Modeling Mobile Code Acceleration in the Cloud

Huber Flores, Xiang Su, Vassilis Kostakos, Jukka Riekki, Eemil Lagerspetz, Sasu Tarkoma, Pan Hui, Yong Li, Jukka Manner

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

5 Sitaatiot (Scopus)


The quality of service of a mobile application is critical to ensure user satisfaction. Techniques have been proposed to accomplish adaptation of quality of service dynamically. However, there is still a limited understanding about how to provide a utility model for code execution. One key challenge is modeling the level of quality in the code execution that can be provisioned by the cloud. Since the allocation of cloud resources has a cost, it is important to optimize cloud usage. We propose a software-defined networking approach that allows modeling and controlling code acceleration of a mobile application deployed across multiple type of devices. By segregating the computational requirements of the mobile application into groups, we were able to define the acceleration needed by each group of devices. As the computational requirements of a device can change across time, a mobile device can be re-assigned to another group based on demand. Our SDN approach implements a model that allows the system to predict workload based on acceleration groups. Evaluating our system in a real testbed showed that it is possible to predict workload and allocate optimal resources to handle that workload with 87.5% accuracy.

OtsikkoProceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017
ISBN (elektroninen)9781538617915
DOI - pysyväislinkit
TilaJulkaistu - 13 heinäk. 2017
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Conference on Distributed Computing Systems - Atlanta, Yhdysvallat
Kesto: 5 kesäk. 20178 kesäk. 2017
Konferenssinumero: 37


NimiInternational Conference on Distributed Computing Systems
ISSN (painettu)1063-6927


ConferenceInternational Conference on Distributed Computing Systems


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