Incentivising resource sharing in edge computing applications

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 10537 LNCS, Issue , 2017, Pages 204-215

  Petri, Ioan ^a   Rana, Omer F ^a   Bignell, Joseph ^a   Nepal, Surya ^b   Auluck, Nitin ^c  

^a CARDIFF UNIVERSITY   (United Kingdom)

^b CSIRO   (Australia)

^c INDIAN INSTITUTE OF TECHNOLOGY ROPAR   (India)

Author keywords

Business models; Cost; Edge computing; Micro data centres; Resource sharing

Indexed keywords

COST FUNCTIONS; COSTS; DISTRIBUTED COMPUTER SYSTEMS; ECONOMICS;

BUSINESS MODELS; CLOUD-BASED APPLICATIONS; DATA CENTRES; EDGE COMPUTING; MODELS OF COMPUTATION; PERFORMANCE LIMITATIONS; PERFORMANCE REQUIREMENTS; RESOURCE SHARING;

DIGITAL STORAGE;

EID: 85032503221     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-68066-8_16     Document Type: Conference Paper

References (11)

1. Bahl, V.: Micro datacenter middleware for mobile computing (keynote). In: ACM Middleware, Vancouver, Canada, 7–11 December 2015. http://2015. middleware-conference.org/keynote-talk-victor-bahl/. Accessed June 2017
2. Bittencourt, L., Lopes, M.M., Petri, I., Rana, O.F.: Towards virtual machine migration in fog computing. In: 10th International 3PGCIC Conference 2015, Poland, pp. 1–8, November 2015
3. Caglar, F., Shekhar, S., Gokhale, A., Koutsoukos, X.: An intelligent, performance interference-aware resource management scheme for IoT cloud backends. In: Proceedings of the 1st IEEE International Conference on Internet-of-Things: Design and Implementation, Berlin, Germany, pp. 95–105, April 2016
4. Gupta, H., Dastjerdi, A.V., Ghosh, S.K., Buyya, R.: iFogSim: a toolkit for modeling and simulation of resource management techniques in Internet of Things, edge and fog computing environments. https://arxiv.org/abs/1606.02007. Accessed June 2017
5. Noronha, A., Moriarty, R., OConnell, K., Villa, N.: Attaining IoT value: how to move from connecting things to capturing insights: gain an edge by taking analytics to the edge. Cisco White Paper (2014). http://www.cisco.com/c/dam/enus/solutions/trends/iot/docs/iot-data-analytics-white-paper.PDF. Accessed June 2017
6. Aazam, M., Huh, E.-N.: Fog computing and smart gateway based communication for cloud of things. In: International Conference on Future Internet of Things and Cloud (FiCloud), pp. 464–470. IEEE (2014)
7. Yannuzzi, M., Milito, R., Serral-Gracia, R., Montero, D., Nemirovsky, M.: Key ingredients in an IoT recipe: fog computing, cloud computing, and more fog computing. In: IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), pp. 325–329. IEEE (2014)
8. Vaquero, L.M., Rodero-Merino, L.: Finding your way in the fog: towards a comprehensive definition of fog computing. ACM SIGCOMM Comput. Commun. Rev. 44(5), 27–32 (2014)
9. Satyanarayanan, M., Bahl, P., Caceres, R., Davies, N.: The case for VM-based cloudlets in mobile computing. IEEE Pervasive Comput. Mag. 8(4), 14–23 (2009)
10. Shekhar, S., Chhokra, A., Bhattacharjee, A., Aupy, G., Gokhale, A.: INDICES: exploiting edge resources for performance-aware cloud-hosted services. In: 1st IEEE International Conference on Fog and Edge Computing (ICFEC), Madrid, Spain (2017)
11. Yi, S., Li, C., Li, Q.: A survey of fog computing: concepts, applications and issues. In: Proceedings of Workshop on Mobile Big Data, Mobidata 2015, Hangzhou, China, pp. 37–42. ACM Press (2015)