http://www.cnr.it/ontology/cnr/individuo/prodotto/ID294526
Service provisioning through opportunistic computing in mobile clouds (Contributo in atti di convegno)
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- Service provisioning through opportunistic computing in mobile clouds (Contributo in atti di convegno) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
- Alternative label
Davide Mascitti, Marco Conti, Andrea Passarella, Laura Ricci (2014)
Service provisioning through opportunistic computing in mobile clouds
in Fourth International Conference on Selected Topics in Mobile & Wireless Networking (MoWNet'2014), Roma
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Davide Mascitti, Marco Conti, Andrea Passarella, Laura Ricci (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- IIT-CNR, University of Pisa (literal)
- Titolo
- Service provisioning through opportunistic computing in mobile clouds (literal)
- Abstract
- Mobile clouds are a new paradigm enabling mobile users to access the heterogeneous services present in a pervasive mobileenvironment together with the rich service offers of the cloud infrastructures. In mobile computing environments mobile devicescan also act as service providers, using approaches conceptually similar to service-oriented models. Many approaches implementservice provisioning between mobile devices with the intervention of cloud-based handlers, with mobility playing a disruptiverole to the functionality offered by of the system. In our approach, we exploit the opportunistic computing model, whereby mobiledevices exploit direct contacts to provide services to each other, without necessarily go through conventional cloud services residingin the Internet. Conventional cloud services are therefore complemented by a mobile cloud formed directly by the mobile devices.This paper exploits an algorithm for service selection and composition in this type of mobile cloud environments able to estimatethe execution time of a service composition. The model enables the system to produce an estimate of the execution time of thealternative compositions that can be exploited to solve a user's request and then choose the best one among them. We comparethe performance of our algorithm with alternative strategies, showing its superior performance from a number of standpoints. Inparticular, we show how our algorithm can manage a higher load of requests without causing instability in the system converselyto the other strategies. When the load of requests is manageable for all strategies, our algorithm can achieve up to 75% less timespent in average to solve requests. (literal)
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