale, A., 2017. Dynamic resource management across cloud-edge resources for performance-sensitive applications, in: 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), pp. 707-710. doi:10.1109/CCGRID.2017.120.
21. Steffenel, L., Flauzac, O., Charao, A.S., Barcelos, P.P., Stein, B., Nesmachnow, S., Pinheiro, M.K., Diaz, D., 2013. Per-mare: Adaptive deployment of mapreduce over pervasive grids, in: Proceedings of the 8th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC'13), Compiegne, France.
22. Steffenel, L.A., Kirsch Pinheiro, M., 2015. Leveraging data intensive applications on a pervasive computing platform: The case of mapreduce, in: The 6th International Conference on Ambient Systems, Networks and Technologies (ANT-2015), the 5th International Conference on Sustainable Energy Information Technology (SEIT-2015), Elsevier. pp. 1034-1039. URL: http://www.sciencedirect.com/science/ article/pii/S1877050915009023, doi:http://dx.doi.org/10.1016/j.procs.2015.05.102.
23. Steffenel, L.A., Kirsch-Pinheiro, M., 2015. When the cloud goes pervasive: approaches for IoT PaaS on a mobiquitous world, in: Springer (Ed.), EAI International Conference on Cloud, Networking for IoT systems (CN4IoT 2015), Rome, Italy. pp. 347-356.
24. Tanin, E., Harwood, A., Samet, H., 2007. Using a distributed quadtree index in peer-to-peer networks. The VLDB Journal 16, 165-178. URL: https://doi.org/10.1007/s00778-005-0001-y, doi: 10.1007/s00778-005-0001-y.
25. Vermesan, O., Friess, P., Guillemin, P., Giaffreda, R., Grindvoll, H., Eisenhauer, M., Serrano, M., Moessner, K., Spirito, M., Blystad, L.C., Tragos, E.Z., 2014. Internet of things beyond the hype: Research, innovation and deployment, in: Internet of Things-From Research and Innovation to Market Deployment. River Publishers, pp. 15-118.
26. Villari, M., Fazio, M., Dustdar, S., Rana, O., Ranjan, R., 2016. Osmotic computing: A new paradigm for edge/cloud integration. IEEE Cloud Computing 3, 76-83. doi: 10.1109/MCC.2016.124.
27. Wen, Z., Yang, R., Garraghan, P., Lin, T., Xu, J., Rovatsos, M., 2017. Fog orchestration for internet of things services. IEEE Internet Computing 21, 16-24. doi:10.1109/MIC.2017.36.
28. White, T., 2010. Hadoop: The definitive guide. 2nd edition ed., Yahoo Press, O'Reilly.
29. Willis, D.F., Dasgupt, A., Banerjee, S., 2014. Paradrop: a multi-tenant platform for dynamically installed third party services on home gateways, in: ACM SIGCOMM workshop on Distributed cloud computing, pp. 43-44.
30. Wu, D., Tian, Y., Ng, K.W., 2005. Aurelia: Building locality-preserving overlay network over heterogeneous p2p environments, in: Proc. of the International Conference on Parallel and Distributed Processing and Applications, Springer. pp. 1-8. doi: 10.1007/11576259-1.
31. Yi, S., Hao, Z., Qin, Z., Li, Q., 2015. Fog computing: Platform and applications, in: IEEE (Ed.), Third IEEE Workshop on Hot Topics in Web Systems and Technologies, pp. 73-78.
32. Zao, J.K., Gan, T.T., You, C.K., Chung, C.E., Wang, Y.T., Rodriguez Mendez, S.J., Mullen, T., Yu, C., Kothe, C., Hsiao, C.T., Chu, S.L., Shieh, C.K., Jung, T.P., 2014. Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology. Frontiers in Human Neuroscience 8, 370. URL: https://www.frontiersin.org/article/10.3389/fnhum.2014.00370, doi: 10.3389/fnhum.2014.00370.