A smart city scenario based on an efficient wireless network allows users to benefit from multimedia services in an ubiquitous, seamless and interoperable way. In this context Mobile Cloud Computing (MCC) and Heterogeneous Networks (HetNets) are viewed as infrastructures providing together a key solution for the major facing problems: the former allows to offload application to powerful remote servers, shortening execution time and extending battery life of mobile devices, while the latter allows the use of small cells in addition to macrocells, exploiting high-speed and stable connectivity in an ever grown mobile traffic trend. In this paper, we propose a technique aiming to move towards the cloud only a fraction of the computing application by minimizing a cost function, that take into account a tradeoff between energy consumption and execution time, in a non-trivial multi-objective optimization approach. The results show that when the application requires high execution and data workload and simultaneously the network is overloaded, a particular value of this percentage best fits the performance.
A partial offloading technique for wireless mobile cloud computing in smart cities / Daniela Mazza; Daniele Tarchi; Giovanni E. Corazza. - ELETTRONICO. - (2014), pp. 1-5. (Intervento presentato al convegno European Conference on Networks and Communications (EuCNC) tenutosi a Bologna, Italy nel 23-26 June 2014) [10.1109/EuCNC.2014.6882623].
A partial offloading technique for wireless mobile cloud computing in smart cities
MAZZA, DANIELA;TARCHI, DANIELE;CORAZZA, GIOVANNI EMANUELE
2014
Abstract
A smart city scenario based on an efficient wireless network allows users to benefit from multimedia services in an ubiquitous, seamless and interoperable way. In this context Mobile Cloud Computing (MCC) and Heterogeneous Networks (HetNets) are viewed as infrastructures providing together a key solution for the major facing problems: the former allows to offload application to powerful remote servers, shortening execution time and extending battery life of mobile devices, while the latter allows the use of small cells in addition to macrocells, exploiting high-speed and stable connectivity in an ever grown mobile traffic trend. In this paper, we propose a technique aiming to move towards the cloud only a fraction of the computing application by minimizing a cost function, that take into account a tradeoff between energy consumption and execution time, in a non-trivial multi-objective optimization approach. The results show that when the application requires high execution and data workload and simultaneously the network is overloaded, a particular value of this percentage best fits the performance.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
